Ivanti Blog: Service Management

Not All Agents Are Created Equal: Getting Agentic AI Right for IT

Wed, 08 Apr 2026 13:00:06 Z

Three months ago, a CIO told me her organization had “already deployed agents.” Her endpoint team assumed she meant the telemetry clients on every managed laptop. Her service desk thought she meant AI chatbots. Meanwhile, her security architect heard “autonomous decision-making.” They were all right and all talking past each other.

This is the agent confusion problem. It sounds like a semantics issue, but it creates real misalignment when teams try to get serious about implementing agentic AI. So, let’s untangle it.

Three types of “agents” for IT — and how they fit together

1. Endpoint agents

Endpoint agents are the lightweight clients that have run silently on managed devices for decades — collecting telemetry, executing policies, applying patches. If you run a modern endpoint management platform, they’re already across your fleet doing the quiet, continuous work. They're your infrastructure layer: always listening and reporting but not making decisions.

2. Automation bots and workflows

Automation bots and workflows handle the repetitive, structured processes IT runs on: proactive issue identification, self-healing, password resets, account unlocks, software provisioning, approval chains. These aren’t legacy limitations to apologize for. A well-built password reset bot is fast, predictable and exactly right for that job. They're your execution layer: reliable, auditable and purpose-built.

3. AI agents

AI agents are something genuinely different. Where endpoint agents collect data and automation bots execute tasks, AI agents coordinate both. Orchestrated by large language models (LLMs), they understand intent, reason across context from multiple systems, plan multi-step actions and decide when to escalate an issue that requires human expertise.

But here’s the nuance that matters: a well-designed AI agent doesn’t replace the automation bot; it calls it. When an employee asks to reset their password through a conversational interface, the AI handles the dialogue, verifies identity, applies policy logic and then triggers the existing workflow to execute. Intelligence orchestrating automation. That’s the architecture worth building toward. Add endpoint telemetry, and the picture gets richer.

Here’s what this looks like in practice:

An employee messages: “My laptop has been crawling since the last patch.”

The AI agent:

Interprets the intent, recognizes this as a performance issue potentially triggered by a recent change.
Pulls real-time CPU load, disk usage and startup process data from the endpoint layer.
Triggers a targeted remediation. Not a guess. A data-informed, auditable action.

That’s what self-healing IT looks like at the conversational layer.

What makes agentic AI for ITSM work

Getting agentic AI for IT service management right comes down to a few critical foundations.

Start with clean, current knowledge

An AI agent is only as good as what it knows and what context it has. Before enabling any agentic capability, audit your knowledge base and ask these key questions:

Is it current?
Is it tagged by use case?
Is it maintained after major changes?

Outdated knowledge leads to wrong outputs that quickly destroy employee trust. That said, these same AI agents can be used to accelerate knowledge creation, too. Every resolved ticket is a draft article. Every question the agent can't confidently answer is a knowledge gap it just surfaced for you. The agent becomes a contributor to your knowledge base, not just a consumer of it.

Provide context

Knowledge alone isn’t enough. Agents need real-time context across your entire IT environment. This includes device data from your CMDB, role and access information from HR systems and ticket history from ITSM. With this context layer, it’s possible to move from a smart-sounding bot to an agent that can close the loop.

Set governance guardrails

Having control and AI guardrails is not optional. Be deliberate about what the agent handles autonomously, what needs a human approval step and what always escalates. Having a human in the loop isn’t about being overly cautious. Rather, it’s a deliberate, intelligent design. For anything security-sensitive like MFA changes, privilege adjustments or data access requests, the agent should surface the decision, not make it unilaterally. Companies must build those thresholds from the start, not try to retrofit them later.

Change management

Even with the perfect setup, deployment fails when companies don’t consider change management.

Your service desk team needs a clear mental model of what the agent handles and where they take over. You might think of it like any other division of labor: you don't want overlap. You don't want humans burning cycles on tasks the agent can knock out instantly, and you definitely don't want the agent making calls where policy says a human needs to be in the loop. Clean boundaries keep both sides working at their highest value.

Your employees need to trust that context won’t be lost mid-conversation when an issue is escalated from agent to human. Immediately letting agents do more than foundational support is how a promising pilot becomes a painful rollback. Start narrow and earn the right to expand.

Here’s what success looks like

To prove ROI with agentic AI, organizations should focus on operational metrics that reflect real impact and can be improved through better orchestration.

Ticket deflection shows how effectively agents resolve common requests end to end without human involvement. Auto-remediation highlights when systems can diagnose issues and take approved corrective action, reducing manual effort and queue volume. Mean Time to Resolution (MTTR) reflects how much the system shortens the path from request to outcome by removing handoffs and tool switching.

Together, these metrics indicate whether agentic AI is truly reducing work, not just shifting it. But the most important measure is end-user satisfaction (CSAT). Speed without satisfaction simply creates faster friction.

The best agentic AI is invisible. Employees ask for help, get what they need, and move on without noticing the workflows, checks, or automated actions behind the scenes. Organizations that achieve success design agentic systems intentionally, with clear guardrails and a strong understanding of how autonomy reshapes operations.

Next steps

If you are evaluating the role of self‑service agentic AI in your IT ecosystem, a conversational entry point is often the most practical place to begin. Consolidating incident creation, service requests, knowledge access, and status checks into a single interface can reduce friction for employees while still respecting policies and existing workflows.

This approach lays the groundwork for a broader agentic platform. For IT leaders under pressure to do more with less, this is the moment to deliberately define how AI should operate, where autonomy adds value, and where guardrails are required.

Ready to take the next step in your agentic AI journey? Get our whitepaper for the framework, maturity model and implementation roadmap you need to succeed.

See It All or Risk It All: The Truth About IT Visibility

Mon, 06 Apr 2026 12:00:02 Z

In everyday life, ignoring what you cannot see may feel harmless. In IT, it creates a false sense of security and a costly illusion.

Although many organizations use some form of asset discovery, 2026 security research from Ivanti reveals that more than 1 in 3 IT professionals (38%) report having insufficient data about devices accessing their networks, and 45% say they lack adequate information about shadow IT. This lack of visibility leaves critical assets at risk of going undetected and unmanaged.

Yet hybrid environments now span offices, homes, clouds and data centers. As devices, identities, cloud workloads and SaaS tools move across these spaces, many of them fall outside the scope of traditional discovery methods. Unmanaged laptops linger on the network. SaaS tools are adopted without oversight. Cloud resources appear and disappear before the CMDB is updated. The result is an environment filled with assets that are present, influential and completely unseen.

The cost of partial visibility is far greater than most organizations realize. Any asset that is not tracked or understood becomes a source of risk, unplanned spending and operational inefficiency.

The scope of this challenge is clearly illustrated in Ivanti’s 2025 Securing the Borderless Digital Landscape Report:

3 in 4 IT workers say that personal device use, or BYOD, is a regular occurrence at their organization. However, just 52% of this same group say their organizations explicitly allow it.
At companies where BYOD is not permitted, 78% of employees disregard the prohibition entirely.

The issue of shadow technology is increasing even further with the exponential rise in AI use in the workplace. According to that same Ivanti study, nearly a third (32%) of people who use generative AI tools at work admit to keeping their use of AI a secret from their employer.

The good news: complete, continuous visibility is possible, and organizations that achieve complete visibility reduce operational costs, eliminate blind‑spot-driven risks and strengthen compliance readiness. Modern discovery approaches now give IT the ability to see every asset, understand its context and manage it with confidence.

The hidden costs of partial IT visibility

Many organizations assume that achieving visibility over “most” of their assets is good enough, yet when some assets are unseen and unmanaged, critical risks can be hiding right under your nose. Examples of common visibility blind spots include everything from undetected laptops that can appear intermittently on IT scanners, newly-acquired SaaS tools adopted without IT involvement, orphaned cloud workloads that never make it into the CMDB and over-provisioned identities that go unnoticed and unpremeditated.

When even a small portion of your environment remains unaccounted for, four big problems surface immediately:

1. Security weakens

Unseen or intermittently visible assets miss patches, skip scans and create openings for attackers. Blind spots slow incident response and make aligning patching priorities difficult. According to a 2026 global study from Ivanti, 38% of IT workers say inaccessible and siloed data causes difficulty tracking patch status and rollouts.

2. Compliance falters

Adding to these security challenges, that same report finds that 35% of IT organizations feel that data visibility gaps make it much more challenging for them to maintain compliance.

Audit evidence becomes fragmented across disconnected tools, spreadsheets and inboxes. Without the ability to confidently track where data lives, it becomes impossible to prove compliance.

3. Software spend leaks value

Even with SaaS management or inventory tools in place, incomplete usage and entitlement data cause overspending. Companies lose roughly 25% of their SaaS budgets to unused entitlements, redundant tools and underutilized licenses, according to Zylo’s 2025 SaaS Management Index.

Ivanti’s 2025 Technology at Work research found that nearly one in three IT workers (31%) say their organizations do not track unused/underused software licenses, possibly because they may not have a complete inventory of the total. Moreover, 39% of IT teams say that outdated hardware drives wasteful IT budget spend.

Every resource you cannot see — or cannot verify — quietly drain your budget.

4. Operations lose efficiency

Conflicting or incomplete data forces teams to recheck device information, chase outdated records and remediate issues on the wrong assets. This slows service delivery and increases rework.

Partial visibility doesn’t just obscure reality. It creates hidden risks, hidden costs and hidden delays.

Why IT visibility gaps continue to grow

Unfortunately, visibility gaps are widening for many companies. As headcounts, devices, identities and SaaS usage grow, it becomes increasingly difficult for IT teams to maintain complete visibility. Several factors contribute to growing visibility issues, including:

Shadow IT and SaaS sprawl accelerating faster than IT can keep up.
Cloud resources appearing and disappearing within minutes.
Remote and hybrid workers connecting to networks outside the corporate network.
Identity sprawl expanding across dozens of apps and platforms.
Legacy discovery tools capturing only a fraction of the environment.

These pressures compound quickly. Employees adopt convenient tools before IT can approve them. When devices, servers, or apps are created in Cloud environments and deleted in minutes, they can be missed by security checks and monitoring. As a result, these short-lived resources might not get patched or protected, creating blind spots that attackers could exploit before anyone notices. Remote workers may never even touch the corporate network. SaaS, identity and device ecosystems expand far faster than legacy discovery tools were designed to track. Without continuous, multi-source visibility, organizations fall behind almost immediately.

To close these widening gaps, organizations must shift from reactive, point‑in‑time inventories to a model built on continuous, contextual, real‑time visibility. This is where understanding and achieving true visibility over your entire IT estate becomes critical.

IT visibility is more than just an inventory

Real visibility is not a list of assets. It is complete, current and trusted intelligence that every team can act on. Total visibility requires identifying every device, SaaS app, identity, cloud workload, configuration and usage signal; no matter where it lives or how long it exists.

It also means understanding relationships: who owns an asset, what data it touches, its risk level, its compliance impact and whether it is actually being used. This is the foundation that turns discovery from information into operational control.

How complete visibility transforms workflows

Once visibility becomes continuous and contextual, the entire environment transforms. Modern IT environments require more than passive observation. As threats, workloads and assets scale at unprecedented speed, organizations need intelligent, automated actions to turn visibility into real outcomes. AI-driven insights and automated workflows empower teams to proactively address security threats, remediate issues and optimize operations without waiting for manual intervention.

With the right approach, organizations can move beyond partial visibility and finally see:

every device, application, identity and cloud workload.
normalized and reconciled data presented as a single source of truth.
vulnerabilities tied to the exact assets and owners affected.
automated workflows that trigger patching, quarantines, CMDB updates and ticket closure with proof.
discovery that spans agent, agentless, active and passive methods to cover every corner of the hybrid environment.

How every team benefits from unified asset visibility

With unified, reliable asset data, every team benefits:

Security can map exposures to real assets and respond faster.
IT operations can close the loop from discovery to remediation to verification.
Endpoint teams can enforce policies consistently.
ITAM employees can optimize spending using accurate usage and entitlement insights, eliminating waste.
Compliance teams can produce automated, audit-ready evidence without manual effort.

Achieving complete IT visibility today

This level of clarity is achievable today. By using modern discovery approaches that combine agent, agentless, active and passive methods, unified asset intelligence ensures that IT teams achieve complete visibility, even as environments become more complex and distributed.

Unified asset intelligence ingests up-to-date data from every corner of the organization, including devices, identities, SaaS applications, cloud workloads and network signals. This data is normalized and consolidated into a single, trusted source of truth.

Instead of managing partial or fragmented inventories from multiple tools, organizations gain a real-time, holistic view. Each asset is accurately represented with its key details and context, removing blind spots and allowing teams to confidently secure and manage the entire environment; eliminating guesswork, reducing risk and restoring control.

See how Ivanti Neurons for Discovery can deliver complete visibility to your environment.

How Agentic AI for ITOps Unlocks Value at Scale

Mon, 05 Jan 2026 17:00:02 Z

Here’s a paradox for the AI era: organizations are obsessed with the promise of AI as the key to unlocking productivity and enterprise transformation, and IT teams are all-in on the advantages AI and automation offer — yet those same organizations are the ones holding that transformation back.

While the majority of IT workers advocate for AI adoption, operational, cultural and budgetary barriers stand in the way of enterprises implementing AI at scale. The result: most companies today have yet to operationalize breakthrough AI and automation use cases that deliver true business value.

That’s not to say; most companies aren’t using AI — but mainly for completing lower-level tasks and boosting individual productivity. While this is an important step, enterprises will need to think bigger and longer-term to see significant ROI and digital transformation from their AI investments.

Automation and outputs vs. agentic AI autonomy

IT teams are ahead of the curve when it comes to generative AI adoption. 84% of IT professionals use generative AI tools at work, according to a 2025 Ivanti research report. That same research shows that IT professionals are also overwhelmingly positive toward AI and automation:

83% expect AI to boost productivity in the next year.
70% say it will make their work more satisfying.

Yet, for all that progress, companies aren’t tapping into the deeper potential of AI-driven technology. Many teams have mastered task-level automation (ticket routing, password resets, log summarization), but few have embraced agentic AI, which goes beyond execution to autonomous reasoning and optimization.

That gap between automation and transformation mirrors a larger problem occurring across industries. While most organizations are already using AI in some capacity, only a few have seen measurable business impact from their AI tools. McKinsey has referred to this situation as “the gen AI paradox.”

This disconnect between AI applications and ROI is further validated by an MIT report published in August 2025, which finds that a staggering 95% of organizations found zero return on generative AI despite $30-40 billion worth of investment in it.

The reason for the problem is straightforward: generative AI creates. It produces content, automates tasks, and accelerates workflows. However, it doesn’t learn, reason, or adapt on its own. The next phase of enterprise AI will be driven by systems that can interpret, predict and act dynamically: what’s now being defined as agentic AI.

Ivanti’s research further underscores the fact that most companies today have yet to integrate more complex AI use cases into their IT workflows.

While 67% of organizations automate ticket routing, fewer than one-third apply AI to root-cause analysis or other predictive use cases. This signals that most teams are still prioritizing standard automation for tasks rather than enabling systems to think and act autonomously via agentic AI.

Standard automation and generative AI tools are frequently employed by IT teams to improve individual productivity and handle low-level, repetitive tasks at greater speeds than human intervention alone. The ability to boost efficiency with less time and resources is a critical advantage of AI — particularly for strained IT teams who are always being asked to accomplish more with less. But efficiency gains are only one piece of the puzzle.

Ivanti data also reveals a deeper organizational issue: nearly half of IT teams say their organizations lack resilience — the ability to adapt quickly to change, recover from disruption and maintain business continuity without excessive manual intervention.

True enterprise agility demands autonomous and adaptive AI solutions that can anticipate problems, reason through potential solutions and continuously learn how to deliver the most optimal outcomes.

This is where many leading organizations are turning to agentic AI. Autonomous AI agents offer teams the opportunity to reshape traditional IT operations from reactive automation to proactive, goal-driven collaboration. Realizing that transforming ITOps with AI means moving from isolated automation wins to system-wide intelligence.

High-impact agentic AI use cases in ITSM and ITOps

Agentic AI is already moving the needle by reducing downtime, cutting costs and improving organizational agility.

Five high-impact use cases for agentic AI in IT follow:

1. Autonomous incident remediation

Autonomous remediation is where AI begins to move from support to strategy. In traditional IT operations, identifying and fixing an issue can take hours of human triage and escalation.

With agentic AI, those same incidents can be detected, diagnosed and resolved in real time — often before users notice any disruption.

Agentic AI doesn’t not only detect anomalies within that IT space and diagnose the root cause — it intelligently devises solutions and then executes fixes without human intervention. Moreover, machine learning enables the AI to learn from previous incidents and use this experience to continually refine and improve response efforts going forward.

2. Proactive problem prevention

Proactive problem prevention happens when AI can anticipate rather than just react to potential tech problems. Instead of solving a known issue, agentic AI continuously monitors data patterns and detects early warning signals in the form of small deviations that might evolve into service disruptions or security issues.

In other words, it moves ITOps toward proactive prevention, monitoring leading indicators and addressing issues before they become significant.

3. End-to-end lifecycle management

Autonomous AI agents will provide a more comprehensive and effective approach to asset lifecycle management.

This lifecycle view of automation extends beyond individual tickets or incidents to touch every stage of IT operations.

From onboarding new devices to patching and decommissioning outdated infrastructure, agentic AI ensures systems remain secure, compliant and cost-effective.

It not only fixes issues but also detects, diagnoses, and optimizes IT systems from provisioning to retirement. It acts as a continuous improvement engine, learning from patterns across the IT ecosystem to proactively optimize resources, streamline updates and reduce the long-term burden on IT staff.

4. Dynamic change and release management

Dynamic change and release management is where agentic AI truly shows its orchestration capabilities. In most enterprises, change management remains a high-friction process, requiring coordination across multiple teams, tools and environments.

Agentic automation transforms this by allowing AI agents to collaborate on complex workflows including cybersecurity incident response and software deployment, working together with minimal human oversight to resolve incidents, provision resources and ensure compliance.

These agents act as intelligent coordinators: synchronizing updates across systems, validating configurations and rolling back changes automatically when anomalies occur. The result is faster, safer and more predictable change cycles that free IT teams to focus on innovation rather than resource-heavy firefighting.

5. Autonomous resource and capacity management

Resource and capacity management are some of the most critical — and often overlooked — dimensions of IT performance. Using AI, companies can anticipate future resource needs by analyzing historical usage trends, workload fluctuations, and demand surges. Agentic systems can automatically allocate compute power, storage and bandwidth before bottlenecks appear, maintaining optimal performance without constant human oversight.

Over time, these self-adjusting systems learn from operational data to continuously fine-tune capacity, reducing waste, minimizing costs and ensuring service continuity even during unexpected spikes.

Research from IBM’s report, Agentic AI’s strategic ascent, underscores this pace of change: by 2027, twice as many executives expect AI agents will make autonomous decisions in workflows. Today, only 24% of executives report that level of autonomy; within two years; 67% expect this to be the norm.

Overcoming barriers and delivering enterprise impact

Yet progress often stalls; not for lack of intent, but because of structural barriers. IT leaders must first overcome the obstacles that stand in the way of their evolution to value-focused work. These barriers are multifold: technical, cultural and operational.

Even AI-forward IT organizations can lack the structural readiness for deep automation. For example, Ivanti’s “2025 Technology at Work Report” found that:

38% of IT professionals point to complex tech stacks as an issue in effective IT operations.
And 72% say their IT and security data is siloed within their organization.

Building a sustainable AI strategy requires more than a positive attitude – it demands alignment between IT and the broader business. Successful organizations are the ones aligning technology goals with tangible outcomes, supported by clear data structures, unified processes and teams equipped to manage new AI-driven workflows. Without that alignment, even the best tools struggle to deliver enterprise-wide impact.

IBM research reveals another layer: 45% of executives cite a lack of visibility into AI decision-making as a major barrier. This AI “black box” problem isn’t just a technical one. It’s also about trust, clear communications and AI guardrails. Scaling agentic AI requires governance frameworks where automated decisions can be understood, audited and explained.

Such transformation must keep humans in focus: design for augmentation — not replacement.

The agentic AI operating model

Think of agentic ITOps as much more than an efficiency upgrade, but as a total reshaping of traditional IT workflows. Organizations leading the next phase of transformation are the ones rethinking how their systems make decisions, collaborate and adapt autonomously across the enterprise.

That level of digital transformation requires leadership from the top. CIOs and executive stakeholders must pivot from experimentation to execution. They must look at embedding agentic AI not as a side project, but as a core operating model that aligns technology, data and people toward shared outcomes.

That pivot marks the real test ahead.

The future ROI of agentic AI initiatives

Even with the productivity boost enjoyed with generative AI tech, IT teams don’t need more tools. They need intelligence that delivers measurable outcomes. Teams should establish before-and-after metrics that resonate with IT and business leaders. Beyond efficiency gains (time saved, faster resolution, lower costs), measure labor savings, fewer resource-intensive outages and reduced tool sprawl.

Transformational organizations see greater impact across every business metric, including productivity, efficiency, revenue growth, brand strength and customer loyalty, than those that limit AI to incremental and even superficial gains.

In fact, organizations that excel in three key AI adoption areas are 32 times more likely to achieve top-tier business performance, according to that same IBM report referenced earlier.

The bottom line

The next 12 to 24 months will test IT leaders’ ability to translate experimentation into sustained value. Those who embrace agentic AI early will build organizations that learn faster, adapt continuously, preempt potential issues and recover from disruption instinctively.

IT has regularly shown that they're fully willing and committed to AI adoption. Now it must lead again, in depth. Agentic AI marks the next maturity stage: self-learning, self-healing and self-optimizing systems that enable greater agility and resilience across the enterprise.

This isn’t “set and forget.” IT teams must build, train, monitor, measure and refine agentic AI to ensure value realization.

To learn more about the role of AI as a transformative tool for IT operations and breakthrough use cases for agentic AI and automation in IT, see Ivanti’s research report: “AI: The Future of ITSM Automation.”

ITAM: Your Unexpected First Line of Cyber Threat Defense

Tue, 16 Dec 2025 14:00:02 Z

When the conversation turns to cybersecurity, people often think of firewalls, intrusion detection systems or state-of-the-art endpoint protection. Yet, beneath these sophisticated shields is an essential (and often unsung) foundation: robust IT Asset Management (ITAM).

For CIOs guiding mid-sized and enterprise organizations through an increasingly perilous digital landscape, ITAM offers not just operational clarity, but a powerful first line of cyber threat defense.

Below, we’ll explore how comprehensive ITAM delivers critical visibility into your organization’s technology environment, strengthens your defenses against evolving cyber threats, supports regulatory compliance and accelerates security operations. Read on to discover how making ITAM a core part of your strategy can help prevent costly breaches and build true cyber resilience.

Global cyberattacks rose 30% YoY, and ransomware attacks now average 20–25 major incidents per day.

Why ITAM matters: Cybersecurity challenges start with obscured visibility

Cyber threats almost invariably exploit the weaknesses organizations can’t see. Shadow IT, obsolete devices, rogue software and unauthorized access points are invisible vulnerabilities that slip through the cracks of traditional security. A comprehensive asset inventory isn’t just good housekeeping — it's the starting point for effective cyber risk management.

Despite 90% of organizations claiming strong detection capabilities, 57% still suffered major security incidents due to lack of full visibility.

Consider this: in the 2023 Data Breach Investigations Report, Verizon noted that a significant proportion of intrusion incidents stemmed from neglected assets — servers went unpatched because they were forgotten, endpoints were provisioned without visibility into their lifecycle, etc.

Here, ITAM is an invaluable early warning system. By providing a real-time, continually updated map of all hardware, software and cloud assets, it allows IT leaders to spot risks before attackers do.

The benefits of ITAM for cyber resilience

Below we’ll look at how the various benefits of robust ITAM result in a stronger security posture for your organization.

Lifecycle management eliminates weak links

Assets don’t just pose risks at the moment of acquisition. The lifecycle (from onboarding, maintenance, and update to eventual retirement) is fraught with opportunities for mismanagement that can result in potential doorways for cyber adversaries. Obsolete systems without vendor support, end-of-life software still running mission-critical apps, devices decommissioned without wiping — these are common in complex environments.

45% of organizations lack confidence in knowing all applications in use, creating blind spots that attackers exploit.

Robust ITAM ensures that every asset gets tracked, routinely assessed and decommissioned securely, closing off both accidental exposures as well as sophisticated attacks that target legacy infrastructure.

Regulatory compliance proves control and prevents penalties

Increasingly, CIOs face regulatory environments that demand demonstrable control over IT assets. Frameworks such as NIST, ISO 27001 and GDPR all emphasize asset visibility as a prerequisite for effective control of sensitive data and critical infrastructure. A mature ITAM practice maps directly onto these requirements, providing the documentation and provable oversight needed for audits and regulatory inquiries.

Over 80% of breaches are linked to gaps in attack surface management, driven by vulnerable internet-facing assets and poor asset inventory practices.

For example, under GDPR, the ability to swiftly identify and remediate vulnerable assets that process personal data is not just good security practice, it’s a legal necessity.

The ITAM-security partnership: More than just inventory tracking

True ITAM goes beyond keeping lists. Integrated asset management feeds context directly into security operations tools. Vulnerability scanners depend on accurate inventories to detect exposures. Incident response hinges on knowing precisely which systems are implicated. Security policy enforcement relies on a clear understanding of asset roles and relationships.

Anecdotally, one financial institution saw its incident response time halved after integrating ITAM data into its SIEM platform, enabling security teams to immediately pinpoint and isolate affected assets during a breach. The value here is measurable and repeatable.

Resilient cyber defense means robust asset management

IT Asset Management is not merely operational hygiene. It is an essential component of a proactive, resilient cybersecurity strategy. For CIOs, investing in a robust ITAM solution can mean the difference between surface-level security and genuine risk mitigation.

If you’re ready to discover how our ITAM solution can reinforce your organization’s security posture from the ground up, contact our team today and take the first step toward building true cyber resilience.

The Rise of Experience-Level Agreements (XLAs) in Practice: A Deep Dive into ITSM Transformation

Fri, 21 Nov 2025 15:17:59 Z

For decades, the backbone of IT Service Management (ITSM) has been the Service-Level Agreement (SLA). While effective for tracking the nuts and bolts of IT delivery, SLAs have one critical blind spot: they say little about how users actually feel about their IT experiences.

This is where Experience-Level Agreements (XLAs) and Digital Employee Experience (DEX) fill in the rest of the picture. They provide a new paradigm that's rapidly gaining traction, promising to transform ITSM by focusing on the human experience behind the numbers.

But what exactly are XLAs and how do they differ from traditional SLAs? Moreover, how does Digital Employee Experience factor into successful XLAs?

What are XLAs?

Experience-Level Agreements are a set of metrics and commitments designed to ensure that the end-user experience is consistently positive and meets (or exceeds) expectations.

While you should use XLAs and traditional SLAs in tandem, the latter focuses on technical performance and uptime. XLAs prioritize the user's overall experience, including factors like ease of use, responsiveness and emotional satisfaction.

By focusing on the user's perspective, XLAs help organizations align their services with user needs, driving satisfaction and loyalty.

Understanding how SLA, XLA and DEX work together

XLAs, SLAs and DEX work in tandem to provide you with a 360-degree view of your technical and user experience metrics.

	Description	Example metrics
Service-Level Agreements (SLAs)	A contractual agreement between service providers and customers that define the expected service quality, availability and responsiveness. SLAs focus on technical metrics.	Uptimes. Response times. Resolution rates. Etc.
Experience-Level Agreements (XLAs)	A contractual agreement between providers and customers that focuses on end-user experience, measuring the quality of service from the user's perspective. XLAs include not just technical performance, but also factors like usability, accessibility and overall satisfaction.	End user satisfaction score. Net promotor score (NPS). Digital experience score (DEX).

Unlike SLAs and XLAs, Digital Employee Experience (DEX) is not another type of agreement. DEX refers to the quality of digital experiences employees have while performing their job functions. It encompasses the technology, tools and digital environments they interact with daily.

Based on their experiences across these tools and environments, a DEX score is created (which is measured as part of the XLA). A positive DEX is crucial for employee productivity, engagement and overall job satisfaction.

How DEX enables successful XLAs

Digital experience analytics are an important metric in the success of XLA's. By ensuring that employees have a positive digital experience, organizations:

Improve productivity — When employees can work efficiently and effectively, they're more likely to deliver excellent service to customers.
Enhance customer experience — A positive DEX often translates to a better customer experience, as employees are better equipped to meet customer needs.
Drive business outcomes — By focusing on DEX, organizations can drive business outcomes, such as increased revenue, reduced costs and improved competitiveness.

Best practices for implementing XLAs

Implementing XLAs requires a careful, strategic approach to ensure that you not only measure user satisfaction effectively, but also drive meaningful improvements in service delivery.

By following the best practices below, organizations can successfully integrate XLAs into their operations and foster a culture centered on positive user experiences.

Define clear user experience metrics: Identify the key metrics that you will use to measure user experience. These should be specific, measurable, and aligned with business goals.
Leverage technology: Use advanced analytics, AI and machine learning to gather and analyze user data. These tools can help identify trends and areas for improvement. DEX tools enable you to gather and measure your IT experience across devices, users and the organization.
Engage users: Regularly collect feedback from users through surveys, feedback forms and testing. This provides valuable insights into their needs and preferences. Ensure that surveys utilize AI to identify and highlight sentiment.
Train and empower IT teams: Train your IT teams in user experience principles and give them the autonomy to make decisions that improve the user experience.
Continuous improvement: Treat XLAs as a living document. Review it regularly and update it based on user feedback and changing business needs.

Challenges and lessons learned

Implementing XLAs isn’t just about new tools — it's a mindset/cultural change. Common hurdles include:

Defining experience — What counts as a “good” experience? It can be subjective and varies across roles.
Cultural buy-in — XLAs need sponsorship from leadership and buy-in from front-line IT teams.
Continuous improvement — XLAs aren’t static. They require regular review and recalibration as user needs evolve.
More than surveys — Surveys are just one method of measurement. Ensure that DEX tools are enabled to capture real technology metrics.

Organizations leading the XLA charge invest in regular feedback loops, co-design goals with business units and link experience outcomes directly to ITSM performance reviews.

The future: Why XLAs matter

In practice, XLAs and DEX are more than buzzwords — they’re the next evolution of service management. As technology becomes ever more entwined with business success, experience is the product. IT teams empowered by XLAs move beyond “keeping the lights on" to driving employee engagement, customer loyalty and strategic differentiation.

For any organization focused on ITSM transformation, embracing XLAs means listening harder, acting faster and thinking bigger about the real purpose of technology: enabling people to do their best work.

Read the Digital Experience Report to understand how DEX impacts productivity, satisfaction and retention.

AI-Driven IT Cost Management: Aligning Spend with Strategic Value

Wed, 22 Oct 2025 13:00:01 Z

Optimizing IT costs is now the top priority for IT teams, according to Ivanti’s 2025 Technology at Work Report. Our survey found that cost optimization was cited as a critical strategic goal for 2025, outranking improving cybersecurity, investing in infrastructure and deploying AI / ML technology.

However, despite many organizations viewing AI and automation in terms of short-term operational improvements, many organizations haven't yet tapped into AI’s full potential to transform how IT manages, predicts and optimizes costs.

It’s clear that IT teams are already bullish on AI's value in everyday operations. IT is currently leading the charge in AI implementation, with 36% of IT teams using generative AI, according to McKinsey research from March 2025 — more than any other function.

While IT teams regularly use AI for coding, support tickets and other day-to-day work, many organizations don’t see beyond these short-term efficiency gains. Too often IT leaders overlook AI's untapped potential for enterprise-wide optimization.

This shift from incremental productivity gains to strategic cost optimization frees resources and grants IT leaders the flexibility to focus on innovation, long-term transformation and consistent alignment of operations with fast-evolving business strategy.

With CIOs under mounting pressure to “do more with less,” AI-driven IT cost optimization has the power to reduce wasteful IT spending, justify investments and deliver strategic value across the entire organization.

However, before this transformation can happen, companies must first understand the biggest sources of inefficient spending and identify the most valuable areas where they can use AI capabilities to better allocate resources and make the most of their IT budget.

Major barriers to IT cost optimization

Cost management challenges are systemic. Inefficient IT spending results from compounding breakdowns across systems, processes and leadership structures. More than half of IT professionals said that wasteful IT spending was a significant problem at their organization, according to 2025 Ivanti research.

Wasteful IT spend is especially egregious in high-complexity sectors like telecoms and government, where legacy systems and sprawling vendor relationships make it difficult to track and control spend. These sectors face greater pressure to cut costs, as unchecked waste limits their ability to fund strategic initiatives and modernize critical infrastructure.

Monthly vendor reviews, quarterly budget reconciliations and annual contract negotiations struggle to keep pace with today's dynamic IT landscape. Organizational cloud spend can spike overnight, and tech complexity compounds rapidly due to decentralized procurement, shadow IT and poor asset visibility. For instance, 38% of IT professionals Ivanti surveyed pointed to “tech complexity” as a major barrier to effective IT operations.

Looking toward the future of AI-powered ITOps, many IT professionals recognize AI's transformative potential to meet these challenges and eliminate unnecessary spending.

AI and machine learning for predictive cost management

Manual cost reviews alone are backward-looking, labor-intensive and prone to human error. Human oversight alone cannot recognize and analyze patterns that emerge through large-scale AI data analysis. AI-powered cost management flips the script. Instead of reporting overspending after it happens, AI predictive analysis can detect potential anomalies and provide organizations with accurate budget forecasting to avoid redundant, unnecessary spending. AI can also surface redundant tools, highlight lifecycle costs and flag spending anomalies that human reviews would likely miss.

Consider this scenario: you can use AI to analyze your IT asset management data to uncover shelfware and unused software licenses, or to mine support tickets for patterns showing when certain device types typically begin to fail. Those insights can inform smarter replacement cycles, reduce downtime and ensure you only pay for what you actually use.

The speed difference is dramatic. Organizations using AI-driven cost optimization are seeing measurable reductions in operational expenses, while others are still compiling last quarter's reports on spreadsheets.

Real-time visibility consistently outperforms reactive reviews. When you can predict and prevent waste instead of just documenting it, that's when IT shifts from expense management to strategic value creation.

AI cloud cost management and resource management

Cloud environments are the single largest source of budget variance and waste. Nearly nine in 10 (88%) of organizations see significant variance between actual spend and forecasted spend, and only 30% know where their cloud budget is going, according to CloudZero’s State of Cloud Costs in 2024.

Ivanti’s own findings expand on these IT resource management challenges:

39% of IT professionals cited outdated hardware as a considerable source of wasteful spend.
Outdated, unused and expired software is also a major factor, with nearly one in three (31%) IT professionals reporting their organizations don't track unused or underused software licenses.
Even more concerning, 48% of IT teams reported that their companies use software that’s reached end of life (EOL).

The combination of multi-cloud environments, unpredictable usage over time, complex and multilateral pricing within the same services and drastically varied costs makes the need for AI and automation clear.

AI-enabled technology can help cut through this complexity. AI solutions can proactively identify underutilized software licenses, over-provisioned cloud resources and redundant applications across environments that'd take human analysts weeks to map.

What’s more, AI combined with ITSM automation can suggest resolutions to inefficient IT spending through intelligent recommendations for rightsizing and deprovisioning. Leading CIOs use strategic IT cost management to fund high-impact initiatives, and AI automation makes this achievable at scale.

Software license optimization delivers significant returns. AI tracks actual software usage against entitlements, identifies downgrade opportunities and predicts future needs based on growth patterns. Organizations pay for what they use, not what they purchased months ago.

AI’s impact on streamlining IT processes

While AI adoption increases among IT teams, its cost optimization impacts aren't yet as widespread as basic use cases like predictive maintenance and automating routine self-service tasks — both popular, according to Ivanti research.

Delayed widespread AI adoption in ITOps prevents organizations from reaping the long-term financial benefits and opportunities for strategic business growth. IT automation solutions can reduce operational costs by up to 90%. The technology handles ticket triage and automates incident response while predicting system failures and managing routine maintenance.

AI elevates IT operations, and the impacts are felt across the entire business. Asset performance monitoring becomes intelligent and proactive. Instead of static thresholds and scheduled checks, AI systems continuously analyze performance data, predict hardware failures and optimize maintenance schedules.

This prevents both downtime costs and unnecessary replacement spending. Process automation also frees IT time, reducing costs from human error: manual misconfigurations, missed patches and delayed responses caused by limited resources.

How AI empowers IT to deliver strategic value

IT cost management isn't the endgame. It's the starting point for strategic transformation. AI enables companies to optimize costs at scale while freeing up budgets for growth investments.

Organizations embracing AI for cost management are repositioning how their businesses view and leverage technology. When every investment must justify its existence, AI enables IT leaders to become architects of value, not just managers of expense by cutting costs and creating value. AI promotes agile resource allocation. When wasteful costs are eliminated proactively, IT executives gain flexibility to fund emerging opportunities and respond to changing business priorities.

Visibility is equally important in transforming IT into a strategic business driver. AI provides the data and insights needed to quantify IT's business value. When investments are tracked and tied to business outcomes, CIOs can demonstrate the true ROI of the IT department and secure strategic support.

The real transformation happens when IT moves from reactive expense control to proactive value creation. AI-optimized IT operations have become the foundation for innovation, enabling teams to experiment and deliver competitive advantages.

To learn more about the major challenges contributing to wasteful IT spending and how AI and automation can help IT teams boost efficiency, improve asset visibility and optimize IT cost management, see Ivanti’s 2025 Technology at Work Report.

Your Windows 11 Migration Is Looming – but There’s a Bot for That

Mon, 28 Jul 2025 19:31:10 Z

I recently spoke with a CIO who had committed a large amount of IT resources to manually migrating computers from Windows 10 to Windows 11. The process required months of planning, device assessments, compatibility testing and hands-on coordination to avoid disruptions to day-to-day business operations. While their dedication ensured their rollout was on track for the looming Windows 11 end-of-support date, it highlighted the strain such projects place on internal teams.

My conversation with this CIO isn’t unique. Before becoming an Account Technology Strategist here at Ivanti, I worked in various roles in IT support and still bear the scars of the Windows XP to Windows 7 migration. I also spent years helping organizations plan, execute and troubleshoot OS upgrades — often under tight timelines, with limited resources.

Automation is key to any major upgrade project. It improves overall IT efficiency, reducing labor costs and human errors. In this blog, I’ll show you how you can use automation in your Windows 11 migration and where Ivanti Neurons bots can help.

Assess the fleet

Before starting any project, asset discovery is key: you can’t upgrade something you don’t know exists or isn’t really there. One Ivanti customer discovered that they had 30% more assets than they expected on their network! This echoes a study from Gartner that found 30% of IT fixed assets are "ghost" assets, or missing and can't be found, which further complicates the task.

Data that exists outside of the device, such as device warranty, is important too. Perhaps upgrading a device with three months’ warranty left isn’t really worth it — it may be replaced through a refresh cycle soon anyway, leaving more disruption for users.

A step you can automate is evaluating whether each device meets Microsoft’s minimum hardware requirements, which you can do in Ivanti Neurons using the Windows 11 Upgrade bot. Then, devices that don’t meet the necessary criteria can be flagged with an automatic ticket in your service or asset management solution. This helps provide the right data to IT-adjacent teams like Procurement for financial planning and purchasing new hardware.

Create a baseline for end-user experience

Creating a baseline helps IT measure the impact of the upgrade, identify potential areas of improvement to review post-upgrade and ensure that the new operating system meets or exceeds current performance levels. It also provides a point of reference for troubleshooting should any issues arise post-upgrade. This data is gold dust for the service desk team, who will be on hand to support users.

One way to create a baseline is with a DEX, or digital experience, score (which you can do in Ivanti Neurons). This quantifies the quality of an employee’s digital experience by aggregating data from various indicators like CPU usage, memory performance, application crashes, disk space and battery health. For example, excessive CPU usage or frequent application crashes can lower the score, while optimal performance in these areas contributes to a higher score. Sentiment analysis of service management incidents can also provide qualitative data that impacts the DEX score.

Surveying the end user bolsters telemetry-based metrics in the DEX score. Surveys provide IT with an early indicator of problems — but you can’t ask too many questions before the end user hits the dreaded mute button! A simple emoji response via Microsoft Teams gives you an empirical response, and a free text field gets user sentiment feedback.

So how do you analyze the data at scale? Feeding these insights into AI for sentiment analysis lets you interpret the tone and emotion to detect frustration or satisfaction levels.

One big takeaway from any migration is its impacts on end users. IT should want the end user to feel part of the process, if not own it!

Put the user at the center of the W11 migration

At this stage, we have devices suitable to upgrade and know our baseline. Now it’s time to interact with the end user.

IT leaders are all too aware of the potential impact that changes like system upgrades or new software deployments can have on end users, but this awareness doesn’t always translate into action. In the push to beat pending deadlines like Windows 10 End of Support, user experience considerations can be overlooked, leading to disruptions, frustration (reduced CSAT) or decreased productivity.

You can use automation, like the Windows 11 Upgrade bot, to keep the user in the loop, providing them a reason for the change and allowing them to schedule the upgrade at a convenient time.

Validate changes with end users

When changes like system updates are made to their computers, end users often face disruptions to their familiar workflows. A major change like upgrading to Windows 11 can lead to confusion, reduced productivity and frustration, especially if the upgrade was unexpected or poorly communicated. Users may struggle to find previously accessible features, encounter compatibility issues, or experience slower performance, all of which can create a sense of being unsupported.

Surveys have shown that knowledge workers experience such issues 3–4 times per day and often don’t raise support cases. A bot like the Ivanti Neurons Survey bot can be used here, capturing end user sentiment and feedback. So far, automation has done much of the hard work in your Windows 11 migration, but there will always be humans … as it stands anyway! A survey offers an opportunity to bring a human into the loop where applicable.

Software updates – and more! – with Ivanti Neurons bots

So, you’ve read a little of how the Windows 11 bot works. This is just one use case for an Ivanti Neurons bot. The same principles can also apply to major upgrades of any software, but also to a wide array of automation use cases on devices:

Reduce IT operational costs by automating manual steps.
Limit opportunities to introduce human error through manual processes.
Ensure the user is engaged and, crucially, happy with the process and their new operating system.

Neurons bots help IT teams proactively identify, diagnose, and resolve issues across endpoints and devices, often before users even notice the problem. Bots communicate with devices in real time, run queries and perform actions to keep systems healthy and secure.

You can check out some of the ways our bots help automate, accelerate and enhance IT operations, freeing up time for you to work on what matters, by visiting the Bot Library.

Is Your ITSM Environment Ready for Agentic AI? Probably Not (Yet)

Wed, 16 Jul 2025 16:01:36 Z

Agentic AI is making waves across various industries, and its potential to transform ITSM is undeniable. With all the talk about agentic AI capabilities, you are probably daydreaming about streamlining ITSM processes through automated incident management, automated change risk analysis, improved efficiency through service desk automation, or enhanced service quality with predictive maintenance. But you also may start to wonder: How real is all of this? Is my organization truly ready for agentic AI?

I would suggest that for most organizations, the answer is no!

Don't get me wrong; organizations are listening to the conversation and are keen on the potential long-term benefits. And some may indeed be ready for to implement agentic AI properly.

Ambitious, but underprepared: why most organizations aren’t ready for agentic AI

The reason I doubt that organizations are adequately prepared is that for agentic AI to function optimally, you require good clean data, seamlessly automated workflows that are well defined, and comprehensive flexible integration across all systems intended for agentic AI operations.

We see the importance of clean, integrated data in the acquisition of data management companies by other tech vendors, notably Salesforce and Informatica. Reconciled, normalized data gives AI agents the best possible intelligence to work with so they can provide the best outcomes and most accurate information.

You should always consider: How will AI agents benefit you and your organization? Can your journey to autonomous work be achieved through workflows? Even Anthropic, a leader in the AI space talks about using the simplest solution possible and only implementing AI agents for complex requirements. In some cases, agents are not only more costly but also less efficient than pre-built workflows.

Preparation today, agentic AI tomorrow

As you consider pursuing agentic AI, there are several factors to examine. With planning and preparation, you can be successful, and this checklist will help guide you on your journey.

Planning

When you start your journey to agentic AI, clearly outline your goals for introducing agentic AI into your service management environment while ensuring that they align with your overall organization's goals. Some common objectives are:

Reduce the workload on IT staff by automating repetitive and time-consuming tasks.
Improve the speed and accuracy of incident resolution.
Enhance the end-user experience with seamless automated request fulfillment.

With your goals defined, what does success look like, and how will you measure it? These will vary based on your expectations and defined goals, but some common metrics could be:

% of tasks successfully automated by AI.
Decrease in errors within tasks handled by AI compared to manual tasks.
User satisfaction score (CSAT).
% of users opting for AI-driven self-service solutions.
Reduction in the average cost of resolving a ticket with AI.
% of incidents escalated to human agents after AI intervention.

Related content: AITSM: How AI Is Redefining IT Service Desk Automation, part of Ivanti’s Digital Employee Experience Research Report Series

Data preparation

Within the context of service management, there are many sources of data that may be required, including sources that are purely ITSM-related, such as a CMDB or asset repository. As you move towards the wider enterprise, you may also need data from CRM, HR, facilities, finance or other departments.

Regardless of where you are getting the data from, you need to consider the following:

Is your data quality reliable? Is the data consistent? How accurate is the information? Is there a more trusted source (or master) that should be considered as the default? Often data is inconsistent across multiple systems, making it harder for an AI agent to make well-informed decisions.
How accessible is your data? How many different data sources are there, and will integration via APIs be required? Are the data sources up to date?
Is your CMDB ready to be used by agentic AI? Do you have critical CIs in your CMDB, and more importantly, how up to date are the relationships and the information?
Are you required to adhere to data privacy compliance? Do you need to adhere to data protection regulations such as GDPR, CCPA or others? It is possible that regulations may demand that you anonymize sensitive data and keep it within country.

Defined workflows and automation

Not only is having high-quality data vital, but having good, functioning workflows to drive tasks is a critical component of successful agentic AI. In some cases, your existing workflows can be repurposed for use within an agentic AI process; however, some workflows will need to be modified to meet the request/response requirements of an AI agent.

Some things to consider for workflows:

Are your workflows able to be used by AI agents? Your existing workflows may not be structured in the most effective way for AI agents to utilize the entire workflow to deliver accurate results.
Will the workflows only be working with data within your organizations, or will it need to access external data sources? When accessing external data sources, what security measures are in place to ensure the security and accuracy of the data within the responses?
Ensure all agent AI and related workflows have audit trails enabled, so you can log and monitor AI actions and decisions. This ensures the correctness of the AI and can be used in the event of compliance or security issues.

Governance and compliance

Earlier we discussed compliance requirements for data and the need to meet regulatory or statutory requirements. Governance and compliance must also apply to the entire AI ecosystem within your organization to deliver responsible, secure and trusted responses and actions.

Here are a few things to consider:

Define policies for how AI is to be used within your organization and assign people or teams who are accountable for protecting the data and evaluating ethical considerations.
Ensure that regulatory or statutory compliance standards are understood across the entire AI workflow and met. For example, if an AI agent requires access to health-related data and data collected from European users, then you would need to consider both HIPAA and GDPR.
Identify potential risks throughout your environment and meticulously mitigate those linked with the AI deployment.

Testing and validation

Start your journey to agentic AI in a controlled environment. Set up a pilot program to test the functionality, ensuring you measure against your goals and gather feedback from users. It is important to have a continuous improvement program in place for adjustments and enhancements. Be patient, as good results may take time as the AI learns and adjusts. Always monitor and adjust as required and define a process for handling issues or failures.

Agentic AI is an evolution, not a revolution

Discussion around AI is everywhere, and while there is a lot of interest from organizations, many are still rightly cautious about how to proceed and what is best for their organization. As we have seen over the last few years, AI has progressed very quickly from generative to agentic. Keeping up with emerging technologies and planning for future enhancements is vital.

Ivanti is well positioned with AI capabilities that can enable you to grow. Find out more about what Ivanti can offer for your AI journey.

How CIOs Can Optimize IT Costs and Eliminate Wasteful Spending

Mon, 23 Jun 2025 19:20:25 Z

When operating in healthy economic environments, business teams are often allowed greater rein to explore how budgets can be allocated. But when times become tough due to geopolitical tensions, global tariffs, tech disruptions, layoffs, restructurings and rising tech costs, there is greater pressure on CIOs to minimize wasteful spending and prove the value of their IT investments — ensuring a louder bang for their buck.

In all this, leaders and CIOs are pressured to “do more with less” – including growing scrutiny over how IT dollars are allocated and justified. Being able to measure and communicate the ROI of IT initiatives to stakeholders becomes more important than ever. The paradox of rising expectations paired with reduced resources is the new normal.

This is especially true in the public and federal sectors, where proposed cuts to CISA and tech security budgets by the US federal government adds to already heightened pressures to align with accountability, regulatory guidelines and compliance.

Ivanti’s 2025 Technology at Work Report reported that more than half (58%) of IT professionals say wasteful IT spending is a problem in their organization. Tech sprawl, scope creep, limited asset visibility, siloed teams and redundant operations represent poor IT cost management practices which drain resources that could be committed to strategic innovation.

Today’s reality is that CIOs are working with less budget across the board. As such, they must focus their energy on finding and reducing inefficiencies in their current spending. But more so, IT cost optimization is shifting from reactive operations to a strategic, future-facing imperative. Leaders are becoming more strategic and targeted with their investments and creating room to fund the initiatives that drive long-term business value.

IT cost optimization is a top priority

Ivanti’s report finds that IT cost optimization is a top priority for enterprise IT teams this year – but at the expense of investment in IT infrastructure and AI / ML. This aligns with trends across industries: CIOs are simply facing increased executive and board-level scrutiny as budget approvals become more centralized and return on spend must be proven faster than ever.

Additionally, Gartner’s 2025 CIO Agenda report finds that only 48% of enterprise-wide digital initiatives meet or exceed their business outcome targets – that means there’s plenty of room for improvement. This is prompting forward-thinking CIOs to rethink IT budgeting not just as an optimization exercise, but also as a strategic reallocation of resources.

IT leaders are looking at ways to tighten spending in some areas to allow for transformation in others and demonstrating measurable business outcomes of their initiatives. While budget cuts are never an easy time for organizations, the need for IT cost optimization could be an opportunity to generate fuel for growth.

Top causes of inefficient IT spending

Inefficient IT spending is often the result of compounding breakdowns across systems, processes and leadership structures. CIOs looking to optimize their budgets must first identify spending redundancies, inefficiencies and misalignments in their current tech stack and processes. Below, we explore top culprits behind IT budget bloat and how each contributes to mounting costs and diminished returns.

Poor asset visibility

Lack of visibility into endpoints, devices and SaaS assets leads to overspend and blind spots. This is compounded by the expansion of attack surfaces as organizations’ external and internal assets continue to grow — oftentimes with unknown or unmanaged visibility gaps.

This is backed by Ivanti’s Tech at Work research, Device and license usage is tracked by just 38% of IT teams, and only 36% track device performance / health.

Complicating matters further is shadow IT. Unknown and unmanaged use of devices and applications often results in duplicate existing capabilities or go entirely unused, leading to avoidable spend and potential compliance issues.

Even sanctioned tools lack oversight without standardized IT asset management practices, making it hard to enforce usage policies, track renewals or manage the asset lifecycle efficiently. Many opportunities are then missed to reduce spending through consolidation or retirement of redundant tools

Tech sprawl and cloud sprawl

Duplicate tools drain resources and fragment the tech stack without adding performance. This adds both cost and complexity to the IT ecosystem. And inaccurate forecasting and poor usage monitoring inflate cloud spend.

Organizations are often challenged by frequent “swivel chairing” – where employees switch between disconnected tools which leads to wasted time and diminished productivity. For example, an IT support agent might bounce between a ticketing system, an asset management database, a separate knowledge base and a communication platform – copying information between them just to resolve a single issue.

Technical debt

Without regular vendor audits, redundant or underperforming tools overstay their welcome and legacy systems linger. These drain resources and diminish returns.

Finally, a lack of integration across overlapping tools contributes to siloed team processes, slower response times and inconsistent or incomplete data. When systems and processes aren’t fully integrated, it’s easy for efforts to be misaligned.

Inefficient processes

Inefficient processes in IT workflows can also be a major budget leech. A good portion of standard IT work can be automated, yet isn’t – leading to talented IT workers spending time on easily optimizable workflows including manual ticketing and patching, at the expense of higher-level strategic initiatives. A study cited in CIO found that the average large enterprise lost an estimated $104 million to digital inefficiencies, leading to shadow IT solutions which only augment the above-listed causes of avoidable spend.

Another process drag comes from siloed work and poorly integrated systems. When teams don’t have a unified platform or standardized protocols, work is duplicated and fixes are delayed. Ivanti’s 2025 research reported that 37% of IT teams reported that organizational silos reduced collaboration within their company – and 40% of IT professionals said that these silos hamper IT efficiency.

Moreover, current IT talent shortages augment an already challenging environment. Understaffed teams have to prioritize day-to-day firefighting, leaving little room for other, higher-level work.

Poor leadership visibility

A major overarching factor in IT efficiency and wasteful spending is lack of visibility with other executive leaders. The 2025 Tech a Work Report revealed that 57% percent of IT professionals felt that their company leadership did not have high visibility into IT efficiency (or lack of efficiency).

This lack of collaboration with leadership often leads to misaligned investments that don’t meaningfully contribute to actual growth. This worsens when budgeting is disconnected from KPIs and OKRs. When the ties to business outcomes aren’t clear, CIOs can’t justify their investment choices or show the real impact of their team’s work.

Fast-paced demands from above without consultation can often push IT leaders to sacrifice long-term stability for short-term speed. And skipping testing and documentation undermines system stability and invites costly breakdowns. This prioritization of operational efficiency over strategic longer-term business impact is a symptom of poor alignment.

Federal and public sector CIOs face unique challenges

Across the board, IT leaders are encountering shrinking resources and growing accountability – from healthcare systems to financial services to manufacturing. But, as mentioned above, public sector CIOs operate in a more rigid and scrutinized environment than their private sector peers.

While private enterprises face similar challenges, public sector IT budget management is usually fastened to annual fiscal cycles, necessitating longer-term decisions and restricting agility. Heightened procurement, compliance and regulatory frameworks bring additional constraints.

Fragmented ecosystems are an issue here as well. This is highlighted in Deloitte’s Government Trends 2024 report. Government bodies struggle with limited understanding of the real value that IT brings and the challenge is that ROI is harder to prove in these environments due to complex procurement processes and strict compliance needs – not due to lack of effort or intention from IT leaders.

Budget constraints are tightening even further, and audits are steadily increasing. CIOs in the public sector must demonstrate cost control and operational efficiency even more diligently than their private-sector peers. Transparent, strategic IT cost optimization frameworks are no longer an option – they’re required.

A strategic approach to IT cost optimization

It’s time to fully embrace a cost-efficient resolution with an actionable playbook. Addressing IT spending is more than cutting costs; it entails a deeper look at how IT integrates with overall business strategy. In doing this, CIOs must align IT with higher-level goals, uncover the right data to inform decisions and clearly measure outcomes.

Every investment must have a specific impact. A smart IT investment strategy ties spending to results – in increased revenue, more efficient processes, better user experience and bigger-picture thinking. The objective is to move from simple cost-cutting to intentional, strategic allocation of resources.

The result is a modernized budgeting model that’s aligned with business and driven by real-time data focusing on actual return on investment. Where does tech drive performance? Where does it drag? Where can automation be applied?

Start by focusing on these actionable steps:

Manage and monitor IT assets

Establish full lifecycle visibility into hardware, software and endpoints by implementing centralized IT asset management solutions. Effective IT asset management will allow teams to better consolidate asset data across the overall environment and standardize how assets are discovered, tracked and retired. Real-time monitoring, supported by AI and automation, enables teams to identify underused assets, reduce redundant purchases, remove bottlenecks and proactively manage renewals.

By integrating ITAM with service management and configuration databases (CMDBs), leaders can gain a holistic view of asset performance and compliance and minimize security risk and improve budget control.

Streamline IT workflows with AI and automation

Manual, repetitive work can be readily automated using AI and other technologies. Identify where steps can be automated across service management, endpoint provisioning and patching. AITSM capabilities have been proven to improve ticketing, detect anomalies and continuously monitor device performance and health in a faster and more complete way than human oversight alone.

There are also cases where an IT team may already possess these tools but aren’t utilizing their full capabilities due to poor visibility, tech sprawl or lack of standardized IT asset management. Conducting an inventory of all assets and identifying redundancies and inefficiencies then frees up valuable resources for other, higher-level priorities that tie back to impact and ROI.

Define and measure IT business value

IT cost management requires quantifying how IT actually contributes to the overall business. Start by tracking real outcomes, including revenue growth tied to technology investments, risk mitigation efforts (ticket resolution, patches, thwarted attacks) and tracking the digital experience of customers and employees.

Improve collaboration and communication with executive leadership

When IT investment strategy is cross-functional and clearly linked to business performance, executive buy-in follows. IT leaders cannot operate in a vacuum, let alone optimize in one. They must define and own measurable KPIs that show the ROI of their investments, be it AI, automation or cloud modernization. And CIOs should proactively set performance benchmarks tied directly to business outcomes. When leaders translate IT strategy into the language of business value, CIOs can shift the perception of IT from a cost center to a cost enabler and make stronger cases to executive leadership and the board.

Aligning IT spend and strategy

IT cost optimization isn’t just about trimming fat. The long game of optimizing IT efficiency is in building a smarter, more responsive and more valuable IT function that’s recognized as crucial to business outcomes. CIOs who tackle inefficiencies head-on implement more streamlined processes, reallocate budgets and deliver greater ROI for their spend will strengthen their strategic position in their organization.

In circumstances where every dollar spent must justify its existence in spades, taking actionable steps to cut down on IT waste and shifting mindsets from reactive cost-cutting to smarter, targeted investments transforms IT departments into an active value generator, even in times of disruption and uncertainty.

For deeper insights into the root causes of IT budget inefficiencies and how to fix them, check out Ivanti’s 2025 Technology at Work Report: Reshaping Flexible Work.

How to Safeguard Healthcare Data in ITSM: Ivanti and Protecto

Mon, 02 Jun 2025 17:00:31 Z

The healthcare sector, perhaps more than any other, needs to scrutinize the balance between data utility and data privacy. Healthcare organizations must manage large amounts of sensitive data while complying with stringent regulations such as the Health Insurance Portability and Accountability Act (HIPAA). For IT teams seeking to implement AI-augmented service management, that responsibility weighs heavily.

A notable recent incident involved over four million customers affected by a data breach at Blue Cross Blue Shield, where Google Analytics had been configured in a manner that allowed member data to be shared with Google Ads, likely including protected health information.

Forward-looking IT leaders want to take advantage of advanced IT service management capabilities to improve operational efficiency, including emerging AI applications. But to avoid becoming the latest headline, they also need the highest standards of data protection. In this article, we’ll go into how Ivanti integrates with Protecto to do just that.

Where healthcare compliance and AI intersect

The myriad regulations that healthcare organizations must follow (HIPAA, GDPR, CCPA and others) are designed to protect patient data and ensure that it is handled securely and ethically. Data security and privacy are fundamental aspects of patient trust, and noncompliance can result in significant fines and legal actions.

At the same time, AI and ML technologies require access to large datasets – data that may include sensitive information that is subject to these stringent requirements. To add another layer of complexity, healthcare organizations are often large and complex, with multiple departments and locations, which means any data privacy solutions need to be able to scale without compromising performance.

Healthcare requirements for ITSM

IT organizations that want to take advantage of advanced ITSM use cases without fear of compromising data privacy have specific requirements – requirements that the integration between Ivanti Neurons for ITSM and Protecto deliver.

Data masking

Intelligent data masking identifies and masks sensitive information such as PII and PHI. This lets AI agents operate on data without exposing sensitive elements, preventing data leaks and reducing misuse. Additionally, data masking ensures that the context and utility of the information remain intact, enabling effective analysis and decision-making.

Role-based access controls

Role-based access controls and policy-driven unmasking ensure data is only accessed by authorized users with appropriate roles. Only users with the necessary permissions can access or unmask sensitive data.

Audit trails

To comply with regulations, healthcare organizations need a comprehensive audit trail of how sensitive data is accessed, used and protected. Detailed logs simplify compliance workflows and support regulatory audits.

Seamless integration

Protecto integrates with Ivanti APIs, which allows existing processes to remain uninterrupted – and for IT teams to deliver the best possible service – adding a layer of protection without disrupting operations.

Scale

A single instance of Protecto can support over 3,000 tenants, safeguarding the data of millions of users. It can handle large-scale deployments while maintaining operational resilience, making it a reliable choice for AI initiatives.

Ivanti and Protecto’s partnership

The partnership between Ivanti and Protecto brings immense value to Ivanti customers in highly regulated sectors with heightened data privacy concerns.

Already available features such as custom masking policies, on-premises and private cloud alternatives, and improved audit logs and reports ensure customers can meet compliance requirements with confidence.

Our commitment to research and development in AI, machine learning and data protection mean customers will always be at the forefront of managing large-scale datasets.
Our work with healthcare organizations, regulatory bodies and technology partners helps customers put in place practical data protection solutions without compromising IT efficiency.

Combining Ivanti Neurons for ITSM with advanced data security and privacy features ensures that our customers’ ITSM operations are both efficient and compliant with the most stringent guidelines, whether they’re in the healthcare industry or any other highly regulated field.

Ivanti’s partner ecosystem

Ivanti works with a wide range of technology partners like Protecto to help customers make the most of their investment in Ivanti solutions. To learn more, visit the Ivanti Partner Markeplace.

The Hidden Gems of ITSM: Features That Matter Most

Fri, 28 Mar 2025 12:34:36 Z

Service management doesn't have to just be a buzzword. It can be a foundation of efficient operations where IT Service Management (ITSM) plays a crucial role in keeping businesses running smoothly. But what truly sets exceptional ITSM apart from the rest? It’s not just about having a sleek user interface — it’s about the powerful features and functionalities that operate beneath the surface, improving user satisfaction and driving operational excellence. From automated incident management to self-healing capabilities, the true power of ITSM lies in its ability to anticipate and resolve issues before they become problems.

The power underneath: what truly matters

Beneath the surface of sleek interfaces and user-friendly designs lies what makes service management indispensable. While a polished UI can improve the user experience, it’s the underlying functionality and efficiency that determines the success of any service management system.

For employees, it’s the speed and effectiveness with which their requests are handled that matters. When an employee submits a request, they expect it to be actioned and resolved quickly. Delays lead to frustration and a decline in productivity, which ripples through the entire organization.

Employees also highly value transparency and communication. They expect to be informed of the status of their requests and any potential delays. By providing regular updates and maintaining clear lines of communication, IT teams can significantly improve satisfaction and trust in the service management process.

For IT professionals, the stakes are equally high. They need the right solutions to efficiently address and resolve issues. The ability to handle incidents at the initial level, often referred to as Level 0 support, is crucial. This means resolving simple issues quickly without escalating them, which can drastically reduce the number of tickets that need to be managed.

In the end, the true test of employee satisfaction with the service management system is in the results it produces. The speed and efficacy with which issues are resolved, the quality of communication received, and the overall impact on their day-to-day productivity are key metrics.

Beyond the Flashy UI: The Core Capabilities of Service Management

The underlying architecture and processes are what actually make service management strong. At the heart of any good service management solution is the ability to streamline workflows, which can greatly increase efficiency. When processes are optimized, teams can focus on more important work, reducing the time and effort spent on mundane, repetitive tasks. This not only increases productivity, but also ensures that the IT department can respond more effectively to the needs of the business.

Automated incident management is another critical component that often goes unnoticed. By automating the detection and resolution of issues, organizations can drastically reduce response times. These self-healing capabilities are a game-changer in modern service management. Ensuring that problems are identified and remediated before users even log them, leading to higher user satisfaction. Additionally, users are less likely to experience disruptions, and when issues do arise, they are resolved quickly and efficiently. This proactive approach not only improves the user experience but also helps in maintaining a positive perception of the IT department.

Integration capabilities are another essential aspect that often gets overlooked. A service management solution that seamlessly integrates with various enterprise applications and services ensures all components work in harmony. This eliminates silos and ensures that data flows smoothly across the organization, improving overall operational efficiency.

However, it’s important to note that not all vendors deliver on their low-code/no-code promises. While many claim to offer these features, the reality often involves more coding than advertised. True low-code/no-code solutions should minimize the need for extensive coding, making it easier for IT teams to deploy and manage services without requiring deep technical expertise.

The digital employee experience is more than just surveys. It involves a comprehensive 360-degree view of how employees interact with various aspects of the service management system, including applications, security and devices. Proactively identifying and addressing issues across these areas can significantly improve the overall employee experience.

Features that make service management great

But what are the specific features that elevate service management from a mere tool to an indispensable solution? One of the most transformative features is automation. By automating routine tasks and ticket resolution processes, service management solutions can significantly improve user satisfaction while reducing the workload on IT teams.

Self-service portals are another game-changer. These portals empower users to resolve simple issues on their own, such as password resets or software installations, without needing to involve the IT department.

Advanced analytics are also crucial for modern service management. By providing deep insights into service performance and user behavior, these analytics enable organizations to proactively address issues before they become major problems. For example, predictive analytics can identify patterns that may indicate an impending system failure, allowing IT teams to take preventive action.

Mobile access is also key. With the increasing mobility of the workforce, it’s essential that IT support is always available, no matter where users are. Mobile-friendly service management platforms enable users to submit tickets, track progress and receive updates on the go.

Finally, AI is increasingly becoming a crucial aspect of successful service management. AI-driven tools can automate more complex tasks, provide intelligent recommendations and even predict and resolve issues before users are even aware of them. However, it’s crucial that these AI systems are transparent and trustworthy, ensuring they operate ethically and in the best interests of the organization and its users.

How Ivanti Helps

This is where Ivanti comes in. We provide a suite of solutions that not only make service management more efficient but also enhance the core aspects of service management. We do this through our AI-driven service management capabilities that make the service desk smarter, faster and more efficient. With AI-driven capabilities, we can summarize incidents and tickets, generate knowledge articles, classify incidents and even create dashboard widgets.

In today’s digital world, security is top of mind for all organizations. That’s why we’re the only ITSM vendor to have signed the Secure by Design pledge. We don’t just say we’re secure — we build security into our products.

Our robust security is complemented by our extensive enterprise integration capabilities. With over 1,000 connectors, our platform can seamlessly integrate with a wide range of third-party systems, both IT and non-IT. Our low-code/no-code approach, powered by the leading iPaaS platform, makes it easy to extend ITSM automation and workflow to external systems without requiring deep technical expertise.

In addition, we offer five out-of-the-box (OOTB) enterprise workflows for HR, facilities, project portfolio management (PPM), governance, risk, and compliance (GRC) and security operations. These aren't just templates — they're fully functional business objects that can be customized to meet your specific organizational needs.

The low-code visual editor is a powerful feature that allows organizations to build and modify workflows across all IT and non-IT processes. This capability allows for the creation of custom solutions that align with unique business requirements, minimizing administrative effort and maximizing productivity. The platform’s integrated DevOps capability, with OOTB bi-directional connectors for Jira, Azure DevOps, GitHub and Jenkins, extends this flexibility to DevSecOps.

One of the most innovative aspects of Ivanti’s platform is its self-healing capabilities. Proactive service management ensures that issues are identified and resolved before they impact users, significantly reducing mean time to resolution (MTTR). This proactive approach not only improves service quality but also improves the overall digital employee experience. Ivanti is the only ITSM vendor that measures the digital employee experience, providing insights into employee sentiment and the performance of devices, applications and security measures.

In a landscape of rapid technological change, Ivanti’s solutions offer the flexibility and security required to lead the pack. Through the power of advanced AI, resilient security and seamless integration, Ivanti equips organizations to deliver exceptional service and spearhead digital transformation with confidence.

Want to learn more? Check out our webinar, Beyond the Surface: Unveiling the True Power of ITSM, to take a fresh look and elevate your service management game to gain a competitive edge.

How AI can alleviate help desk workloads

Mon, 24 Feb 2025 16:46:45 Z

Republished with permission from CIO.com

The rising flood of trouble tickets is straining help desk operations. Yet many still rely on phone calls, outdated knowledge bases and manual processes. Unsurprisingly, this is leading to staff frustration and burnout, dissatisfied end users and persistent security vulnerabilities.

As many as 56% of IT workers say that help desk ticket volume is up, according to a survey by Ivanti. The reasons include more software deployments, network reliability problems, security incidents/outages and a rise in remote working.

Old solutions for new problems

Today’s burden is acute because help desks are responding to the same questions and problems in the same way. For many, the main channel of interaction with users is the telephone.

That means organizations are lacking a viable, accessible knowledge base that can be leveraged, says Alan Taylor, director of product management for Ivanti — and who managed enterprise help desks in the late 90s and early 2000s. “We end up in a cycle of constantly looking back at incomplete or poorly documented trouble tickets to find a solution.”

How AI can improve help desk workloads

AI can improve many help desk tasks. Yet Ivanti’s Everywhere Work Report found only 40% of respondents were using AI for ticket resolution, 35% for knowledge base management and only 31% for intelligent escalation. With AI, these activities can have a positive impact on help desk operations and end-user satisfaction. Organizations don’t need to overhaul major business processes to achieve these targeted results, says Taylor.

In fact, there are a number of steps organizations can take to successfully introduce AI to alleviate staff workload.

Start with a small pilot project. This could include automating a frequently asked question or ticket routing, to demonstrate the value of AI without overhauling processes. These pilot projects can be expanded as success is proven.
Prioritize automation of routine tasks. “AI can have a big impact here,” Taylor says. “Use AI to drive automation for repetitive, low-complexity tasks like ticket classification, prioritization, and routing. This helps reduce manual effort and improves response times.”
Educate and train help desk analysts. A lot of organizations talk about AI and its benefits at a high level, notes Taylor. “But that rarely filters down to the help desk analysts taking end user calls.” Equip the team with the necessary training to work with AI tools. Ensuring they understand how to use the tools effectively will alleviate concerns and boost engagement.

Prioritize high-quality data

Effective AI is dependent on high quality data. “The number one help desk data issue is, without question, poorly documented resolutions,” says Taylor. “High quality documentation results in high quality data, which both human and artificial intelligence can exploit.” Upskilling help desk staff to create good documentation is a critical step in leveraging AI for improved operations.

Ivanti’s service automation offerings have incorporated AI and machine learning. These technologies handle ticket classification, improving accuracy. Accurate classifications, in turn, can be used by AI to route problems consistently for fast resolution. Finally, Ivanti software uses AI to see where and how incidents are clustering, exposing root causes and enabling the help desk to craft a systematic response.

The bottom line

IT leaders can start breaking the repetitive, exhausting help desk logjam. They can tactically exploit AI and machine learning in small projects that relieve the workload, improve end user satisfaction and build trust in AI’s capabilities. High-quality data is essential for effective AI.

Reduce Your Carbon Footprint: The Role of IT Asset Management

Fri, 03 Jan 2025 16:13:08 Z

Sustainability has shifted from being a trendy, “nice-to-have" option for companies to a mandatory core business strategy for remaining relevant and competitive.

Over 40% of the information and communication technology (ICT) sector's carbon emissions are tied directly to IT assets, according to the World Bank. So, these organizations are actively seeking ways to curb their environmental impact and to reduce energy costs without sacrificing operational efficiency.

One powerful yet often overlooked tool in this quest is IT Asset Management (ITAM). By strategically managing IT assets throughout their lifecycle, organizations improve their sustainability outcomes, corporate reputation and reduce energy spending.

Understanding digital carbon footprint

A carbon footprint is a measurement of the total amount of greenhouse gases, primarily carbon dioxide (CO2), released into the atmosphere because of the activities from a particular individual or organization. It's typically quantified in tons of carbon dioxide equivalent (CO2e), which includes direct emissions from energy consumption and indirect emissions from the lifecycle of goods and services.

A digital carbon footprint refers to the greenhouse gas emissions specifically caused by the use of digital devices, internet services and data centers plus emissions from manufacturing and disposal. For organizations, a high digital carbon footprint can lead to increased operational costs due to inefficient energy use, potential penalties for non-compliance with environmental regulations and damage to the company’s reputation.

On the other hand, organizations that manage and reduce their emissions can benefit from cost savings, an improved brand reputation and access to new market opportunities. IT organizations have a need to show leadership in how they can support companies' environmental, social and governance (ESG) initiatives, and ITAM can contribute to that.

The role of IT Asset Management in digital carbon footprint

ITAM helps companies reduce their digital carbon footprint by tracking, managing and improving the footprint of their IT assets over their entire lifecycle. This practice encompasses everything from hardware and software to licenses and contracts, ensuring that every asset is utilized efficiently and effectively. By providing a comprehensive overview of an organization's IT landscape, ITAM lays the groundwork for strategic decision-making that aligns with sustainability goals.

ITAM serves as a central point to track and minimize carbon output by providing a comprehensive understanding of the carbon contribution of IT assets. Research has shown that e-waste is a major contributor to global emissions, accounting for roughly 6% of total emissions. By effectively managing the lifecycle of assets, ITAM allows organizations to extend the life of existing resources and defer new purchases, thereby reducing the environmental impact associated with procurement and disposal.

ITAM also plays a significant role in promoting sustainability within an organization. By providing a wholistic view of an organization's carbon footprint, ITAM can analyze and provide informed decisions about hardware and software upgrades. This includes suggestions like the greater adoption of eco-friendly hardware, the implementation of green software solutions and more effective management of e-waste.

Additionally, ITAM may support compliance with environmental regulations by maintaining accurate records of asset disposal and recycling, ensuring that businesses adhere to legal requirements and avoid penalties. By integrating ITAM with a digital employee experience platform, organizations can also inform employees about their carbon footprint and offer suggestions for reduction. This fosters a community-driven approach to carbon reduction, engaging everyone in the sustainability effort.

ITAM: A strategic tool for cutting your digital carbon footprint

ITAM is more than just a solution for managing the financial aspect of IT assets; it’s a strategic approach to holistically optimize the value of IT assets, including the option to significantly reduce a business's digital carbon footprint.

By leveraging the capabilities of ITAM, organizations can achieve a balance between operational efficiency and environmental sustainability. Through careful tracking, analysis and optimization, ITAM empowers businesses to take proactive steps towards a greener future, benefiting both the environment and the bottom line.

Learn how Ivanti Neurons for ITAM can help you track and reduce your organization's carbon footprint.

ITAM or CMDB? Why You Need Both

Tue, 03 Dec 2024 16:28:54 Z

Many organizations look to IT asset management (ITAM) solutions to ensure all their IT assets are discovered, tracked, secured and disposed of at the end of each asset’s lifecycle.

Some IT administrators ask if they can use a configuration management database (CMDB) for their ITAM requirements. But others worry that tracking IT assets in two solutions will require them to duplicate each asset record and increase their workload.

What is ITAM?

ITAM is a set of best practices for tracking IT asset inventory. Its objectives are to manage an IT asset’s overall cost, including ownership, contracts associated with the asset lifecycle, warranty and refresh information.

ITAM focuses on IT assets from an organization’s financial perspective. When organizations follow ITAM best practices, they can make informed decisions about technology acquisitions. Furthermore, they can avoid unexpected costs and penalties associated with software audits.

What is CMDB?

A CMDB is a central repository of information about an organization's IT assets. That includes details about hardware, software, networks and their various relationships.

Configuration management involves tracking IT assets from an operational and support perspective. Since asset availability and stability impact an organization’s day-to-day operations, assets need to be documented along with their configuration and service offerings.

Do you need ITAM if you’re using a CMDB?

Determining whether you need ITAM when using a CMDB will depend on the size of your organization and complexity of its IT service management (ITSM) needs. An organization might find it attractive to avoid purchasing a separate software solution or train employees on an additional product. Managing ITAM data in the ITSM solution could simplify building and managing request fulfillment processes.

Most CMDB solutions provide extensive customization features, so it is possible to customize a CMDB with ITAM properties and features. But CMDB objectives are much different from ITAM objectives.

Imagining your city or town’s bus service offers a basic example of how different data — route number and bus number — are used for different objectives. Buses are assigned routes, and each route is assigned a number displayed on the bus. A second number is assigned to each bus so it can be tracked through its lifecycle. Administrators assign different buses to a route without impacting the bus route number. And it would confuse things if the number used to identify a physical bus was the same number as that of a bus route.

A CMDB configuration item (CI) representing an email service — the “route” in our analogy — will most likely outlast the lifecycle of the asset, a physical server — the “bus” — used to provide the email services.

Storing ITAM data

A CMDB could store all your ITAM data, but significant CMDB modifications would be needed to meet ITAM requirements. The CMDB lacks discovery capabilities, so connectors or integrations to external IT asset discovery tools must be implemented to ensure IT asset configuration information is discovered and kept up to date in the CMDB database.

Further customizations would need to be added to the CMDB, which may be expensive. And even after applying ITAM capabilities to the CMDB, it would still be unlikely that an organization would have a complete ITAM solution. This type of ITAM may be sufficient for a smaller organization, but the CMDB would need to be modified so it could handle contract, financial and lifecycle information.

Additionally, IT asset manager roles would need to be created in the ITSM solution, with appropriate rights to the CMDB for the ITAM administrators. Beyond this, ITSM processes would need to be modified or added to provide ITAM process functionality.

Perils of a single database

Storing excessive unrelated data in a CMDB, especially data unrelated to the specific business problem like mapping a business service into the CMDB, can result in a very large and expensive database. The more extensive the stored data is, the more time, effort and human resources are needed to maintain accurate data.

If a database isn’t accurate, it can’t be trusted. With many people maintaining and making changes to the data, you run the risk of unapproved changes – potentially to business-critical configuration items (CIs). Limiting the amount of data will also limit the number of people who can make changes to the data, maintaining its integrity. This is a solid argument for having separate tools for CMDB and ITAM.

Plus, putting too much data that might be irrelevant to relationships or business services into a database creates the risk of overloading anyone trying to interpret or view that data with unnecessary information.

What about asset reports?

Incorporating complete details about IT assets into the CMDB can simplify the creation of IT asset reports. A CMDB provides insights into the relationships among IT assets, including their configurations, the risks of changes and the impacts of those changes. It also differentiates from standard ITAM solutions, which typically track the hierarchical associations between IT assets.

Centralizing all ITIL and ITAM asset relationship data within the CMDB may make reporting more straightforward and cost-effective than using disparate databases. But this would demand extensive modifications to the CMDB.

Learn more: Ivanti Asset Manager free demo

Why two solutions to track IT assets?

Change management is vital for ITSM solutions that follow ITIL best practices. ITIL provides guidance and best practices for handling changes to an IT environment to reduce risk associated with IT configuration changes.

ITIL best practices suggest that IT assets providing operational services be documented and tracked using a CMDB. Each asset tracked using a CMDB is a CI that could be a hardware asset, a software asset or multiple assets combined to provide an IT service. Each CI is tracked to ensure it’s operational.

An ITAM solution addresses different goals and provides its own benefits. Many organizations want to centralize all data in a single source of truth, but it might not be the best place to store every type of data. For instance, some want to put contracts, process guidebooks and policies into their CMDB. Storing this sort of very specific data in a tool that specializes in managing it ensures the right functionality is in place.

In the case of contracts, an ITAM tool or contract lifecycle management system would store them in a proper format so they can be imaged, key dates pulled out and workflows created or associated with cost centers or groups.

CMDBs aren’t designed to support this level of detail without extensive customization. Selecting the right management tool for certain types of data and then linking or integrating it to the CMDB can ensure functionality isn’t sacrificed for centralized convenience.

Does it make sense to track an IT asset in both a CMDB and an ITAM solution? Not really, when there’s a way to avoid duplicating IT asset records with a solution that integrates the CMDB with an ITAM solution.

Imagine the database that manages the bus route services. That database would track service-related items such as schedules, drivers and the bus assigned to the route. With integration, administrators would simply assign a bus to a bus route using a lookup table that shows available buses. When the CMDB is integrated with the ITAM solution, the IT asset can be directly linked to the CI instead of being recreated and duplicated.

ITAM vs. CMDB: It’s not about “versus”

Trying to use CMDB to take on the asset management role of ITAM has sizable downsides. It’s not really about “CMDB vs. asset management,” then, because ITAM and the CMDB are critical for any enterprise leveraging technology at a high level.

IT assets providing services to the organization need to be tracked using a configuration management process, per ITIL best practices. Those IT assets also need to be tracked using ITAM best practices to avoid unexpected costs that result from lost or stolen assets, uninformed acquisition decisions and unlicensed software. To ensure seamless integration, organizations should consider using an ITAM solution integrated into a service management platform.

3 Keys to Evolving Toward Enterprise Service Management

Mon, 02 Dec 2024 21:58:37 Z

With businesses scaling up operations amid the increase in remote work, extending IT services across business units to HR, Facilities and beyond is essential.

Enter enterprise service management (ESM), extending the proven principles of IT service management (ITSM) across various departments and functions within an organization.

The benefits of ITSM

Ivanti’s experience with ITSM offers clues to the benefits that ESM can spread across an organization.

30%

faster ticket resolution with automation and improved workflows.

20%

improvement in resolving issues on the first contact.

50%

reduction in tickets by empowering users with self-service options.

Properly managed ITSM creates efficient standardization and commonalities within processes and assets. These can include the IT services catalog, knowledge management repository, forms, reviews and approvals and self-service portals.

Why evolve to ESM?

With the success of ITSM, it makes perfect sense to extend its benefits to other parts of the organization. ESM goals are very similar, if not identical, to those of ITSM:

Simplify access to services: Improve operational efficiency using simplified workflows and streamline access to services and support by removing complexity.
Engage employees anywhere: Streamline self-service to enable employees across any digital experience and remove barriers for employee engagement.
Support hybrid work: Enable support for employees regardless of location. Automate and simplify processes to facilitate work from the home, office or remote location.

Begin with a solid ITSM foundation

To evolve toward ESM, start with a firm foundation in ITSM best practices. Only once you’ve optimized core processes can you be sure you can explore expanding that success into other business areas.

It's not effective to promise solutions to other units if the IT department is known for not delivering on time or if users encounter constant digital employee experience (DEX) issues. Additionally, some employees are simply reluctant to change their processes, especially if they believe their current methods are working well. They might not see a need to seek external help; sometimes, it's easier for them to do nothing.

Is ESM really needed?

When looking at a specific organizational unit, are you positive they need ESM?

To answer that question if you’re an IT manager, ask yourself: How do you currently interact with the department(s) in question, such as HR or Facilities? Do they have multiple locations? Are interactions only via email? How long do they take? How much visibility is there into processes? And in dealing with them, how does it make you feel?

Some complimentary questions that should be asked on the line of business (LOB) side: How does a manager know a team’s workload? How is work prioritized? Are communications recorded and audited? What workflows are automated? How do teams conduct handovers? How is service delivery measured?

Answers to these questions will tell you if you should move forward with ESM.

Keys to ESM adoption

If ESM implementation is warranted, observe these key steps:

Start simple

New ESM users within a different department might have to be gradually acclimated to the new tools being provided, so begin with these foundational functions:

Segregate email intake: Make emails automatically generate a case or query; this is readily accomplished using a full-featured ESM solution.
Build reporting and dashboards: This not only provides visibility into processes so users can identify and address issues, but also lets them track performance against KPIs to justify expanding services and promoting ESM adoption to other units.
Knowledge management and policies: This is the stage where it makes sense to put the right systems in place to record (and share) how issues are remediated and what best practices should be followed.

Evolve ESM capabilities

Once ESM has proven its value and gained traction with its new users, then:

Implement self-service: “Shift left” is eminently desirable in ESM, too, so provide tools such as a self-service portal where everyone in that unit or department can access a knowledge base that’s specific to their group or submit requests.
Automate: Automating basic or oft-repeated responses will cut costs, minimize errors and accelerate remediation. Analyze incidents within each business unit to find its specific common cases that should be automated: HR and Facilities, for instance, won’t have the same issues.
Set up chat: Users should be able to request a chat session with a live analyst via the self-service portal.
Establish SLAs: In extending ESM to different business units, establish SLAs specific to that unit so there are clear expectations, service standards and objectives.

Integrate

Integration is key, especially when it comes to seamlessly aligning HR, Facilities and IT systems. A good ITSM/ESM solution should offer integration platform as a service (iPaaS) tools that make it easy to connect with enterprise systems that include:

HRMS
Payroll management
Employee onboarding
Other LOB systems

Use their terminology

Understanding the unique terminology and requirements of different business units is vital. Don’t throw IT jargon at them; use language they’re familiar with. An HR staffer might want to open a “case,” while a Facilities worker will think in terms of a “work order.”

Tailoring communication fosters better buy-in and engagement and helps prevent the wrong lingo from confusingly popping up in their forms and processes.

Know their services

To help them enable better service delivery, it's crucial to wrap your head around their service offerings. One action you’ll need to take is to build a service catalog that contains a centralized list of all ESM services available to employees of that business unit, clearly organized and presented.

Prioritize the services listing so the most important or commonly requested services are first and users won’t have to search for them.

A strategic move: Begin with HR and Facilities

These departments typically have a wide variety of service needs that can benefit from ESM. Each deals with a diverse assortment of needs that provide excellent use cases that can demonstrate tangible benefits to support broader ESM initiatives.

HR pain points

Reducing the time to fill open positions by streamlining recruitment, improving candidate tracking and accelerating hiring processes.
Improving employee experiences through proactive HR services, self-service options and transparent communication.
Reducing employee turnover through proactive employee engagement strategies and improved talent management.

Facilities challenges

Reducing maintenance costs via preventive maintenance and efficient work order management.
Improving space utilization by optimizing space allocation and tracking space usage.
Enhancing occupant satisfaction by addressing comfort and safety concerns promptly.

Overcoming resistance

Transitioning from ITSM to ESM is not without challenges. Common hurdles include resistance to change, budget constraints and the need for IT departments to earn credibility.

By focusing on delivering a better employee experience and showcasing the value of ESM through tangible metrics, you can drive successful ESM adoption.

Beyond initial implementation

As organizations navigate toward wider ESM adoption, continuous improvement and collaboration are in order. Regular check-ins and metrics tracking will help monitor progress and refine strategies over time and further prove ESM’s value.

By empowering business units with visibility, reporting and efficient workflows, ESM can be a catalyst for organizational growth and innovation. This journey from ITSM to ESM is really a strategic evolution of an organization’s operational DNA, resulting in a business that’s more agile and responsive across the board.

Changing IT Service Management: East Coast City’s Journey with Ivanti’s Enterprise Service Management Solutions

Tue, 26 Nov 2024 16:08:57 Z

In every city, a complex web of technology ensures seamless operations. Imagine the chaos if traffic lights or the subway stopped functioning. Information Technology Service Management (ITSM) plays a crucial role in maintaining urban environments and preventing city-wide disruptions.

Recognizing this, the City embarked on a journey to transform its ITSM capabilities, creating a blueprint for future enterprise service management. By transitioning to Ivanti’s Enterprise Service Management (ESM) solutions and partnering with T4S Partners, the city addressed the limitations of its previous system and introduced functionalities that better align IT with broader business objectives.

The City faced significant challenges with its existing ITSM system, which became difficult to manage and scale. Relying on a highly customized Cherwell Service Management (CSM) platform approaching its end-of-life, complexities and fragmented data across multiple sources led to inefficiencies, hampering operations and strategic decision-making.

Despite the challenges, the benefits were significant, such as improved service delivery and quality of life for residents. Advanced automation capabilities and a comprehensive Configuration Management Database (CMDB) streamlined IT operations and laid a robust foundation for future digital transformation. The successful ITSM migration not only improved day-to-day operations but also set a precedent for future technological progress. To achieve a successful migration, the first phase focused on a comprehensive project plan aimed at elevating Information Technology Service Management (ITSM) capabilities.

ITSM Migration Project Overview

Mission:
- Elevate Information Technology Service Management (ITSM) capabilities.
Goals:
- Integrate key systems.
- Enhance process maturity.
- Leverage automation.
- Bolster portal and reporting capabilities.
- Streamline IT operations.
- Align IT services with the city's business goals.
Platform Selection
- Chosen Platform: Ivanti's Enterprise Service Management (ESM) solutions.
- Key Features:
  - Robust capabilities.
  - Scalability.
  - Proven track record in large-scale implementations.
  - Comprehensive Configuration Management Database (CMDB).
  - Advanced Change Management capabilities.
Implementation Partnership
- Partner: T4S Partners, a Premier Channel Sales Ivanti partner.
- Role and Requirements:
  - Deep understanding of Ivanti's offerings.
  - Navigated migration complexities.
  - Ensured seamless implementation without disrupting existing operations.
  - Key to achieving improved process maturity and service delivery.

To further enhance these successes and future impacts, the City undertook a strategic migration to Ivanti's ITSM and ITAM solutions.

Migration benefits of Ivanti ITSM and ITAM

The City gained significant advantages by switching from the outdated Cherwell system to Ivanti's modern ITSM and ITAM solutions. This transition prevented end-of-life issues and provided a more robust framework for enterprise systems management. It not only solved immediate problems but also brought new features that improved overall service delivery.

Retiring old systems reduced technical debt and brought benefits. Ivanti's platform improved the service catalog and support portal, making it easier for users to request services. The centralized configuration management database provided accurate data, increasing the efficiency of support operations. Neurons for Discovery automated asset management, making the IT environment more transparent.

The migration included automation features to improve service requests and onboarding. Automating routine tasks freed up IT staff to focus on strategic initiatives and ensured efficient handling of service requests, leading to faster resolutions and improved user satisfaction.

Ivanti's solutions provided a systematic approach to change control, ensuring changes were well-documented, authorized and implemented smoothly. This was essential for preserving the integrity and reliability of the city's IT services. Despite the systematic approach and benefits provided by Ivanti's solutions, the City faced several challenges during the transition to the new ESM system.

Overcoming challenges

As the City aims to streamline operations and improve service delivery, a comprehensive Configuration Management Database (CMDB) became vital. Serving over 4,000 users, the service desk's limitations in asset management and discovery hindered timely incident response and asset tracking.

One primary hurdle was integrating with Microsoft's Entra ID, initially posing a significant roadblock for seamless migration of user data and access control. Ivanti’s technical support team stepped in with robust solutions, ensuring smooth integration and maintaining the project's momentum.

Data fragmentation was another challenge. The previous ITSM system caused data to be scattered, making it difficult to use the new CMDB and Asset Management solution fully. Ivanti’s solutions introduce a cohesive data management strategy, consolidating and streamlining information to improve IT asset tracking and management.

The City’s complex customization requirements added another layer of complexity. The absence of advanced Change Management solutions and automation capabilities was also a critical pain point. These features are essential for ensuring service delivery continuity and operational efficiency in a fast-paced urban setting. Recognizing these gaps underscored the need for a more robust ITSM solution that aligned IT services with business goals.

With the support of T4S Partners and Ivanti’s advanced solutions, these challenges were effectively addressed. Ivanti's solution's flexibility allowed seamless integration of custom processes, ensuring a smooth transition without disrupting ongoing operations.

Overcoming challenges in automation and discovery was also critical. These abilities were essential for improving service delivery, and careful planning ensured their successful implementation. The collaboration with T4S Partners was instrumental in managing the initial setup and setting the stage for future digital transformation.

The City’s experience highlights the importance of a robust and adaptable ITSM solution, a well-thought-out transition strategy and the value of expert support. Advanced ITSM solutions have a transformative impact on improving operational efficiency and service delivery.

Aligning IT with business goals

Building on this understanding, the City strategically adopted Ivanti’s Enterprise Service Management (ESM) solution to further align IT Service Management with its goals for enhanced efficiency, accuracy and user experience.

By integrating Neurons for Discovery with the CMDB, the City improved asset and configuration management, addressing Intune connector issues and laying the groundwork for better incident handling and change management. This led to efficient asset tracking, reduced downtime and improved service delivery.

Ivanti’s platform also improved incident handling and streamlined change management, boosting response times and service quality. Comprehensive surveys ensured IT services met user needs, refining service request workflows and improving the customer portal's user-friendliness. Automating service request management allowed IT to focus on strategic initiatives, aligning IT capabilities with the City's goals and modernizing service management for future digital transformation.

These strategic improvements positioned the City for long-term success, showing its dedication to improving service delivery and the quality of life for its citizens through aligned IT and business goals. Having established these strategic improvements, the City continued its digital transformation journey by moving to IT Service Management.

Implementation Approach

The City’s move to IT Service Management with Ivanti Neurons for ITSM is a major step in the city’s digital transformation journey. The move not only addressed the immediate challenges of the previous system, but also introduced advanced capabilities such as automation and a full CMDB, which will help the city grow and innovate in the future. The new platforms capabilities in asset management and discovery have significantly improved the city’s IT capabilities, ensuring that IT services are closely aligned with the city’s business goals.

The partnership between T4S Partners and Ivanti was key to the success of the transition. T4S Partners’ expertise made the migration process seamless and non-disruptive to the City’s operations. This partnership has laid a strong foundation for the City to continue to improve its IT operations, showing the City’s commitment to improving service delivery and the quality of life for its residents. The implementation of advanced Change Management tools has further enhanced the City’s ability to adapt to the ever-changing technology landscape, ensuring the City’s IT infrastructure remains robust and efficient.

Conclusion

The City’s transition to Ivanti Neurons for ITSM marks a major milestone in its digital transformation journey. This move overcame previous system limitations, significantly improving IT capabilities. The modernization project introduced advanced ITSM functionalities like a robust CMDB, Asset Management and Change Management to align IT with the city’s business goals. Automation and discovery capabilities will help the city adapt to technological changes, improving service delivery and residents' quality of life.

Partnership with T4S Partners was crucial, as their expertise ensured a seamless migration without disrupting daily operations. This collaboration met project goals, from initial implementation to ongoing optimization.

By leveraging the strengths of both organizations, the City has set a strong foundation for continued IT improvements and created a blueprint for other municipalities aiming to modernize ITSM. The investment in Ivanti's ESM solutions promises long-term benefits, allowing the city to keep pace with technological advancements and respond to residents' evolving needs. This transformation underscores the City's commitment to innovation and the value of strategic partnerships in achieving successful digital transformations. Other municipalities are encouraged to explore similar upgrades to improve their services and meet community needs.

Learn more about Ivanti’s Enterprise Service Management solutions. For insights from industry experts, check out Ivanti's YouTube Partner Insights interviews featuring various Ivanti partners and Michelle Hodges, Ivanti’s Senior Vice President for Global Channels and Alliances. Additionally, we encourage you to engage with our online community by participating in our forums and webinars. These are great opportunities to connect with other IT professionals, share your experiences and learn from industry experts.

Eliminate infrastructure and reduce maintenance costs by moving to the cloud

Mon, 04 Nov 2024 15:50:11 Z

Today, companies are constantly searching for ways to streamline operations and gain an edge. Many, though, are weighed down by the burdens and costs of on-premises IT infrastructure. That’s why some are considering the benefits of cloud migration.

In this article, we’ll take a look at cloud migration benefits and how they help you save money, scale your business and improve your operations. We’ll talk about how getting rid of on-site infrastructure, lowering maintenance costs and using the latest security technologies can help businesses of all sizes.

Lower costs and increase scalability

By moving to the cloud and leveraging its pay-as-you-go model, businesses can avoid investing heavily in on-site infrastructure, such as servers, software and data centers. This eliminates the capital expenditures associated with purchasing and maintaining hardware and software, freeing up valuable financial resources that can be reallocated to other areas of the business.

Scalability is another major benefit of moving to the cloud. Businesses can easily scale their IT resources up or down based on their needs, ensuring that they only pay for the resources they use. This is particularly helpful for businesses with fluctuating workloads or seasonal demands. By not overprovisioning infrastructure, they can optimize their IT spending and avoid unnecessary costs.

Furthermore, the cloud opens the door to using the latest hardware and software, empowering businesses to improve their performance and agility. With cloud providers handling infrastructure updates and maintenance, companies can focus on their core business, free from the burden of managing and updating systems. This allows them to remain competitive and responsive, driving innovation and growth.

Reduce costs by eliminating on-site infrastructure

Moving to the cloud means more than just not having to buy and maintain hardware. It also means significant reductions in the ongoing costs of on-site infrastructure. By migrating to the cloud, companies can avoid the cost of maintaining physical servers, storage systems and networking equipment. This means no more capital expenditure for hardware, no more power and cooling costs and no more maintenance contracts. Instead, companies can direct that money into initiatives that drive growth and innovation and move their business forward.

In addition, by reducing the need for an on-site infrastructure, you reduce the need to hire IT personnel to maintain and troubleshoot it. That means your existing IT team can spend less time on routine maintenance and more time on other projects that drive business value. And when you work with a cloud provider, they provide a team of experts who are always monitoring and optimizing their cloud infrastructure to make sure it’s both highly reliable and performing at its best.

And, because cloud providers benefit from economies of scale, they can provide infrastructure services at a lower cost than on-premises solutions. They do this by making significant investments in state-of-the-art data centers, using energy-efficient technologies and optimizing resource utilization. As a result, your business can save money without sacrificing quality or performance, which is especially important in today’s competitive environment.

No need to worry about applying upgrades and patches

A major benefit of cloud computing is eliminating the need to apply on-premises upgrades and patches. This shift reduces the risk of human error and delayed upgrades while freeing up IT resources to focus on strategic business initiatives. By removing the complexity of managing vendor relationships for system updates and patches, organizations can significantly streamline IT operations.

Furthermore, cloud computing providers offer reliable and secure data backup and disaster recovery solutions. This means that in the event of a natural disaster or system failure, businesses can quickly and easily retrieve their data and continue operations without major disruptions. This level of data protection and resilience is often difficult and costly to achieve with on-premises systems. With cloud computing, businesses can enjoy peace of mind knowing that their valuable data is always backed up and readily accessible.

Eliminate downtime caused by on-premises upgrades

One of the most attractive advantages of moving to the cloud is the elimination of downtime caused by on–premises infrastructure upgrades. These upgrades can be required at regular intervals, often involving lengthy downtime and disruptions to business operations. This can result in lost productivity and revenue as well as customer dissatisfaction.

In contrast, cloud computing offers a seamless and continuous upgrade process. Cloud providers handle all infrastructure maintenance and upgrades, ensuring minimal or no downtime for businesses. This allows organizations to focus on their core competencies without worrying about the complexities of IT management. By eliminating downtime, they can maintain uninterrupted operations, improve customer satisfaction and gain a competitive edge.

Furthermore, cloud computing offers access to cutting-edge security measures and compliance certifications. Cloud providers invest heavily in robust security infrastructure and employ dedicated security teams to protect data and systems. So, businesses can enjoy heightened security without the need for substantial investments in their own security infrastructure. This not only reduces costs but also guarantees adherence to industry regulations and standards.

Showing a green commitment

Beyond security, cloud computing also plays a role in environmental sustainability. Moving to the cloud means businesses can reduce their carbon footprint by decreasing energy consumption and minimizing hardware waste. This is particularly relevant as sustainability and responsible resource management are increasingly important. Embracing cloud computing isn't only a smart business decision but also a way for companies to demonstrate their commitment to a greener future.

In summary, cloud migration eradicates downtime, eliminates the cost of on-premises infrastructure and fortifies security. Making a move to the cloud delivers a strategic advantage for businesses in pursuit of efficiency, scalability and a competitive edge.

Cloud Migration Benefits – and the Challenges to Overcome

Tue, 29 Oct 2024 16:11:40 Z

Cloud migration has become a strategic priority for many organizations. By moving data, applications and IT resources from on-premises infrastructure to a cloud-based environment, they can see multiple benefits. But cloud migration also comes with its own unique challenges.

Gaining a deeper understanding of both the benefits and possible pitfalls of cloud computing is crucial before embarking on your cloud journey. Whether your goal is to reduce infrastructure expenses, improve time-to-market, or more easily scale your IT environment, these insights will empower you to make informed decisions and navigate the migration process with more confidence.

Benefits of cloud migration

We’ve said there are multiple advantages for an enterprise that makes this move, so here are some of the details.

Scalability

Resource elasticity: Cloud platforms offer elastic resources that can scale up or down based on demand. This enables businesses to handle diverse workloads without additional hardware investments.
Global reach: Cloud services have a global reach. Businesses can deploy applications closer to their users, reducing latency and improving performance.

Cost efficiency

Pay-as-you-go: Cloud computing operates on a pay-as-you-go model where businesses only pay for the actual resources they use. This aligns perfectly with scalability and contrasts with traditional subscription models where customers pay a fixed fee on a regular schedule regardless of their actual usage.
Reduced or eliminated infrastucture costs: Since organizations that move to the cloud no longer need to deploy extensive on-premises architecture to support operations, the costs of buying and maintaining those systems are minimized or eliminated.

Business continuity

Backup solutions: Cloud providers offer comprehensive disaster recovery solutions, ensuring business continuity in the event of infrastructure failures or other disruptions.
High availability: Cloud platforms are designed for high availability, with multiple data centers and redundancy measures in place to minimize potential downtime.

Security

Advanced protection: Leading cloud service providers invest heavily in security capabilities in order to protect cloud-based applications and their users from cyber threats and vulnerabilities. These include access control, identity management, encryption and compliance across multi-cloud and hybrid-cloud environments.
Regular updates: Cloud providers constantly update their security protocols to protect against emerging threats and ensure that businesses benefit from the latest security advancements.

Agility and innovation

Innovative technologies: Cloud platforms offer easier access to advanced technologies such as artificial intelligence, machine learning and big data analytics, enabling businesses to remain competitive.
Faster time-to-market: Cloud services can support faster application deployment, reducing time to market. With fewer infrastructure barriers, businesses can rapidly respond to changing market conditions and competitive threats.

Collaboration and remote work

The Everywhere Workplace: Cloud-based tools and services facilitate collaboration among teams, regardless of their physical location, enhancing productivity, efficiency and the overall employee experience.
Secure everywhere: The cloud supports remote work by providing secure access from anywhere to necessary applications and data, which has become crucial in the modern work environment.

Cloud migration challenges

As just seen, once applications have been migrated to the cloud, there are numerous benefits. But cloud migration can pose certain challenges. Anticipating them can help IT teams prepare for any potential issues.

Data security and privacy

Breach exposure: Migrating applications and sensitive data containing personally identifiable information (PII) to the cloud might expose that data to potential security breaches, so ensuring robust encryption and access control is critical.
Maintaining compliance: Ensuring compliance with industry regulations and standards can be challenging in a cloud environment. Regulated financial services, healthcare and e-commerce industries must choose a cloud provider that’s fully capable of supporting their specific compliance requirements.

Downtime and disruption

Migration downtime: The migration process can potentially cause downtime and disrupt business operations. Careful planning and a phased migration can help mitigate this risk.
Service interruptions: Although rare, cloud service outages can occur and impact business operations. Having a contingency plan in place is essential. Organizations with zero tolerance for downtime should design for redundancy by utilizing two or more cloud service providers.

Cost overruns

Uncontrolled usage and spend: Even with a pay-as-you-go model, cloud costs can spiral out of control without proper management. So, it’s essential to implement cost management practices and constantly monitor usage.
Hidden costs: Every cloud instance is unique. Beware of costs associated with data transfer, CPU, storage, memory and additional services that may not be initially apparent.

Vendor lock-in

Single provider dependence: Relying too heavily on a single cloud service provider may result in vendor lock-in, making it difficult to switch to an alternate provider or move back to on-premises.
Limited flexibility: Vendor lock-in can limit flexibility, as the cost, capabilities and limitations of their chosen provider may constrain businesses.

Skill gaps

Specialized skills: Migrating to the cloud requires specialized IT skills and expertise. Investing in training for your team and hiring experienced professionals is crucial for a successful migration.
Change management: Adapting to new cloud-based processes and tools can be challenging for employees at all levels. Effective change management strategies and pre-migration training are necessary to ensure a smooth transition.

Performance Issues

Latency and bandwidth: Although cloud resources are elastic, specific applications may experience latency and bandwidth issues, especially if the data centers are far from end user locations.
Resource contention: Over-subscribed cloud resources can lead to performance degradation if not properly managed.

Summary: Planning can equal migration success

Cloud migration offers many benefits, including scalability, cost efficiency, enhanced security, employee flexibility and access to the latest technologies. On the flip side, it also may involve several challenges, including exposure to security breaches, potential downtime, cost management issues and the risk of vendor lock-in.

But by carefully planning the migration process, addressing potential pitfalls and leveraging the expertise of skilled professionals, organizations can successfully navigate their cloud migration journey and open new opportunities for growth.

Learn how solutions like Ivanti Neurons for Zero Trust Access can protect enterprise cloud applications, data and devices from unauthorized access and threats. Team it with other cloud-enabled security solutions such as Neurons for RBVM and Multi-Factor Authentication to empower your organization with secure anytime, anywhere access to business-critical apps and data.

Named Licenses vs. Concurrent Licenses: Choosing the Right Model for Your Business

Wed, 25 Sep 2024 06:58:47 Z

When it comes to licensing for ITSM solutions, understanding the different types of licenses available and choosing the right one can significantly impact your business’s efficiency and budget.

While many subscription vendors only offer named licenses, some vendors also offer a more flexible concurrent license. Each has its advantages and situations in which it might be the better choice.

Many SaaS solutions only use a named-user licensing model, which can be costly for certain organizations. To offer more flexibility to customers, some software vendors provide concurrent licenses in addition to named licensing.

What are named user licenses?

Named user licenses, also known as fixed user licenses, are assigned to individuals who plan to use the system. Once a license is assigned to an individual, only that person can use this license to access software. The license is considered consumed, regardless of whether that person is using the software or not. This type of license is tied to the user’s identity and requires a unique username or ID.

By assigning licenses to specific users, software companies can control who has access to their software and prevent unauthorized use. This level of control assists in controlling budget and software spend and ensuring license compliance.

Named licenses are a simple, easy-to-manage licensing option for organizations with a well-defined user base. They provide a clear record of software usage, which can help simplify license management and ensure compliance with software license agreements.

Advantages of named licenses

Named licenses provide several benefits that make them a compelling choice in specific situations.

Personalization and security: Since the license is linked to a specific user, it can be customized to the individual role and needs within the company. This also adds a layer of security, as only registered users can access the software.
Simplicity in management: Managing named licenses is straightforward because each license is associated with a specific user. Tracking who has access to what becomes easier.
Compliance: It's easier to ensure compliance with software usage policies and licensing agreements since the allocation is clear and distinct.
Price: Compared to concurrent user licenses, named licenses are less expensive.

Disadvantages of named licenses

Overlicensing: An organization is required to license anyone who might use the software, so this may lead to having more licenses than actual usage. For example, you may have purchased 100 named user licenses but find that you only use up to 75.
Casual users: A casual user, such as a contractor or service provider who requires occasional access to the software, will still need a named license regardless of how many times they log in.
Shift workers: If you have staff who access your solution on different shifts, you must license users across all shifts.
Administration: Named licenses require reallocation of users as they come and go. Some vendors also place restrictions on how many times a named license can be reallocated.
Underlicensing: Most software vendors who license their products by named users don't restrict you from accessing their software without an actual license. However, without carefully monitoring usage, you might have more users using the system than you have licenses for. The vendor will typically perform a "true up" of your licensing to match the number of users who have used the software over the period.

Ideal use cases

Businesses whose employees need guaranteed access to software at all times.
Environments in which software usage is heavily integrated into the daily workflows of individual users.
Organizations with stable or slowly changing team structures.

What are concurrent user licenses?

Concurrent user licenses, also known as "floating" user licenses, are shared among a pool of users and offer a more dynamic and flexible model. These licenses limit the number of simultaneous users rather than the total number of users. For example, a company might purchase 10 concurrent licenses that any employee can use, but only 10 people can use the software at the same time.

Advantages of concurrent licenses

Cost effectiveness: This model can be more economical, especially if all users don't need the software at the same time. You pay for peak usage instead of individual access.
Flexibility: Concurrent licenses offer flexibility in a dynamic work environment in which different users might need access to the software at different times.
Maximized resources: These allow for efficient use of software licenses based on the fluctuating demands of the business.

Disadvantages of concurrent licenses

Understanding the number of concurrent licenses can be a complex task and requires constant monitoring to determine peak concurrent usage.
Concurrent licenses typically prevent users from accessing the software once the maximum number of concurrent users has been reached.

Ideal use cases

Companies with employees who use software intermittently or in shifts.
Organizations where software is needed for specific tasks that don’t occur daily.
Work environments with high employee turnover or fluctuating project demands.
Organizations that must expand usage to other areas.

How to calculate the number of concurrent users

There's no one-size-fits-all formula for determining the number of concurrent users. It can vary depending on your organization’s usage patterns. Some organizations might fall into a 3:1 ratio — meaning one license for every three users – but you could have higher or lower ratios based on usage patterns and peak activity. It's common to include a buffer as a safeguard in your calculation.

Example license calculation

Here's an example of calculating across named versus concurrent licenses:

An organization is licensing a new SaaS IT service management platform. The breakdown of users within the organization is:

Total people in IT: 1,000.

Service desk: 25 users across three shifts.

Morning shift: 10 users.
Afternoon shift: 10 users.
Night shift: Five users.

Change managers: 20.

Asset managers: Five.

External consultants: 20.

HR service management: 10.

	# named required	# concurrent required
Service desk	25	10	For the service desk, for named licenses we require one license per service desk user across all shifts. However, for concurrent licenses, we only need to purchase for the number of users in an individual shift – in this case 10.
Change managers	20	6	We have assumed for concurrent that only six change managers can be active at any time.
Asset managers	5	2	We have assumed for concurrent that only two asset managers will be active at any time.
External consultants	20	4	As external consultants must have a license, all named licenses are allocated even though they might be intermittent users.
HR service analysts	10	2	HR also wants to use the platform, so assumptions have been made across the number of concurrent users.
	80 named	24 concurrent

These concurrent user licenses are not limited to a specific role and can be used by any users up to a maximum of 24 concurrent users.

It should be noted that an organization can opt for a combination of both named and concurrent licensing.

Identifying the most appropriate model for your organization

The decision between named and concurrent licenses often comes down to analyzing your organization’s specific needs:

Assess usage patterns: Understand how often and predictably your team uses the software. Named licenses are better for constant daily use, while concurrent licenses are ideal for occasional access.
Consider budget constraints: If budget is a concern, evaluate the cost implications of each licensing type based on your usage patterns.
Evaluate administrative overhead: Consider the ease of managing each type of license in terms of IT overhead and compliance.

Named and concurrent licensing provide organizations with increased flexibility, and many choose to use both types simultaneously. The decision between named and concurrent licenses hinges on a business's operations and software needs. Careful consideration of these factors allows you to select a licensing model that suits your budget, enhances team productivity, and aligns with your operational workflows.

Ivanti offers concurrent and name licensing approaches. Find out more about Ivanti’s flexible service management options.