How Artificial Intelligence (AI) Will Impact IT Service Management
"Alexa! Where are my keys?"
I am looking forward to a day when I do not have to ask anyone to help me find my keys. I am convinced that in the very near future, I will have that technology in my home. I am often teased by my wife and children about losing things around the house. “Someone must have broken into the house and stolen your keys” is a phrase I have heard too many times. Ha! Ha! Very funny!
I dream of the day when Alexa notices that I am forgetting something, like my wallet, then alerts me before I leave the house. How could that be possible? By making Alexa intelligent.
Artificial Intelligence (AI)
AI is technology that has the ability to learn, and as a result, provide responses that were not programed or predicted by its creators.
In a Gartner report titled Hype Cycle for the Internet of Things, 2016 , Gartner claims that, “Business and IT leaders are stepping up to a broad range of opportunities enabled by smart machines, including autonomous vehicles, smart vision systems, virtual customer assistants, smart (personal) agents and natural-language processing. Gartner believes that this new general-purpose technology is just beginning a 75-year technology cycle that will have far-reaching implications for every industry.”
Artificial Intelligence (AI) will dramatically improve technology in our homes and in the workplace. As AI infiltrates our corporate and government networks, IT Service Management (ITSM) organizations will be burdened with the responsibility to keep these systems up and running.
According to Gartner, “Employing AI offers enterprises the opportunity to give customers an improved experience at every point of interaction, but without human governance, the opportunity will be squandered.”
Initially, without humans to govern systems powered with AI technology, AI will not be successful. As we look even further into the future, advancements in AI technology will probably negate the need for human governance, but that is another topic for another day.
We should expect AI technology to impact ITSM offerings in three key areas:
- Point of Entry (Incident/Request Creation)
- Automated Backend Processes
- Knowledge Management
Before discussing these three areas, let’s explore how AI will impact some of the technology we use today.
AI in the Home
Introducing AI to existing technology such as Amazon’s “Alexa,” will provide it with the ability to learn. If Alexa can learn my unique habits or patterns that I follow before leaving the house, Alexa would be able to alert me if I was going to forget something I typically take with me.
Until recently, technology struggled when there existed an infinite number of possible outcomes for a given situation. AI will enable technology, such as Alexa, to read and interpret patterns, not just mathematical equations with a predicted outcome as most computer technology does today.
If Alexa is to help me find my keys, she (it) will have to be aware of her surroundings. Alexa will need to “see” the entire house. This type of technology is available today with 360 camera technology.
For Alexa to have the capability to alert me if am going to forget something, she will have to be able to read and understand patterns, or in other words, she will need to know that when I leave my house, I always take my wallet, keys, cell phone, and reading glasses. However, there are still many complexities associated with this scenario before a pattern can be established.
For example, Alexa would have to be smart enough to know the difference between me leaving the house to drive somewhere versus me leaving the house to work in the yard. I am sure that over time, there are enough consistencies in my process for leaving the house that Alexa powered with AI, would see certain consistencies and therefore identify a pattern.
Once Alexa establishes my pattern, Alexa would then be able to make predictions, which means she would be able to notify me that I am going to forget my wallet as I am getting ready to leave.
The word hello can easily be understood and translated by technology using pattern translation technology. It is simple math a=b. Although everyone has a unique tone or accent when saying “hello,” today’s technology can translate the dictionary meaning of “hello” and give an appropriate response using pattern translation technology.
Sometimes when I say hello, I am sad, and sometimes I am happy. However sometimes I am just tired. When I say hello to a person, that person may detect I am sad and say “what’s wrong?” However pattern translation technology is not equipped to handle an emotion associated with the pattern.
Chatbots powered by AI
If you whisper “hello” to Alexa, or if you have loud music playing in the background when you say “hello,” Alexa still has the ability recognize the pattern of the word and respond accordingly. But what if you want the technology to translate “hello” into a feeling?
In the future, we will see chatbots evolve with AI technology. There will come a day when chatbots will be able to understand what we mean, not just what we say. The challenge for programmers with technology available today is that it is very mathematical. A mathematical equation for translating someone’s words into feelings is not possible because there are too many variables and possible outcomes.
Pattern recognition technology, not to be confused with pattern translation, opens the door for AI to be able to “learn” and interpret an individual’s feelings, thus allowing for such a complex translation. Pattern recognition will be a key component for AI technology to succeed.
With IoT and smart machines flooding into the network, a big challenge for ITSM administrators is a lack of resources. The problem is that analysts are still personally involved with too many requests and incidents (one-to-one). For better or worse, we have to face the fact that in the future, human intervention for ANY request or incident (one to one) will not be sustainable. Therefore, we will see many organizations turn to chatbots with AI capabilities as a means to handle front line IT support calls.
ITSM solutions will experience disruptive changes as a result of AI technologies in the following three areas:
1. Point of Entry (Incident/Request Creation)
AI will ensure information is accurately interpreted before it is entered into an IT Service Management solution.
In a report titled Predicts 2017: Artificial Intelligence, Gartner claims that “Chatbots driven by artificial intelligence (AI) will play important roles in interactions with consumers, within the enterprise, and in business-to-business situations.”
Automated ITSM processes are designed to work when the information provided is accurate. I remember working with an organization that provided a self-service portal for requests and incidents. The online form that the end-users were required to fill out asked if they were making a request or if they are asking for help, which then determined the backend process that would be applied.
Unfortunately, many requests turned out to be incidents, and many incidents turned out to be requests. As a result, the end-user experience was negatively affected as requests and incidents were often delayed or lost.
Until these types of challenges are resolved, IT service management organizations will continue to be reluctant to remove human front line analysts. This is because they fear they might spend more time and money correcting errors caused by miscommunication from an inefficient system than they would spend on supporting the end user directly.
Adding AI technology to chatbots will enable automated ITSM solutions with the capability to interpret incidents and requests accurately. As the technology matures, we will see it improve and personalize the end-user experience in addition to improving the efficiency of the service management solution.
2. Automated Backend Processes
IT service management consists of backend processes that are designed to manage any request or issue entered into the system. Traditionally, requests and issues are entered into the system by an analyst or an end-user through a self-service portal. However, ITSM solutions that are integrated with other systems on the network will be able to detect and automatically open a request or incident without any human intervention.
For example, imagine an ITSM solution is integrated with a facilities management solution that manages IoT devices, such as smart lightbulbs. By communicating to the facilities management solution, the ITSM solution would be able to detect that a lightbulb is not working, then automatically open a service ticket, or open an asset request to replace the lightbulb without any human intervention.
Gartner states that “The next big shift is convergence of technology products and services to create next-generation service offerings that will include AI platforms. More specifically, Gartner defines these next generation service offerings as "intelligent automation" services that use one or more AI technologies (such as a cognitive-computing technology platform) as the basis of an offering's core value proposition.”
The power of AI in ITSM will manifest itself through integration with other technologies on the network. For example, integrating an ITSM solution with a solution that provides IT Operations Analytics (ITOA) would enable your ITSM solution to be notified of potential network issues.
Based on patterns, an ITSM solution powered with AI technology will be able to learn as it updates its knowledge database, ultimately improving how it reacts to any issue. In other words, AI will be equipped to remember past experiences so that it can learn from them.
If ITSM is integrated with every system installed on the network, then it will have the ability to see much larger patterns, making it more efficient. For example, imagine the ITSM system that is integrated with an ITOA solution, is also integrated with an IT security solution. If the ITOA solution detected an increased amount of browser crashes occurring on the end-user devices throughout the day, it would report that data back to the ITSM solutions as a potential problem.
The ITSM solution would be able to investigate that issue and cross reference the data with the IT security solution to find any patterns that might explain the anomaly. When the ITSM solutions logs the “problem” it would be able to provide insight, predictions about how the problem will progress, and recommendations about how to fix it.
As we move further into the future, the ITSM solution will be able to automatically correct the issues by working with the other IT solutions it integrates with on the network. No human intervention will be required.
3. Knowledge Management
ITSM solution powered by AI could then look to knowledge databases for answers. If they are not there, they will have the ability to go to trusted knowledge sites in the cloud. ITSM solutions powered with AI will be able to solve problems based on infinite amounts of data, and they will document these findings in knowledge databases that will also be used to support humans, both end-users and analysts.
Knowledge management solutions powered with AI technology will learn by applying “deep learning” techniques.
- Deep learning architectures ... have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, and bioinformatics where they produced results comparable to and in some cases superior to human experts.
Knowledge solutions powered with AI technology will change the way end-users ask for help. They will give accurate answers to almost any question very quickly. We live in a world where “instant gratification” has become the norm. We expect the right answer right now.
For me, when I lose my keys at home, I would much rather ask an intelligent Alexa device for help over asking my wife or kids. Why? First, I believe that Alexa powered with AI technology would be faster, providing me with instant gratification. Second, Alexa would not be annoyed with me.
Alexa will not care that I lose my keys several times a week, or that the keys I am looking for are right in front of me, she would just help me.
ITSM knowledge solutions in the future will not only provide answers to our IT questions, these solutions will be able to provide training and tips and tricks for end-users and analysts.
Eventually, much of the knowledge provided by an ITSM solution will be knowledge that was learned by the ITSM knowledge solution, versus documents that were created by human analysts, which are often outdated or not relevant to the current issue. However, until AI is perfected over the next few decades, human input will be vital for ITSM knowledge solutions.
The Future of the ITSM Analyst
In the future, human ITSM analysts will be replaced with self-service portals and chatbots powered by AI. Human ITSM analysts will shift their focus to major incidents (one-to-many), problem management, and change management. Over time, human involvement for any ITIL process will continue to decrease. Expect to see IT analysts of the future become much more focused on business objectives instead of IT objectives.
On April 6, 2017, an article was posted on Phys.org titled “Workplace diversity will soon include artificial intelligence,” In that article, Rebekah Hayden writes about Michael Harré (PhD '09), who is an AI enthusiast and lecturer in Complex Systems at the University of Sydney.
There is no doubt automation will change the workforce; and not just for repetitive tasks. AIs are already being used in law and medicine, not only to read and assess documents but to make recommendations, while advances in robotics are allowing doctors to perform surgeries remotely. Soon simple surgeries may even be performed by AI. Despite the pervasive fear that technology will innovate whole careers out of existence, Harré claims believe that people who are flexible and open to learning will continue to be in demand.
Although ITSM solutions are rapidly evolving, service management will never go away as long as IT exists. However, by implementing AI technology, IT service management will experience a disruptive change that will change the way humans are involved with the service management process. It is also important to note that these disruptive changes will affect all service management operations, not just IT service management.
Eventually, memory and learning capabilities in AI technology will not have a limit to how much they can remember and learn, which is what alarms many “futurists” who claim AI could one day become “self-aware.” However, for simple people like myself, I just look forward to an Alexa that is powered by AI. I don’t want to forget anything before I leave the house anymore, and I need a little help finding my keys every once and a while.