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Posted November 30, 2018 in Cloud

AI and Machine Learning in ITSM

Even though we may not recognize it, we all receive service from AI in some capacity, fairly regularly. This could be from a website chatbot or maybe even it’s what’s keeping your information safe at the bank. But not recognizing AI doesn’t mean that you don’t notice AI and this is especially relevant for ITSM. As AI becomes more mainstream, employees will continue to become accustomed to the level of service it provides in their daily lives; it will soon be expected at work as well. To maintain high levels of service and security, organizations should be creating roadmaps for how to integrate AI technology into their ITSM.

Major impacts of AI and Machine Learning in ITSM

The biggest way that AI will disrupt ITSM is by acting proactively instead of reactively. This is great news for IT, as finding ways to anticipate problems is an ongoing priority, but has been elusive due to the rate technology advances. AI and machine learning can help by actually anticipating everything from application failures to equipment maintenance and then can either solve these problems independently or at least notify IT. Finally, this may be a way to feel ahead of the game.

AI is capable of being proactive through conversational computing. Instead of guessing when a piece of equipment will fail and either replacing it before it truly needs to be replaced or waiting until it breaks down, AI will know when it will actually fail and will send a notification for a replacement. The organization dodges service interruption and saves money. As the IoT gains ground, AI will have even more access to equipment and will be able to manage lifecycles even easier.

Automating Backend Processes

A big part of ITSM relies upon someone recognizing a problem, submitting a request or issue into the system, and then someone else receiving that request and finding a solution. In the future, a vast majority of these requests or issues could be both identified and solved by AI.

This backend AI usage becomes even more powerful by integrating other technologies into the network and giving AI access to bigger databases in order to learn and anticipate even better. Patterns may emerge that would be impossible to detect otherwise and may give key insights into potential security incidences. Just think about what would happen if you had the ability to monitor every piece of IT and cross-reference any anomalies. You would see relationships indicating that there’s a problem so much sooner than if you waited until the issue was obvious enough that something stopped functioning.

Again, AI enables ITSM to be proactive.

AI in Onboarding and Employee Troubleshooting

With AI, onboarding can be a lot more seamless and can cut down on the back and forth often required for onboarding a new employee and setting them up with their IT needs. For example, AI could anticipate that a person sitting in a specific location in an office might need access to a certain printer. It would also recognize the role a person was hired for and could anticipate the permissions they would need as well as the software their role would demand.

Down the road, when that employee would like additional software, they could submit the request and AI would be able to know whether their system could handle the software as well as any upgrades they would require to complete the request. Just think of the number of emails that simple interaction would save.

AI in ITSM Example: ServiceNow Virtual Agent

Just as employees are used to having access to AI through chatbots in their daily lives, ServiceNow’s Virtual Agent brings that same functionality and convenience to ITSM. Instead of needing to contact IT for every need or issue they have, employees can use the Virtual Agent messaging to troubleshoot or submit requests. This instantaneous access to IT help reduces interruptions and allows individuals to resolve requests immediately. As we already mentioned, employees are accustomed to this level of service in their daily lives, so integrating it into their workflow can be relatively seamless.

AI Knowledge Management

AI’s trump card is its access to infinite data and the ability to interpret that data. This is the most valuable difference between AI and automation. Automation requires correct information to carry out a task while AI can interpret information and learn. AI can build, use, and update its own database. So, what’s left for those who work in IT to do?

As with almost any conversation about AI integration, the concern is always whether there will be job losses because of this technology. So far, AI seems to be freeing up time as opposed to replacing anyone. Like automation, AI can take care of time-consuming tasks, making ITSM much more efficient and also increasing service level. The job of ITSM is only becoming more demanding, especially with cybersecurity, so any way to free up time and energy is beneficial for everyone.

Interested in how to integrate AI into your organization’s ITSM?

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