Widespread AI adoption has created more than a few challenges for information technology departments, which must now deploy, manage and secure AI applications and services alongside traditional IT assets. At the same time, AI has the potential to make IT service management — the work that typically occupies much of IT analysts’ time — much more efficient and less draining.
Here’s a look at six ways AI can supercharge ITSM, along with the caveats that IT teams must be prepared to address if they plan to hand off IT service work to AI.
What Is IT Service Management?
ITSM refers to the processes that IT teams use to plan, implement and manage IT services. It encompasses a wide range of tasks and responsibilities, ranging from deploying new servers, to monitoring and troubleshooting application performance problems, to responding to end-user requests for assistance.
1. Ticket Management
One of the most daunting tasks facing IT teams is handling the never-ending stream of tickets that staff receive. Most tickets come from monitoring tools that alert engineers about issues like failed servers. Tickets can also come from users who want to request support or service or have a problem to report.
Managing tickets can be messy for a variety of reasons. Tickets may be redundant in cases where a user submits multiple tickets for the same request, or where the same root cause results in multiple alerts; for example, if a server crashes, the team may receive alerts about the failure of the server itself, as well as any applications and databases hosted on the server.
In addition, tickets can be hard to assess because they include a lot of data and it’s not always immediately clear what’s relevant to the issue and hand and what’s not. Traditionally, IT teams had to sort through tickets manually to interpret what each ticket meant and trace them to root causes.
But now, they can let AI do this tedious work for them. AI can identify redundant requests. It can also summarize lengthy tickets so they're easier for IT staff to review, and it can set priority levels for requests to clarify which ones staff should address first.
2. Automated Response
IT teams used to use basic rule-based or pattern-matching automation to manage tasks like sending a user a link to reset a password in response to an email containing phrases such as “lost password.”
But with AI, automated responses can become much more sophisticated, making it possible to automate complex tasks that would previously have required human intervention. For example, instead of a simplistic pattern-matching system that responds to user queries with links to self-service resources (like password request links), IT departments can deploy AI-powered chatbots that engage in live interactions.
Rather than merely sending a user a link to reset a password, a chatbot that integrates with a business’s identity management service could reset it for the user, leading to a smoother experience for the user and a lower risk that the user will end up needing hands-on support from a technician due to a failed self-service experience.
3. Guiding IT Response
Even in cases where service requests are too complex to be automated completely, AI can play an important role. It can, for example, review service requests and provide recommendations to IT staff on how best to fulfill them based on resources like the IT department’s documentation database or data showing how technicians resolved similar requests in the past.
This allows IT teams to solve issues faster and with less assessment and planning effort. In addition, using AI to help guide manual response operations can enable a more standardized approach to ITSM. This is because AI can offer consistent recommendations, whereas individual engineers might choose to approach problems in different ways.
4. Personalizing ITSM
Requesting support has often required submitting tickets and being treated like a generic user. With AI, however, it’s become possible to personalize ITSM experiences.
For instance, an AI user support chatbot could analyze customer histories and tailor responses based on them, eliminating the need for the user to provide the information he or she has already supplied or to respond to recommendations that aren't relevant.
In addition to providing a more satisfying experience for the user, personalization can reduce the time necessary to fulfill support requests, thanks to the ability to hone service based on unique user needs.
5. Predicting ITSM Resource Requirement
Knowing how many IT staff members you’ll need to meet ITSM needs is often a challenge because there is no way to predict with full accuracy how many requests you’ll receive or how complex those requests will be.
Businesses can use predictive analytics, a type of AI that predicts future trends based on historical data, to forecast service demands. In this way, IT teams can more accurately predict how many resources they’ll need to support a wide variety of ITSM tasks, such as hardware management, end-user support and new software rollouts.
6. ITSM Optimization
Beyond assisting in day-to-day operations, AI-powered analytics tools can help to identify ITSM trends and challenges by examining service data. For instance, an analysis of ticketing data might reveal which types of incidents take the longest to respond to, or show how response time varies relative to how many technicians are staffing the help desk.
With these insights, IT departments can make informed decisions about how to optimize ITSM over time. They can identify bottlenecks and opportunities to streamline workflows, resulting in a better experience for users and greater operating efficiency for IT teams.
The Limits of AI-Based ITSM
AI can’t automate all aspects of ITSM, at least not in the foreseeable future. Some ITSM tasks are too complex for AI to handle. Plus, limitations like hallucination risks in generative AI technology make it challenging to trust AI to make high-stakes decisions without requiring humans to approve them. In this sense, we remain a long way from achieving NoOps, meaning an approach to ITSM that fully eliminates the need for manual management.
But even though AI isn’t perfect, it can still transform ITSM. Now is the time for businesses to begin taking full advantage of AI within ITSM, lest they be left behind as AI upends the way IT departments work.
