Ok, so we were sceptical, but Artificial Intelligence (AI) is no longer a futuristic concept—it’s here, and it’s making a massive impact on IT Service Management (ITSM).
Let’s not overlook the fact that it comes with some maturity considerations (I’ll come back to that later), but whether it’s automating mundane tasks, predicting incidents before they happen, or enhancing the user experience, AI is beginning to change how IT teams operate, forever.
Let’s dive into some of the key ways AI is being used in ITSM today.
1. AI-Powered Chatbots and Virtual Agents
One of the most obvious and visible AI applications in ITSM is chatbots. These AI-driven assistants handle basic service requests, answer FAQs, and even guide users through troubleshooting steps. Instead of waiting in long queues for human support, employees can get instant responses.
Some advanced virtual agents go beyond simple scripts, using Natural Language Processing (NLP) to understand context and intent. This means they can have more meaningful interactions and escalate issues to the right human agent when needed.
When done right, this can be hugely beneficial and cost effective.
But a word of warning; we’ve also seen it done very badly, and unless you have solid Incident and Knowledge practices in place, it can just create more misery to your already frustrated users.
2. Automated Incident Management
AI can significantly reduce the time it takes to detect, categorise, and respond to incidents. Traditional ITSM relies heavily on manual ticket triaging, which is both time-consuming and prone to human error. AI, on the other hand, can analyse incoming incidents, categorise them correctly, and even suggest the best resolution paths based on historical data.
Powerful stuff eh?
Again this does come back to having solid Incident data held in your ITSM platform in the first place, but this kind of automation can certainly help IT teams focus on more complex issues while ensuring end-users experience minimal disruption.
3. Predictive Analytics for Problem Management
As most readers will know, whilst Problem Management is arguably one of the most important and powerful ITIL practices, it’s often the most overlooked, due to resourcing issues. Problem Management isnt hard, it just takes time and energy, and that often doesn’t exist in busy IT teams, or just isnt prioritised.
Now, wouldn’t it be great to prevent IT issues before they happen?
AI-driven predictive analytics can actually make that possible. By analysing historical incident data, system performance logs, and real-time monitoring feeds, AI can identify patterns that indicate potential failures.
For example, if AI detects that a specific server configuration often leads to crashes, it can alert IT teams to fix it before an outage occurs. This proactive approach reduces downtime and keeps business operations running smoothly.
Now without wanting to sound like a broken record here, a precursor to this of course is solid Incident and Knowledge data in the first place. But AI supported proactive Problem Management is probably one of the most obvious and beneficial use cases today, and is definitely worth some prioritised focus if you are starting to embark on an AI journey.
4. Intelligent Change Management
Change Management in ITSM is often a tricky process to balance correctly, whilst balancing a desire to do things faster, but with one wrong move leading to system outages and major disruptions and egg on your face. AI can help assess the impact of proposed changes by analysing previous change requests, their outcomes, and dependencies between IT assets.
Do I need to repeat myself about solid Incident (and now CI) data again, no I probably don’t… but I will anyway – FOUNDATION DATA IS CRITICAL.
But with good foundational practices and solid data across your ITSM platform, and then using AI to simulate different scenarios, AI enables IT teams to make informed decisions about whether to proceed with a change, modify it, or reject it entirely. This potentially vastly reduces risks and improves the overall stability of IT environments.
5. AI-Enhanced Knowledge Management
Ahhhh our old friend, Knowledge Management. Along with Problem Management, arguably one of the most important and often overlooked practices in ITIL.
So can AI can do Knowledge Management for us…ermmm, no (at least not yet).
A well-maintained knowledge base and supporting process, is critical for efficient IT support, but keeping it up to date is of course a challenge. Tools like ServiceNow have all sorts of great functionality to help manage knowledge more effectively, but where AI can really help is by automatically extracting insights from past tickets, documentation, and even chat interactions to help keep on top of it all.
With AI-driven recommendations, IT teams can quickly access relevant solutions, reducing resolution times and improving the overall support experience. Additionally, AI can help identify outdated or redundant knowledge articles and suggest updates (although most ITSM platforms have ways to do this without AI also).
But, again let’s not forget the base data, the Incident Practice and the effort needed to put into Knowledge Management in the first place.
6. IT Asset and License Management
Let’s face it, ITAM and CMDB never quite do what you are told they will when you have your tooling demos. Not because the tools cant do it all, but it’s often not understood how much effort is needed to manage a solid effective CMDB.
Tracking IT assets and software licenses is often an extremely time-consuming, tedious, and error-prone task. AI can streamline this process by automatically identifying underutilised assets, ensuring compliance with licensing agreements, as well as predicting when hardware components are likely to fail.
So by introducing and leveraging AI to help automate asset management, organisations can most likely optimise costs and avoid unnecessary purchases or compliance penalties.
Again, base data is key here of course. But with a combination of a thrust of data cleansing and process / practice oversight, there’s some huge opportunities around AI, ITAM and the CMDB.
7. Service Reporting
No matter how good your ITSM tool is (and dare is say it, your foundational data) those pretty automated bar graphs and pie charts always need some dialogue to go with them.
Now AI can provide that for you without the manual intervention, which can save your ITSM team a great deal of time and effort. Gone are the days for SDMs needing to spend a day or two a month just creating monthly service reports.
How about that long Major Incident Report that the CIO is demanding for that catastrophic Major Incident last week, well, guess what, AI has got your back and is here to help with that too. Yes, your new best pal AI has the power to summarise and simplify all that ticket data and all those MIM calls, into one single easy to consume report. Nice!
Final Thoughts
There’s no question, that AI is starting to revolutionise ITSM.
It’s early days but where applied correctly it’s already making IT teams more efficient, helping to reduce costs, and improving service quality.
While AI won’t replace IT professionals, it will undoubtedly change how they work—allowing them to focus on strategic initiatives rather than repetitive tasks.
As AI capabilities continue to evolve, its role in ITSM will only grow. Organisations that embrace AI now will be better positioned to deliver faster, smarter, and more proactive IT services in the future.
However, we encourage you to get your foundations in place before you pull the trigger and buy all that great new AI tooling functionality, dont buy it if you're not ready for it.
What are your thoughts on AI in ITSM?
Have you seen it in action?
If you need any help with any of the topics in this article, give the ITSM People a shout - hello@itsmpeople.co.uk
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