The rapid evolution of artificial intelligence (AI) capabilities and increasing end-user expectations mean your corporate IT support and wider IT service management (ITSM) capabilities must transform. Not only is more possible with AI, but your employees or end-users now expect more from their corporate IT services, too.
This article explores why your IT support capabilities must evolve and how organizations can leverage AI, including generative AI (GenAI) and Agentic AI, to improve their IT service desk operations and outcomes.
“Start with the ‘why’”
Just because new GenAI-powered and Agentic AI capabilities are available in your ITSM tool isn’t the “why.” It’s great that they are available (GenAI and Agentic AI capabilities are available in Provance ServiceTeam ITSM 3.0), and we’ll return to them later. Instead, the real “why” for changing your IT support capabilities is the higher expectations of your end-users. The various AI capabilities are a “means to an end” rather than the “end” itself.
Your employees are increasingly demanding and expecting more from their corporate IT services, including IT support. Their consumer-world service and support experiences continue to raise the bar for your corporate IT organization (although not always; I think most of us have experienced badly designed chatbots). One aspect of this is employee experience, with experience data and insights able to identify IT service delivery and support issues and to prioritize related improvements based on what matters most to your end-users.
In terms of improving, it’s important to understand your end-users’ expectations and where, in particular, your IT organization is failing to meet them (despite consistently meeting your traditional IT metric targets). Financial restrictions might limit the opportunity to improve. For example, doubling the number of IT service desk agents just isn’t going to happen. However, the available AI-enabled capabilities will help your IT service desk to deliver against these higher expectations, especially in terms of replacing slow and costly manual activities with superior automated capabilities.
The commonly provided AI IT support capabilities
One of the most important things to remember when considering the AI capabilities available in your ITSM tool is perspective.
This approach can be employed twice. First, when looking at “the art of the AI possible.” There’s the AI perspective, i.e. what the technology can do, versus the ITSM process or capability perspective, i.e. the AI use cases in the context of what your IT service desk does. For example, incident management and service request management.
Second, there’s the end-user perspective. It’s likely that an average end-user won’t care if your IT service desk has added AI-enabled capabilities to its incident management process say. Instead, they’ll likely only be interested in whether you’re making them productive again more quickly. Perhaps thanks to immediate engagement and delivering an extremely quick fix to their issue.
Returning to the “start with the ‘why’” point, this end-user perspective should guide your IT service desk’s prioritization, adoption, and use of AI-enabled ITSM capabilities. Ultimately, leveraging AI to improve “what matters most” to end-users.
Resolving end-user issues as an example of AI IT support
This isn’t “enabling incident management” because that would be the IT service desk’s view of the opportunity to employ AI-enabled capabilities (and it might limit the scope, perhaps to the mechanics of ticket handling).
This can be viewed as three “umbrella” use case scenarios where:
- Service desk operations are optimized using AI capabilities
- Service desk agents are empowered through AI capabilities
- End-users can efficiently self-help using AI capabilities.
This is just one of the possible ways to divide up the many opportunities for your IT service desk team to benefit from AI-enabled capabilities. The important point is to make it easier for everyone to understand how different AI technologies can benefit IT operations and end-user outcomes. Each of these “umbrella” use case scenarios is examined below.
How IT service desk operations are optimized using AI capabilities
One of the early ITSM AI adoption use cases is still popular – intelligent ticket triage. In this case, the AI analyzes incoming incident tickets and automatically categorizes, prioritizes, and routes them based on context and historical patterns. When possible, the AI can also automatically resolve the end-user issue as per the next point. This AI-enabled capability reduces the manual effort (and cost) required for what is a high-volume IT service desk task, but it also speeds up ticket handling (especially when automated resolutions are applied) and provides better end-user experiences (with lower productivity losses).
The automated resolution of tickets is tied in with intelligent ticket triage, but it can also be employed in other use-case scenarios. For example, a service desk agent can invoke a “one-click” resolution as part of their incident handling. Or an end-user can be offered the automated resolution via the self-help route. This could be a password reset, printer issue resolution, or another repeatable incident resolution task that can be delivered through back-end automation.
AI also offers predictive analytics capabilities. While this can be used for administrative tasks such as forecasting service desk staffing schedules, there’s a particular use case in resolving end-user issues. This is forecasting potential issues (such as device failures or application outages) based on diagnostic and historical ticket data. This AI capability allows the IT service desk, or whichever IT team is responsible, to proactively take actions to prevent an issue affecting one or more end-users before they are impacted.
How service desk agents are empowered through AI capabilities
The AI empowerment of service desk agents could be considered “service desk operations optimization.” However, there’s a nice synergy between the available service desk agent AI capabilities and those available for self-help improvement, and treating them separately is beneficial.
Your service desk agents can receive AI-suggested next-best actions or known solutions in real-time while handling tickets. This assistance is drawn from knowledge bases, other available documentation, and past ticket contents. This allows your agents to handle more ticket types (or issue types), reduce the resolution time, and improve the consistency of IT support across agents. It’s particularly helpful for new service desk agents who are still “learning the ropes.”
AI capabilities can also provide agents with important information, such as device diagnostics, to help with issue resolution. Or specific details such as this being the third time an end-user has had the same issue with their device, facilitating an alternative course of action such as device replacement. This additional insight doesn’t need to be technology-related. For example, AI can analyze the tone used in ticket submissions or chat conversations to identify frustrated end-users or serious scenarios, such that tickets can be escalated or a different approach can be taken when needed.
How end-users can efficiently self-help using AI capabilities
The primary capability available to end-users is AI-powered chatbots (often called “virtual agents”). These provide 24/7 support, offering helpful information and guiding end-users through troubleshooting steps (with automated resolution capabilities invoked when possible). This capability overlaps with the first two “umbrella” scenarios, optimizing IT support operations by reducing the volume of tickets that need to be handled by service desk agents. It also delivers a better service experience for end-users wishing to quickly self-help rather than enter the people-based service desk process.
However, the AI assistance doesn’t need to be limited to the chatbot use case. Natural language search can be employed in knowledge bases, interpreting end-user intent and language to make it easier to find relevant solutions without the right keywords. Or AI capabilities can be embedded into commonly used applications to provide real-time, context-aware help based on what the end-user is doing.
Finally, self-help assistance can be personalized, with the AI leveraging factors such as the end-user’s role, location, and behavior, device performance, and ticket history to proactively provide help.
These three “umbrella” use case scenarios aren’t exhaustive, but they offer the opportunity to see what’s involved from an outcome-oriented perspective. Importantly, they show how different AI capabilities are needed to deliver against a particular IT support need. For example, delivering a portfolio of AI capabilities to better enable your service desk agents will likely provide more business value than applying a single AI capability to produce a partial solution across multiple use cases.
What would you add to this view of IT support and AI? Please let me know in the comments.
Roger Labelle
With over 15 years at Provance as the Director of Product and Development, Roger Labelle has extensive expertise in ITSM and ITAM. Recently, Roger has been harnessing Microsoft AI technologies to transform ServiceTeam ITSM and ITAM, Provance’s flagship products, which will enhance customer and agent satisfaction. Roger is dedicated to balancing core ITSM functionalities with innovative AI solutions, ultimately reducing the total cost of ownership for customers.
