AI is clearly on the road to becoming the backbone of ITSM. CIOs are consistently reporting higher-than-expected success with AI projects, even outperforming other tech rollouts. This C-suite optimism is backed by our latest State of AI in IT 2025 report built in collaboration with ITSM.tools and PeopleCert, where 47% expressed greater trust in AI more than they did a year ago — a powerful sign of shifting attitudes.
But not everyone is sold. A lot of organizations are still wary of trusting agentic AI for their ITSM transformation, which only creates a vicious cycle of underwhelming results. The pattern also emerged out loud in our survey of 700+ end-users and 300+ IT professionals: Without enough trust, investments stay small, and AI’s true potential is never realized, resulting in lackluster ROI that just fuels their doubts.
So, what makes the difference between the AI leaders and those falling behind? How can they prove the real ITSM returns from AI? The answer lies in building a solid AI ROI framework that tracks everything from operational gains to long-term growth.
The case for building an AI ROI framework
Microsoft-backed research shows AI investments can yield up to 3.5X returns, with a lucky 5% of businesses seeing 8X. While that sounds impressive, it’s easy to get swept up in those numbers. The truth is, to measure AI’s ROI accurately, we need to look past the immediate financial impact, and even our own anecdotal evidence and feel-good stories.
An AI ROI Framework solves this problem by giving IT the tools to measure AI success through both immediate and accumulated benefits. It provides objective data to compare pre-AI vs post-AI company performance and helps identify areas where AI investments deliver the most value, or where they might not be worth the effort.
We present five actionable ways to evaluate AI’s impact on your ITSM to guide the process.
1. Productivity gains
Productivity gains in terms of people and process efficiency offer one of the most tangible and data-driven ways to view the ROI of AI investments. In a company with 5,000+ employees, the IT team could reclaim 2,500 hours and $55,000 annually that would otherwise be tied up in outdated, manual access provisioning. But that’s just the beginning—employees waste another 10,000 hours annually chasing approvals, tracking down multiple department heads for permissions, and dealing with slow IT response times.
AI eliminates all that hassle by automating the entire process. It speeds up approvals, automatically adds users, sends notifications through Microsoft Teams/Slack, and grants instant access with automated reminders to managers and security teams.
This way, you will be able to track AI’s ROI through time saved per resolved ticket, improved first-time accuracy, reduced approval chain delays, and resources redirected to strategic initiatives that boost productivity and make employees’ lives a lot easier.
2. Faster ticket deflection
Ticket deflection refers to resolving issues through self-service or AI agents with a few simple clicks. The better your deflection rate, the fewer tickets your IT team has to manage, and the faster IT can reduce operational bottlenecks, service costs, and unproductive work that ties support teams. This is crucial for ROI because each ticket costs anywhere from $15 to $37, while self-service options drop that cost to just $2 per ticket.
With AI assistants tapping into knowledge bases, users can solve common problems on their own, driving up ticket deflection rates. For instance, US-based safety gloves distributor Ammex Corp, implemented AI-driven knowledge management to improve their deflection rate from 20% to 65%.
Chad Ghosn, Ammex’s CTO, is all in on the ROI, saying, “Atomicwork allowed us to maintain our IT service team without adding a single headcount in six months. AI handles simple queries that used to disrupt our Finance team, and it gives our CEO real-time updates on orders and shipments—without needing a phone call or email to slow anyone down.”
3. Employee experience (EX) and satisfaction
Whether it’s 3 a.m. or peak office hours, AI instantly acknowledges support requests and delivers smarter, faster fixes every time. A smooth, hassle-free experience like this is a powerful ROI driver, as it minimizes downtime and empowers employees to stay focused on getting their work done without jumping through the approval chains.
For instance, let’s say a team faces printer-related issues. AI’s intelligent automation pulls up the model, verifies warranties, and offers a one-click resolution, all while keeping the employee updated in real-time, without humans in the loop.
When employees don’t have to chase IT for fixes or approvals, they can get back to doing what they’re great at—driving value, innovating, and making an impact. AI cuts out the bottlenecks and lets them focus on meaningful work that boosts their morale, ignites creativity, and even accelerates digital dexterity across the enterprise.
4. Operational cost optimization
It’s no secret that operational cost savings are one of the most significant ways AI drives ROI. In fact, 61% of professionals in our above-mentioned survey said they’re seeing these kinds of savings. That’s no small feat, especially when you consider that simple operational IT tasks like password resets can cost up to $85,000 annually.
AI slashes password reset costs by automating employee identity verification and handling the reset through Active Directory. What used to take 15-20 minutes now happens in under 2 minutes, all while keeping security protocols intact.
Since password resets often account for 30% of IT service desk tickets, AI can cut down on tickets charged by third-party vendors, and bring the cost down to just a few dollars per automated reset.
5. Headcount optimization
As your business grows and the volume of IT tickets rises, AI can scale to meet that demand without you having to increase your workforce. Just look at Ammex—they saw their ticket volume soar over six months using Atom but didn’t need to bring in extra IT staff.
With an AI-driven service management platform, you can handle tickets across multiple categories simultaneously and sort them based on urgency, priority, and content. It also routes tickets to the right agents based on skill, experience, and current workload, predicts future demand, and even eliminates duplicates so your IT team can stay focused on high-priority, complex issues like server outages or critical updates. This means you can grow without the costly hiring spree.
Bottom line: Trust as a multiplier for ROI
This trust in AI systems is a key factor in driving AI ROI, as Stephen Mann, Principal Analyst at ITSM.tools, points out. High trust in AI initiatives translates into companies putting more money and effort into AI adoption, training, or integration.
The payoff? Improved employee experience, hyper (and intelligent) automation, and sustainable revenue growth. “It’s like a chain reaction—AI investment leads to success, which builds trust, and other times, trust leads to more investment, which sparks success”, remarks Stephen.
But for this loop to work, trust must start at the top and later percolate to IT teams. In our research, companies where the C-suite backs AI but lets IT drive its execution see significantly higher returns.
But leadership alone won’t cut it—the buy-in must be strong and visible across the organization. Case in point: 94% of companies with negative ROI had invested less than 10% of their IT budget in AI initiatives. On the flip side, a solid budget commitment directly impacts ROI.
When trust aligns with leadership support and budget allocation, it creates a compounding effect. Teams embrace AI, initiatives scale, and outcomes speak for themselves. To build that trust, don’t wait for the perfect moment. Just start. Begin by giving your AI workflows full visibility, pulling data from all angles, and tracking productivity and cost savings, ticket deflection, and employee impact.
If you’re not seeing the ROI you expected, ask yourself: Is trust missing from the equation, or are you measuring the wrong “ROI” metrics?