Many IT leaders still struggle to find ROI when deploying AI agents at scale, but a few IT sweet spots are emerging as use cases that can provide CIOs tangible cost relief.
Rhonda Baldwin, CIO at LaunchDarkly, says coding agents and service desk agents are helping the SaaS provider cut IT costs.
“Coding agents increase engineering capacity without requiring a proportional increase in headcount,” she says. “They also help us optimize cloud costs and reduce workflow consumption costs.”
In addition to coding and cloud cost optimization, IT leaders see tier 1 and 2 IT support as another promising area for agents to free up IT budget, although many have just begun to track savings from AI agents, and those that do use several different metrics.
For Baldwin that includes cost avoidance, as coding agents have helped the company build internal tools rather than buying additional software, she notes.
Here, the savings have been substantial, she says, with the company foregoing about $1 million in spending on two optimization projects and another $120,000 by building its own enterprise asset-management solution with AI coding tools.
In addition, LaunchDarkly has saved about $50,000 in annualized savings by using agentic AI for tier 1 IT support. “This not only boosts employee productivity but also helps us avoid costs related to software, implementation, asset management, and having remote service technicians,” she says.
IT support and self-service resolution
IT support is a strong use case for IT leaders looking for agent cost savings, says Gil Pekelman, CEO of AI agent provider Atera, whose company recently released a joint study with Forrester claiming significant ROI for its IT incident support agent.
“The calculation is very straightforward,” he notes. “We have a company that has 10,000 employees, and all IT support is offshored. If they’re going to close that down now, they can immediately measure the savings there.”
Kevin Rooney, CIO at West Monroe Partners, reports significant savings for the digital consultancy through just such a deployment.
Now, employees can an internal IT and HR support agent in Teams or Slack to get answers to common questions, request software access, reset passwords, unlock accounts, submit and update tickets, or connect with a live support professional when needed, he says.
“By handling high-volume, repeatable requests and improving ticket intake and routing, it helps our IT team spend more time on complex issues and higher-value work,” Rooney adds.
West Monroe is evaluating the impact of the agent in terms of self-service resolution, ticket volume, response time, and capacity savings, but it has driven a 40% reduction in yearly managed service provider costs, he says. The bot has also led to an estimated operational time savings of 2,700 hours per year, he adds.
Cost savings in the cloud
Matthew Wallace, co-founder and CTO of KamiwazaAI, has also found major IT savings from agentic AI. The Ai orchestration platform provider uses agents in several areas, including software engineering, project management, data science, and systems engineering.
Cloud optimization is another area where the company is saving money by using agents, he adds.
“We have a set of agents that monitor new systems in the cloud, coordinate with those turning them up, and coordinate budget approvals, with an easy way to shut down unauthorized spend and log it,” he says.
That agentic system has replaced a function that required a high amount of human coordination and attention, he notes
“You have to check and understand who set it up, when, what the cost is, whether it has internal approval, and various details about resource sizing, placement, etc.,” he explains. “Later, you have to check whether someone has responded with information and whether anyone in management has offered an approval or rejection.”
The first round of cloud optimization agents that Wallace’s team deployed cut cloud spending by 70% immediately, he says.
Check the numbers
However, Jeet Pattanaik, founder and CTO of AI-base solutions provider Glokal AI, says some organizations are inflating their IT savings from agentic AI because they’re not measuring all the costs.
While he believes some IT leaders are finding real savings, they’re often smaller and slower than advertised, he says, noting that in reality most organizations are still hunting for ROI.
“The pilot always looks great because it runs on the easy tickets,” Pattanaik says. “Then, production brings in all the odd cases, and somebody has to check what the agent actually did. That checking is what quietly eats the savings, and it almost never shows up in the business case.”
He sees tier 1 support — password resets, access requests, answering questions already in the documentation — as the place where organizations are saving IT budget using agents.
“The sweet spot is work that’s high volume, well documented, and cheap to undo if the agent gets it wrong,” he says. “Tier 1 fits that nicely. Tier 2 only partly. Anything that changes someone’s permissions or touches production systems isn’t ready yet, because one bad action there can cost more than a thousand good ones save.”
IT leaders deploying agents for IT support should keep an eye on how often tickets get reopened, Pattanaik adds. “A ticket the agent closed isn’t always a problem solved,” he says. “If people keep coming back with the same issue, you didn’t save anything, you just pushed it down the road.”
He gives this example: A service desk handles 10,000 tier-1 tickets a month at about €15 each. The agent closes 40% of them, which, on paper, saves €60,000 a month. But if 15% of those come back reopened, that’s €9,000 of work returning to humans. Add around €15,000 for people checking what the agent did, and the real cost reduction is closer to €36,000, about 60% of what the pilot promised.
There’s also a cost to eliminating workers focused on tier 1 support, he adds. “One cost nobody seems to count: Tier 1 is where people learn the job,” he says. “Automate all of it, and you lose the path that turns juniors into your future senior engineers.”