CEOs, their boards, and the rest of the C-suite continue to push AI as a strategic imperative.
As a result, IT’s investments in AI are up, with the percentage of the IT budget earmarked for AI projects nearly tripling from last year, according to the 2025 CIO Playbook from Lenovo and research firm IDC.
But while research also shows that most IT budgets are higher this year than in 2024, CIOs say those increases aren’t enough to cover all the tech-enabled initiatives their organizations have identified.
Moreover, they’re reporting that the executive drive for all things AI has them recalibrating their IT project agenda, prioritizing AI spending while bumping other items down or even off the to-do list.
“Budgets are finite, and because AI investments are an imperative for CEOs, the boards, and CIOs to support the business functions, AI shrinks the dollars available for other initiatives and so the line on priorities is being drawn differently,” says Dhaval Moogimane, who leads the high-tech and software practice at West Monroe, a business and technology consulting firm. “This is going to force a level of discussions in organizations not only about how they prioritize but how they manage their spend.”
What IT projects are losing out
Recalibration of budgets to accommodate newly prioritized projects — as is the case for AI pilots, proofs of concepts, and full-on implementations — is not an entirely new phenomenon.
“CIOs in general always have too many priorities, so there are always projects that are delayed,” says Marco Bill, senior vice president and CIO at Red Hat.
Still, significant pressure to “do AI” — as some have phrased the command CIOs have heard from the C-suite — is forcing some errors in IT budget allocation, IT consultants, researchers, and CIOs observe.
“There’s still a little too much ‘just do something with AI’ that is producing too much pressure versus well-informed, thoughtful strategic decision-making,” says Mike Mason, chief AI officer at Thoughtworks, which provides software design and delivery, as well as consulting services.
As a result, some CIOs have seen work that should be prioritized get pushed aside, Mason says. For example, he adds, some organizations have paused experiments on other emerging technologies to focus entirely on AI.
Fabien Cros, chief data and AI officer at global consulting firm Ducker Carlisle who also advises clients through the firm’s SparkWise Solutions, has observed other organizations pushing off transformation efforts in favor of AI experimentation.
Others have deprioritized addressing technical debt as well as modernizing legacy systems and architecture, says Sumeet Gupta, senior managing director and leader of the digital transformation and AI transformation teams at FTI Consulting.
“Often it’s this kind of longer-term investment that’s getting pushed off, and that can be to their determinant,” Gupta adds.
A calculation of risk and opportunity
Some of these recalibrations could come with significant consequences for CIOs and their organizations.
Consider, for example, how removing funds from innovations on tech other than AI could leave IT departments behind the curve when other emerging technologies move toward the mainstream.
“AI is a great example of not waiting to see, that you need to get into it, and start experimenting early or be left behind,” Mason says, noting that organizations that skimped on funding experiments in AI’s early days found themselves playing catch-up later.
Likewise, ignoring modernization efforts while chasing AI-enabled opportunities could put the organization at a disadvantage down the road, as legacy tech will likely stall IT’s ability to capitalize quickly on future AI opportunities, Gupta says. That could mean significant losses if the company’s competitors are able to speed ahead with their AI use at critical moments.
Ducker Carlisle’s Cros has a similar take, noting that some organizations want to go at full tilt on AI but balk at spending money on transforming the IT or data architecture — both of which are essential for advancing AI ambitions but where ROI can be harder to articulate.
“Many companies are trying to leapfrog, and there’s no way they can leapfrog. So what they’re doing is just putting everything on hold,” he says. “They need to move forward, and they’re just keeping everyone hostage on this old technology. They’ll reach a point that it will be so expensive to do a transformation, and the step [to advance] will be so huge.”
Cros is not alone in that assessment. The 2025 Great Data Divide study from digital services company Softserve found that 73% of tech leaders believe their company has allocated funds or talent to the latest generative AI trends at the expense of more valuable data and analytics initiatives.
Even in such cases, though, West Monroe’s Moogimane says CIOs and their executive colleagues often do so with awareness of the risks and tradeoffs.
“They’ll accept that there is some risk in deferring a needed investment now for a potential problem in the future,” he says.
Indeed, Cros and others say forgoing some items — including certain transformation and modernization efforts — to seize on AI can sometimes be the smarter move to make.
For example, CIOs who go for small AI wins can modernize components of their tech stack in pursuit of significant returns that could in turn create enough margins to get buy-in for funding modernization efforts whose ROIs take longer to recoup.
Still, Moogimane cautions against being cavalier in such calculations, particularly if they involve pushing off IT projects that will support future AI initiatives.
“With AI, there is a big data investment required, and sometimes it’s hard to justify spending on data initiatives,” he explains. “But as companies think about spending on AI initiatives, they have to make sure they’re making the investments in data. Initiatives like data cleanup, tech debt remediation, or some infrastructure updates historically have had more challenges getting funded because they’re harder to quantify. But they’re foundational and need to get done.”
Governance more critical than ever
As the exuberance around AI settles, CIOs and their advisers say enterprise leaders are now rushing less into AI initiatives at the expense of other needs. They’re putting more reliance into their portfolio management skills to make investments (AI related or not) that align with business goals.
“Through the end of 2024 we were seeing a lot of people in a reactive mode, doing AI and pushing off other important things, but I think companies are now getting smarter and trying to do more prioritization,” Gupta says.
He stresses the need for CIOs and the rest of the C-suite to prioritize problems to be solved rather than focus on the technology they need.
Even so, CIOs, researchers, and consultants say AI-enabled projects still have an easier time reaching the top of the priority list, whereas more conventional IT work has a harder time earning the go-ahead.
“The bar for AI projects [to get approved] is lower, and I don’t think that’s unwarranted, given where we are. As a result, there is going to be some waste, like there is with any other early-stage technology adoption,” Moogimane says.
On the other hand, business projects that leverage more conventional technologies face more rigorous scrutiny to ensure they’ll deliver ROI big enough to justify the work.
“AI has pushed off the nice-to-haves. AI has increased the need to really pick and choose the projects IT needs to do. It is certainly improving the need to be thoughtful and justify every project,” Thoughtworks’ Mason says.
CIOs, too, acknowledge that the hype around AI can pull attention toward the technology itself rather than business needs. Those who have successfully resisted that pull credit strong governance.
“I get asked a lot about AI from the leadership team and the board, but there isn’t a push to do AI at any expense,” says Kathy Kay, CIO at Principal Financial Group.
Rather, she and the executives center on the strategic objectives they’ve set and what will get them to those targets. She says the team believes AI is only one of “the enabling technologies that will help get efficiencies for us and drive growth.”
Kay acknowledges that her IT department has been prioritizing AI initiatives but it is doing so because it’s the best technology to solve the problem at hand and deliver the best ROI.
She also says her IT team continues to tackle other prioritized projects that don’t involve AI, noting that she can’t think of any in-flight IT initiatives that were grounded to shift resources to AI projects.
“We’re aligned on the highest priorities and initiatives that will help move our company forward. It helps sort out which shiny objects will move us forward and which ones won’t,” Kay adds. “That allows us to have the right conversation around AI.”
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