68% of tech leaders plan AI budget hikes; 39% see AI as top growth driver
The newest Apptio poll hints that bigger AI wallets are becoming the norm: 68 % of tech leaders say they’ll lift their AI budgets, and 39 % point to AI as the main engine for future department growth. But more cash doesn’t automatically mean better outcomes. Executives seem eager to pour money into machine-learning projects, yet the same data hints at a gap between what’s spent and what’s delivered.
Gartner® throws another twist into the mix, noting “despite an average spend of $1.9” - a fragment that suggests even hefty investments might fall short of expectations. It’s unclear whether those dollars are reaching the right use-cases or simply inflating balance sheets. Companies are betting heavily on AI, but the link between cost and result stays fuzzy.
For CIOs, that mix of optimism and opacity raises a tough question: can they keep expanding AI spend without a clearer picture of the financial payoff? My sense is the answer will depend less on the size of the budget and more on how well the spend is tracked and reported.
According to Apptio research, 68% of technology leaders surveyed expect to increase their AI budgets, and 39% believe AI will be their departments’ biggest driver of future budget growth. But bigger budgets don’t guarantee better outcomes. Gartner® also reveals that “despite an average spend of $1.9 million on GenAI initiatives in 2024, fewer than 30% of AI leaders say their CEOs are satisfied with the return on investment.” If there’s no clear link between cost and outcome, organizations risk scaling investments without scaling the value they’re meant to create.
To move forward with well-founded confidence, business leaders in finance, IT, and tech must collaborate to gain visibility into AI’s financial blind spot. The hidden financial risks of AI The runaway costs of AI can give IT leaders flashbacks to the early days of public cloud. When it’s easy for DevOps teams and business units to procure their own resources on an OpEx basis, costs and inefficiencies can quickly spiral.
In fact, AI projects are avid consumers of cloud infrastructure — while incurring additional costs for data platforms and engineering resources.
Will the bigger spend actually turn into real gains? The numbers show a lot of optimism: 68 % of technology leaders say they’ll raise AI budgets, and 39 % see AI as the main driver of future growth. Still, the article points out that hype can outpace fiscal discipline, especially when AI projects can swell in cost fast.
Companies are touting operational efficiency, higher worker productivity and better customer satisfaction as early wins, but without clear cost visibility those wins might fade. Gartner’s data, an average spend of $1.9, reminds us that even big tickets don’t guarantee the returns people expect. Apptio’s push for cost transparency suggests disciplined budgeting could be the missing link between ambition and outcome.
It’s unclear whether firms will tighten controls or keep chasing headline-level budget bumps. I think the tug of war between ambition and accountability will shape AI’s long-term impact on the bottom line. Stakeholders will have to watch spend against real performance metrics, making sure each dollar moves the needle rather than just feeding speculative projects.
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Common Questions Answered
What percentage of technology leaders plan to increase their AI budgets according to the Apptio survey?
According to the Apptio survey, 68% of technology leaders expect to increase their AI budgets. This finding highlights a strong trend of growing financial investment in artificial intelligence initiatives across departments.
What does the article identify as the potential disconnect between AI spending and performance?
The article points out that while 68% of leaders plan budget hikes, Gartner research indicates that despite an average spend of $1.9 million on GenAI, fewer than 30% of AI leaders report CEO satisfaction with the return on investment. This suggests that increased spending does not automatically guarantee better outcomes or performance.
What are the emerging benefits of AI projects mentioned in the article?
The article cites operational efficiency, worker productivity, and customer satisfaction as the key emerging benefits from AI initiatives. However, it also warns that without clear cost visibility, sustaining these gains can be challenging.
Why does the article caution that enthusiasm for AI can outpace fiscal discipline?
The article cautions that the high enthusiasm, with 39% of leaders viewing AI as the top growth driver, can lead to a situation where spending increases without a clear link to outcomes. This is compounded by the fact that the costs of AI projects can balloon quickly, making fiscal discipline essential.