Finance leaders wary of fair AI pricing, survey finds

SpendHound has published research showing that 57% of finance leaders are not confident they are paying a fair price for AI. The findings come from a survey of 172 finance and procurement executives and spending data from more than 1,300 companies.

The report points to growing unease over AI purchasing as businesses commit more money to tools with evolving pricing models. It found that 19% of respondents believe they are overpaying for AI products, while only 51% said their AI investments are delivering measurable return on investment.

Budget discipline also appears strained. The data shows that 46% of respondents exceeded their AI budget in 2025, compared with 37% for traditional finance and accounting software. That suggests usage-based pricing and rapid adoption are making costs harder to predict.

The findings also highlight governance gaps inside companies. While 81% of respondents expect spending on general-purpose AI to increase in 2026, 22% said there is no single owner of the AI budget, indicating that in some organisations spending is rising without a clearly accountable buyer.

Tom Ruello, Vice President of GTM at SpendHound, said finance teams are being pushed to forecast a category of spending that remains difficult to track.

"Two years ago, most companies didn't have AI spend on their income statements. Today, it's one of their fastest-growing expenses," said Tom Ruello, Vice President of GTM at SpendHound.

"Finance leaders are being asked to forecast that spend, but most teams don't even have visibility into their current spend, let alone their future spend. Add constantly evolving pricing models and fast-changing usage, and teams have no real reference point for what fair pricing looks like," Ruello said.

Vendor pressure

The research also suggests that AI is influencing how businesses review existing software providers. Seventy-six per cent of respondents said they are actively reconsidering current vendor relationships because of AI, while 28% said they are very likely to replace or consolidate finance and accounting tools within the next 12 months for that reason.

Another 48% said they were somewhat likely to make such a change. Better AI-native alternatives were cited by 41% of respondents as a trigger for switching, equal to the share who said tools were too expensive or poor value and close to the 42% who pointed to efforts to consolidate their software stack.

The figures indicate that AI has become a factor in procurement decisions alongside more established concerns such as price and product fit. At the same time, the data suggests AI software is often being added rather than replacing existing systems.

Only 7% of respondents said general-purpose AI had reduced their spending on traditional finance software. By contrast, 62% reported no change and 17% said AI had increased that spending, while 65% said adding AI-native tools was the main reason they expected software bills to rise.

CJ Gustafson, a Technology Chief Financial Officer and Founder of Mostly Metrics, said the numbers matched what he had been hearing from finance teams.

"Everyone said AI would simplify the tech stack. Fewer tools, leaner bills, cleaner workflows. That is not exactly what is happening yet," said CJ Gustafson, Technology Chief Financial Officer and Founder of Mostly Metrics.

"Teams are adding AI tools faster than they are removing existing software, and governance is running about six months behind experimentation. In SpendHound's AI Spend Report, I finally see some hard numbers to support the stories I keep hearing," Gustafson said.

Pricing opacity

The report argues that a lack of pricing reference points is a central problem for buyers. Unlike more mature software categories, AI contracts can vary widely, and usage levels may be difficult to estimate in advance. That leaves finance leaders with limited benchmarks when negotiating renewals or new purchases.

Its findings are backed by transaction data drawn from anonymised business software purchases across mid-market and enterprise groups. The respondent base included Chief Financial Officers, Finance Directors, Controllers, FP&A leaders and procurement executives across sectors including software, healthcare, manufacturing and financial services.

SpendHound is positioning its own product around that problem, offering benchmarking data and a module designed to track AI usage and costs across providers including OpenAI, Anthropic, Cursor and Amazon Bedrock. Customers named by the company include ZoomInfo, SoFi, Datavant and Clear.

Rebecca Martins, Vice President of Marketing at SpendHound, said visibility into live usage and peer pricing was becoming more important as companies tried to control costs.

"The teams managing AI spend well aren't the ones with the biggest budgets. They're the ones who know what they're spending in real time and what their peers pay for the same tools," said Rebecca Martins, Vice President of Marketing at SpendHound.

"You can't negotiate a price you can't see, and you can't consolidate a stack you've never fully inventoried. That's why we built AI Spend Visibility: to give finance teams a clear view of usage and token spend before the invoice arrives. Pair that visibility with our real pricing benchmarks at renewal, and teams can actually control what they spend," Martins said.