Experts warn software budgets could rise as AI bills rise

Forrester analysts warn about four in five executives and IT leaders plan to have bigger budgets in 2027.
Consumption-based AI pricing makes it harder to predict spending
Targeted investments to improve data quality are essential

Forrester predicts that software budgets could increase, with more than four in five executives expecting an increase in overall budgets over the next 12 months and 82% of technology decision-makers expecting larger budgets.

While some of the extra cash could result from increased confidence and willingness to spend on technology, the company’s analysts warn that a change in pricing structures could also force companies to shell out more.

This comes as software companies move away from traditional per-seat licensing in favor of per-token or per-credit pricing, which introduces many more variables, including model selection, context size, release duration, and agent uptime, leading to much more unpredictable spend.

The Real Reason Businesses Are Preparing to Spend More on Software

“Business leaders no longer anticipate a return to stability, but a future where volatility is a constant,” noted research director Sharyn Leaver.

Recent changes from major AI vendors indicate that this emerging pricing model is becoming the norm, with GitHub moving its Copilot factories to usage-based billing in June and OpenAI adding pay-as-you-go Codex seats in April. Anthropic also recently removed Fable 5 from its standard subscription and seat-based models due to difficult-to-predict demand, but plans to reintroduce it where capacity allows.

Recognizing these major changes, Forrester’s report reveals two areas where companies can increase their budgets for 2027: developing machine-readable business context and insights, and increasing brand visibility in response engines.

The report also hints at the major role that AI can play in marketing and customer experiences, as well as the potential use that synthetic data can provide subject to testing. Overall, it’s more about targeting investments rather than pouring money into solving the problem, as Leaver concludes:

“The organizations that outperform in 2027 will not be the ones that spend the most on AI. They will be the ones that invest in the foundations that make AI work.”

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