- Forrester analysts warn about four in five managers and ITDMs envision larger budgets by 2027
- Consumption-based AI pricing makes it harder to predict spending
- Targeted investment to improve data quality is key
Forrester predicts that software budgets could be set to increase, with more than four in five executives expecting to increase overall budgets over the next 12 months and 82% of technology decision makers expecting bigger budgets.
While some of the extra money may come as a result of increased confidence and willingness to spend on technology, the company’s analysts warn that a shift in pricing structures could also force companies to pay more.
This comes as software vendors shift from traditional per-seat licenses to token or credit pricing, which introduces so many more variables, including model selection, context size, output length, and agent runtime, leading to far more unpredictable outputs.
The real reason businesses are gearing up to spend more on software
“Business leaders are no longer planning for a return to stability – they are planning for a future where volatility is constant,” noted Chief Research Officer Sharyn Leaver.
Recent moves by major AI providers all point to this new pricing model becoming the norm, with GitHub moving its Copilot facilities to usage-based billing in June and OpenAI adding pay-as-you-go Codex seats in April. Anthropic also recently removed the Fable 5 from its standard subscription and seat-based models due to difficult-to-predict demand, but laid out plans to reintroduce it where capacity allows.
Recognizing these major shifts, Forrester’s report reveals two areas where companies can increase their budgets for 2027 – building machine-readable context and enterprise knowledge and increasing brand visibility in response engines.
The report also suggests the major role AI can play in marketing and customer-facing experiences, and the potential use synthetic data can provide subject to testing. All in all, it’s more about targeting investment rather than throwing money at the problem, as Leaver concludes:
“The organizations that do better 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 effective.”
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