Forrester warns AI-driven price hikes and usage-based billing will inflate software budgets in 2027

A Forrester survey of more than 2,600 business and technology decision-makers found that 80% expect data and software budgets to rise in 2027 as AI adoption accelerates. The research firm attributes the increases to vendors passing infrastructure costs to customers through price hikes and usage-based billing models.

In the last six months, Anthropic, OpenAI, GitHub, and Microsoft have moved services away from flat-rate subscriptions toward usage-based pricing. Anthropic, OpenAI, and GitHub were specifically cited for adopting token- or usage-driven billing, while Microsoft was noted for its premium E7 license that bundles M365 Copilot, Agent 365, and security tools onto the E5 tier.

Forrester’s chief research officer, Sharyn Leaver, emphasized that organizations outperforming in 2027 will focus on foundational investments—such as trusted data, governance, and organizational readiness—rather than simply spending more on AI. Leaver stated, 'The organizations that outperform in 2027 won’t be those that spend the most on AI. They’ll be the ones that invest in the foundations that make AI effective.'

Personnel costs remain a persistent driver of IT budgets, with staffing accounting for 35% of IT budgets in 2025. For 2027, 67% of tech decision-makers expect staffing budgets to increase, while 68% of data technology decision-makers anticipate higher spending on data/analytics-specific roles. Forrester cautioned against overreliance on AI to replace employees, noting that 'AI washing' of layoffs continues amid financial and restructuring pressures.

Forrester recommended that organizations adapt their Financial Operations (FinOps) practices to manage the unpredictable costs associated with AI. The firm advised implementing runtime cost controls such as model routing, semantic caching, and usage guardrails to prevent runaway spending. Traditional FinOps frameworks were not designed for token-based, usage-driven AI costs, but Forrester argued that FinOps teams are best positioned to develop these new capabilities.

The findings align with broader concerns about cost management in AI adoption. In July, KPMG research found that nearly a third of corporate leaders reported difficulty understanding and controlling operating costs when implementing business AI at scale. KPMG noted that as usage-based pricing becomes more common, organizations are still building the capabilities required to forecast, monitor, and manage AI spending effectively.