Forrester warns bigger AI budgets won't fix weak ops

Forrester has published its 2027 budget planning guides for technology and security leaders, pointing to rising spending plans while warning that bigger AI budgets alone will not fix operational weaknesses.

The research shows broad confidence among decision-makers after a more cautious period. It found that 82% of technology decision-makers expect budgets to rise over the next 12 months, while 60% of security technology decision-makers expect security budgets to increase by 5% or more.

Within security, spending expectations vary. Some 16% of security leaders expect increases of more than 10%, while 44% anticipate growth of between 5% and 10%.

Forrester based the guides on a global survey of more than 2,600 business and technology decision-makers across industries and functions. The results, it said, reflect a broader shift from AI experimentation to larger deployments, exposing gaps in data quality, governance, and operating models.

That tension sits at the centre of the new guidance. While boards and executives appear more willing to fund technology and security projects, the research argues that spending more on AI without fixing underlying systems and processes risks adding to fragmented data, duplicated work, and technical debt.

Spending pressure

Cloud infrastructure and data rank among the fastest-growing areas of technology investment in the survey. In cybersecurity, software remains the largest spending category, while labour costs continue to rise as organisations contend with platform sprawl and demand for AI-related skills.

These pressures suggest that even with larger budgets, technology leaders may face tighter trade-offs than the headline figures imply. New forms of spending are emerging as companies also try to prove returns from AI initiatives.

One clear example is what Forrester described as a new security budget line item: token economics. The term refers to the cost structures attached to AI model usage, and those expenses could offset some of the efficiency gains companies expect from AI adoption.

The guidance also points to a growing list of priorities for security and risk teams. These include post-quantum preparedness and security frameworks designed for agentic AI systems, reflecting concern that the next stage of AI deployment will create new attack surfaces and governance demands.

Where to invest

For technology leaders, the recommendations focus less on broad expansion and more on selective groundwork. The research calls for investment in AI-ready enterprise knowledge, stronger governance, better orchestration, and targeted work on data quality and accessibility.

At the same time, it advises organisations to scale back projects without clear ownership, governance, or a path to scale. That includes AI pilots that increase activity but do not demonstrate organisational readiness.

For companies trying to reduce technical debt, the message is similar. Rather than cutting all clean-up work, the research suggests focusing spending on specific fixes that improve data quality, data access, and productivity for developers or AI agents.

The budget advice also has an experimental element. Forrester identified synthetic data and AI agents used in marketing operations and customer-facing work as areas where organisations should test new approaches while maintaining guardrails.

The broader backdrop is persistent economic and operational uncertainty. Rather than planning for calmer conditions, many leaders appear to be budgeting on the basis that volatility will remain a constant feature of the market.

That helps explain why the guides extend beyond technology and security into areas such as data, AI and analytics, digital business and strategy, marketing, customer experience, and revenue operations. The research suggests AI spending decisions increasingly cross departmental lines, with governance and operational questions affecting the whole organisation rather than a single technology budget.

Sharyn Leaver, Chief Research Officer at Forrester, set out the firm's view of the challenge facing executives. "Business leaders are no longer planning for a return to stability - they're planning for a future where volatility is a constant," said Leaver.

"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: trusted data, strong governance, organizational readiness, and the ability to continuously adapt as technology and customer behavior evolve," Leaver said.