Investment Research Spend Flat Despite Rising AI Demand

What happened

Research from Substantive Research shows that spending on investment research has stayed flat even as asset managers and banks step up their calls for AI-powered research and data tools. The findings point to a widening disconnect between how enthusiastically financial institutions talk about AI-driven research capabilities and how much they are actually willing to allocate to acquiring them.

According to the report, buy-side and sell-side firms continue to ask providers for more sophisticated, AI-enabled research outputs and data products, but procurement budgets for research have not grown in step with that demand. The result is a market where expectations around AI capability are rising while the commercial willingness to pay for it lags behind.

Why it matters

This is fundamentally a story about AI adoption economics rather than AI capability itself: the technology to deliver richer, faster, more personalised research exists and is being actively requested, but the budget cycle that funds it has not caught up. For transformation leaders in financial services, it is a reminder that demand signals for AI tools do not automatically translate into funded mandates — someone still has to make the case that AI-enhanced research is worth paying more for, not just worth asking for.

It also exposes a familiar pattern in enterprise AI rollouts generally: internal stakeholders want the upside of AI-driven products without necessarily reallocating spend to secure it, often assuming efficiency gains will be absorbed within existing budgets. Providers of AI-enabled research and data tools may need to get sharper about quantifying value — in time saved, decision quality, or competitive edge — if they want research budgets to actually move.

The Renascence take

The gap Substantive Research has identified is less about technology readiness and more about an unresolved value conversation between buyers and providers.

Asking for more AI capability while budgets stay flat is a classic behavioural tell: stakeholders are expressing aspiration, not committing to a trade-off. Providers chasing this demand should stop pitching "more AI" as a feature and start pitching a measurable outcome — a specific decision made faster, a specific risk caught earlier — because that is the only currency that reliably unlocks new spend. Buy-side and sell-side firms, for their part, should be honest with themselves about whether their AI wishlist is a genuine investment priority or simply a hedge against looking behind the curve.