Generative and Agentic AI in Financial Markets: From Pilot to Platform

Financial markets are at an inflection point in their relationship with artificial intelligence. The question is no longer whether to invest, it is how quickly institutions can move from experimentation to operational deployment, and what separates the firms that are scaling from those still stuck in extended pilot phases.

The gap is wider than most assume. Sell-side institutions are deploying agents at a materially faster rate than the buy side. Within the buy side, hedge funds are a full 16 percentage points ahead of asset managers on operational deployment. Canada is outpacing the UK .Across every segment and geography, the same pattern holds: firms that prioritised data readiness are scaling, while those that led with model capability are still piloting. The foundation matters more than the technology built on top of it.

This white paper, based on a survey of 200 senior AI decision-makers at buy-side and sell-side institutions across the USA, UK and Canada, explores the five forces shaping the next era of AI deployment in financial markets:

• The build versus buy divide – why the decision is driven by legacy infrastructure rather than strategy, and what AI sovereignty means in practice for buy-side firms protecting proprietary data and algorithms.
• Real-world ROI and where AI is delivering – the use cases generating measurable value today, the practitioners putting hard numbers on their AI investments, and the areas where firms are still falling short.
• What agents actually look like in practice – how firms are operating across the autonomy spectrum, where deployment intent is strongest, and what the data reveals about institutional risk appetite for autonomous AI.
• The data problem in detail – why data trust dominates quality concerns across both segments, and why UK and North American firms face inverted data challenges requiring fundamentally different solutions.
• Unlocking budget and senior buy-in – the ROI windows, proof points and internal framings that move the CFO conversation from scepticism to approval, and why organisational culture is the ultimate scaling differentiator.

Together, these themes point to a single underlying reality: the AI race in financial markets is being won by the firms that have resolved their data foundations, democratised access to AI tooling, and built the cultural conditions for deployment at scale. For institutions still navigating that journey, the data in this white paper offers a map of where the market stands, and what the leading edge looks like in practice.