Senior leaders from banking, asset management, regulation and policy met under the Chatham House Rule to separate where AI is creating value now from what agentic systems will require next. The full report is now available.
Artificial intelligence is rapidly moving from experimentation to real-world deployment across financial services. The next phase of AI in finance may be defined not simply by more powerful models or smarter copilots, but by the rise of agentic systems: AI that can plan, execute multi-step tasks, interact with tools, coordinate workflows, and escalate decisions to humans when appropriate.
For financial institutions, this shift opens significant new opportunities for efficiency, innovation, and customer value while also introducing new questions around governance, control, accountability, and risk.
This roundtable brought together senior leaders to explore where AI is already delivering tangible value, and how the emergence of agentic AI could reshape the industry in the years ahead.
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Current use cases show where AI is creating value today; agentic AI raises the next set of questions about workflow, control and institutional readiness.
The clearest results came from defined tasks close to a real user need, where AI released capacity without removing human judgement.
AI added to a process built around manual checks and legacy systems produces little. The end to end workflow has to be mapped first.
Colleague facing assistance and autonomous customer facing action were treated as different categories, with review and escalation retained for high impact decisions.
Token, licence, compute and assurance costs may decide which use cases survive at scale, so feasibility demonstrations are no longer enough.
Once systems plan and act, ownership, permissions, auditability, incentive alignment and resilience matter as much as model performance.
The strongest cross cutting finding. Professionals lack practical understanding of what AI can do, where it fails and how to redesign work around it.
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