Agentic AI has moved from pilots to systems that touch real credit decisions, real client money and real compliance rules, and the institutions getting the governance right this year are setting the ceiling for the next decade. This session examines where accountability sits once an agent, not a person, initiates the action, across risk, audit and reporting lines — and then confronts the scenario most institutions would rather not discuss: what actually happens in the moments after an agent goes wrong.

An agent doesn't take a coffee break. When it fails, it can fail at machine speed, across every transaction it touches, before a human even notices. So the real test isn't whether agents fail, but how fast an institution can contain them when they do, and who is authorised to make that call. This discussion moves from the accountability question to the operational one: what real-time containment looks like in practice, where autonomous systems are most likely to break, and how to build the kill switches and safeguards that limit the blast radius before autonomy is extended any further.

Attendees leave with a sharper view of the controls that need to exist before autonomy is extended further. One of the key questions the panel will look to dive deeper into: Who is accountable when an autonomous agent makes a bad call, moves client money, or silently breaks a compliance rule?

The conversation around AI in financial services has moved beyond experimentation. The challenge is no longer identifying promising use cases—it's deploying AI at scale in ways that deliver measurable business value. From payments and banking to fintech and customer engagement, leading institutions are embedding AI into core operations to improve productivity, strengthen risk management, personalise customer experiences, and accelerate innovation. Yet while some initiatives become enterprise capabilities, many others remain trapped in pilot mode.

Bringing together leaders from across the financial services ecosystem, this panel explores where AI is creating tangible impact today, what it takes to scale successful deployments across the organisation, and the operational, cultural, and governance challenges that determine whether AI delivers lasting value. The discussion will examine how institutions are prioritising AI investments, measuring success beyond productivity gains, and building the data, operating models, and organisational capabilities needed to move from isolated use cases to enterprise-wide transformation.

Core banking functions such as credit decisions, trade finance, fraud detection and KYC are shifting from pilot demonstrations into live, algorithm-driven workflows, and the institutions pulling ahead are rebuilding these processes end to end rather than adding AI on top of what already exists.

This session brings together the people actually doing that rebuild - the platforms it runs on, the institutions deploying it, and the regulators overseeing it - to work through what that rebuild actually requires: which controls move from human sign-off to automated checkpoints, and where the audit trail needs redesigning rather than retrofitting.