Financial regulation has always assumed that decisions can be traced through a clear chain of human accountability. But as AI agents begin directing other agents, that assumption starts to break down. Agentic AI won't just automate tasks—it has the potential to reshape how financial institutions are organised. Decision-making may shift between people and AI systems, reporting lines become more fluid, and the traditional structures underpinning governance, accountability and supervision begin to evolve. In that world, who is ultimately responsible for a decision? What exactly is a regulator supervising?

Bringing together senior policymakers and regulators, this session explores how supervisory frameworks—from senior manager accountability regimes to board oversight and the three lines of defence—need to adapt for organisations where humans increasingly govern systems that, in turn, govern other systems. The discussion will examine how institutions can demonstrate accountability, maintain effective oversight, and provide regulators with meaningful traceability in increasingly agent-driven operating models. Rather than focusing on individual AI decisions, the panel asks a broader question: how should governance evolve when the organisation itself becomes dynamic?

No bank can or should build every AI capability itself. The real strategic question isn't build versus buy; it's whether institutions retain meaningful choice over the technology they depend on. As agentic AI begins making decisions that affect customers, capital, and risk, financial institutions must ask: How much digital dependency is acceptable? Can they trust and explain the decision of models they didn't build? What happens when the AI underpinning critical operations is controlled by a single provider?

The panel explores what digital autonomy should look like in the AI era. Rather than arguing for complete self-sufficiency, the discussion focuses on optionality: the ability to choose between providers, maintain control over sensitive data, satisfy regulatory expectations for explainability, and preserve resilient fallback options when business or technology priorities change. The conversation will examine how banks can adopt AI at scale without sacrificing transparency, governance or strategic independence - and why genuine optionality may become one of the industry's most important competitive advantages.

The more money behaves like software, the more the decisive questions become legal and political rather than technical. Who is liable when a smart contract executes exactly as written and wrongly? How do sanctions and AML function when compliance is embedded in code rather than checked after the fact? What does systemic resilience mean when value moves at machine speed and a flawed rule can propagate across the system in a single run cycle? We will close the track with the question programmable money must answer to earn its licence: governance-by-design or not at all.