Trends 2026: Powering the Future of AI

To realise enterprise AI ROI, integration, analytics, and business leaders must rewire their approach. But with so many organisations invested, yet so few seeing a return, what needs to change? Centralise for control, or decentralise for innovation? How about both – and neither? It’s the classic “governance vs self-service” debate, revisited.

Panel discussion: Can AI tackle financial crime: Strengthening defences across the fraud lifecycle

As financial crime grows more sophisticated, so must our defences. This panel explores how AI is transforming fraud detection and where its blind spots still lie. From real-time detection to post-payment forensics, we will examine how institutions can build resilient, end-to-end fraud strategies that balance automation with accountability.

Moderator: Bartosz Golba, Director of research and analysis, GlobalData

Agentic AI at scale: Shifting the fulcrum

Agentic AI promises systems that can act, adapt, and make decisions at scale. As that capability increases, a more fundamental question emerges: where does control and accountability actually sit? In this session, Jonathan Sunderland sets the context for Agentic AI beyond capability alone, exploring how organisations must think systemically about decision-making, trust, and boundaries, and examining what must change, what must stop, and what must remain under explicit control. As enterprises push toward more autonomous systems, the real constraint is not capability, but whether the system they are built on can support them reliably, transparently, and at scale. The session examines how one enterprise, working with Ab Initio, has taken a strategically different approach to shifting the fulcrum and building the foundations required for Agentic AI.

Scaling generative AI in customer service

Generative AI is redefining customer service in the financial sector. Yet the real challenge is not launching a chatbot or automating a single process. It is scaling AI across channels and teams in a way that delivers consistent quality, lower cost to serve, and higher customer satisfaction. Scaling requires strong AI models, but even more importantly, it demands redesigned processes, trusted data, clear governance, and leaders willing to rethink how service is delivered.