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AI investment across Financial Services is accelerating rapidly, but the returns are not evenly distributed. While some institutions are already generating measurable business value through improved productivity, faster decision making and more intelligent customer operations, many others continue to invest heavily while struggling to move beyond isolated pilots and experimentation.

The gap between AI ambition and enterprise execution is widening. The decisions leadership teams make over the next 12 to 24 months around governance, operating models, data foundations, talent and execution discipline will increasingly determine which institutions create long term competitive advantage and which fall behind.

This session moves beyond the hype to focus on the harder operational and strategic questions senior leaders are now facing. Where should boards demand measurable ROI and where does continued experimentation still make sense? Why do so many AI initiatives fail to scale into production across large financial institutions? What differentiates the organisations successfully embedding AI into core business operations from those still trapped in proof of concept cycles? How do you monetise data assets that most organisations are still leaving largely untapped?

The discussion will explore the topics shaping the next phase of enterprise AI adoption across Financial Services, including Agentic AI driven operating models, intelligent automation across risk and compliance, the evolving regulatory landscape and the organisational challenges involved in scaling AI responsibly and effectively.

This is a conversation for leaders who have moved beyond asking whether AI matters and are now focused on how to turn AI investment into measurable enterprise value.