Session One: AI and innovation: reinventing the digital-first bank
Chair's opening remarks
Juliette Foster
Keeping the customer at the heart of innovation
Krista Phillips
Building an AI-first bank
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Building the first AI-native financial institution: what does ‘AI-native’ actually mean, and why does it require building a new bank rather than just improving the ones we already have?
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Taking stock of the challenges: what are the hardest problems to solve (technically, legally, and operationally) in embarking on building an AI-first institution?
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When it comes to AI agents making autonomous financial decisions, how prepared are identity and compliance practices today to ensure effective controls and risk management? And what may need to change?
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With AI being part of a nexus of change amidst the rise of agentic finance, stablecoins and digital assets, how do you see these trends intersecting?
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Over the next 2-4 years, what could agentic finance and commerce actually look like in practical terms? What are the implications for banks and how should they be preparing?
Adam Berrey
Theodora Lau
AI Transformation: from business case to banking reinvention
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With AI accuracy key to customer-facing solutions, what steps can banks take to achieving more predictable and deterministic outcomes in practice?
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How far can incumbent banks really become AI-first on top of their existing core banking infrastructure, and where does AI create a new imperative to modernize the core?
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What role can agentic capabilities play in fundamentally changing how modernization of the tech stack is done? And what are the trade-offs for banks to consider?
Ignacio Sarquis
Chris Panneck
The AI-powered bank: unlocking enterprise agility and new revenue models
- From experimentation to enterprise value: what separates the organizations that are generating measurable business value from those still stuck in experimentation mode?
- The AI-powered bank: when you look three to five years ahead, which banking functions are most likely to be fundamentally reinvented by AI, and which are being overhyped today?
- Beyond AI as an efficiency tool: where do you see the greatest opportunity for AI to create entirely new products, services, or sources of revenue for banks?
- Building the AI-ready enterprise: what are the architectural decisions banks need to make now in cloud, platforms and operating models to avoid creating the next generation of legacy technology?
- Data as a competitive advantage: what does a modern data strategy look like in an era where AI models are only as effective as the data that powers them?
- The build-versus-buy dilemma: as foundation models evolve rapidly, where should banks differentiate through proprietary AI capabilities and where should they rely on external providers?
- Agentic banking: as agents become capable of executing increasingly complex tasks, where do you see the biggest opportunities, and challenges, for deploying autonomous agents in the bank?
- Ensuring responsible AI: how should banks redesign governance, controls, and human oversight to enable innovation at pace without creating new risks?
Michael Blanco
Kelley Conway
Greg Clark