Themed lunch areas:

• Banking: capital, new entrants, technology and culture
• Asset management: private markets, wealth management and sustainable investing
• Insurance: climate, AI and cyber risks
• Pitch stage open with series of short fintech pitches   

AI in financial services: From hype to implementation 

Current applications of AI: fraud detection, credit scoring, algorithmic trading, and customer service - Moving from pilot projects to scaled deployment - Data quality, availability, and governance as prerequisites for effective AI - Explainability and transparency: addressing the "black box" problem in AI models - Regulatory expectations for AI use in financial services: model risk management and accountability - The competitive advantage of AI: efficiency gains, enhanced decision-making, and personalised services - Ethical considerations: bias, fairness, and the impact on customers and employees - Collaboration between financial institutions, technology providers, and regulators 

Which global problems might AI solve and in what timeframe? 

International governance, regulation and standards for AI 

Overview of emerging AI regulatory frameworks: EU AI Act, UK approach, US executive orders, and China's regulations - The challenge of regulating a rapidly evolving technology: principles-based vs. prescriptive approaches - Risk-based regulation: categorising AI applications by potential harm - Standards for AI safety, robustness, and accountability - International coordination efforts: OECD AI principles, G7 initiatives, and UN discussions - The role of industry self-regulation and voluntary commitments - Balancing innovation with public trust and societal values - Ensuring that AI governance frameworks are interoperable across jurisdictions

Pitch stage open with series of short fintech pitches   

The AI leaders’ perspective: where will we be in 5- and 10-years’ time?

Predictions for AI capabilities: from narrow AI to more general intelligence - The trajectory of large language models and multimodal AI systems - AI in the workplace: augmentation vs. automation and the future of human-AI collaboration - Breakthrough applications on the horizon: autonomous systems, advanced robotics, and creative AI - The competitive landscape: leading AI companies, research institutions, and national strategies - Infrastructure requirements: computing power, energy consumption, and sustainability - Societal implications: education, employment, governance, and ethical frameworks - Ensuring AI development is aligned with human values and global challenges 

Cybersecurity and operational resilience: A board-level imperative 

The evolving cyber threat landscape: state-sponsored attacks, ransomware, and supply chain vulnerabilities – Recent high-profile cyber incidents in financial services - Regulatory expectations for cybersecurity and operational resilience: DORA, PRA/FCA requirements, and international standards - The board's role in cyber governance - Building cyber resilience: prevention, detection, response, and recovery capabilities - Third-party risk management - The intersection of cybersecurity and AI - Collaboration across the industry: information sharing, joint exercises, and collective defence - Investing in talent, technology, and culture to strengthen cyber defences