Data & Analytics

This session explores how organisations can avoid scaling AI consumption faster than the value they create – particularly as we move from copilots towards agents and autonomous workflows, where token consumption, model choice and the cost of intelligence become increasingly important.

Strong governance should enable innovation – not slow it down. Yet many organisations continue to treat governance and agility as competing priorities, creating unnecessary delays for analytics and AI initiatives.

This session explores how modern governance frameworks are evolving through automation, policy-driven controls and self-service access, enabling organisations to innovate with confidence while maintaining compliance, security and trust across the enterprise.

Many AI models perform well in development but struggle to survive changing business priorities, evolving data and operational complexity. Sustainable AI requires far more than technical accuracy – it demands governance, ownership, monitoring and continuous improvement.

This discussion brings together enterprise leaders responsible for deploying AI at scale to explore what separates long-term success from expensive experimentation.

Discussion topics include:
• Moving beyond proof of concept
• Monitoring model performance over time
• Product ownership and governance
• Building reusable enterprise AI capabilities
• Keeping AI aligned with changing business needs

Delivering successful customer-facing AI requires more than deploying large language models. Organisations must balance innovation with trust, governance and measurable customer outcomes while ensuring AI complements – not complicates – the customer journey.

This session explores how ING is embedding Generative AI into customer engagement strategies while maintaining responsible governance, improving employee productivity and delivering meaningful business value.

Lloyds Banking Group has moved beyond isolated AI projects to establish AI as a core enterprise capability – improving customer experiences, empowering colleagues and delivering measurable business value across the organisation.

This session explores how the organisation is scaling AI responsibly, embedding governance from the outset and building a reusable platform that supports enterprise-wide adoption. Attendees will hear practical lessons from one of the UK’s largest AI transformation programmes.

Topics include:
• Building a secure enterprise AI platform
• Embedding responsible AI into delivery
• Equipping thousands of colleagues with AI skills
• Scaling reusable AI capabilities
• Measuring enterprise-wide business value

The most valuable analytics programmes are rarely straightforward. Behind every successful deployment are lessons learned from failed assumptions, poor-quality data and changing business priorities.

This session explores how organisations are improving decision-making by learning from both successful and unsuccessful analytics initiatives, helping leaders avoid common pitfalls while building stronger, more resilient AI and data strategies.

As Generative AI matures, executive attention is shifting from experimentation to execution. Organisations now face the challenge of embedding GenAI into everyday operations while balancing governance, cost, security and measurable business outcomes.

This panel brings together leaders delivering GenAI programmes at scale to discuss what it takes to move from ambition to sustainable enterprise value.

Discussion topics include:
• Aligning GenAI with business strategy
• Establishing governance that supports innovation
• Prioritising high-value use cases
• Scaling adoption across the enterprise
• Measuring business outcomes beyond productivity gains

Join Chloé, Behavioural Research Manager at Swiss Re, as she explores how behavioural science and AI can be combined to enhance decision-making.

This session will highlight how to design human-AI collaboration within workflows, improve engagement, and manage change effectively – while addressing risks such as skill erosion, lack of oversight, and regulatory challenges.

Learn how putting humans at the centre of AI leads to better outcomes, increased productivity, and measurable business value.