Archives: Agenda

• Defining success before you start: setting metrics that connect AI investment to business outcomes
• Moving beyond productivity anecdotes to a rigorous view of cost, revenue and risk impact
• Reporting AI value to the board: what senior stakeholders actually want to see

• Why fragmented data estates remain the single biggest brake on enterprise AI ambition
• Architectures that work: unifying access to structured and unstructured data without a multi-year replatforming programme
• Embedding governance, security and lineage into the data layer so AI can scale safely

• Practical techniques for making AI decisions transparent, auditable and defensible to regulators and clients
• Building monitoring and human-in-the-loop controls that satisfy risk without slowing the business

• A practical playbook for taking an AI use case from concept to live deployment in a single quarter
• Avoiding the common traps that turn quick wins into stalled projects

• Moving from isolated bots and point solutions to orchestrated, end-to-end intelligent workflows
• Where generative and agentic AI are extending the boundaries of what can be automated
• Real-world results: efficiency, accuracy and capacity gains from institutions already scaling automation

• Moving beyond experimentation: what separates the institutions turning AI ambition into production-grade deployment from those stuck in pilot purgatory
• Where is AI delivering measurable enterprise value today, and how are leaders prioritising investment across the front, middle and back office?
• Building the business case: aligning AI initiatives with commercial strategy, risk appetite and board-level expectations
• Lessons learned from early adopters: what senior leaders wish they had known before scaling AI across the organisation

Humans/workers are ‘freed’ – now what?

Time saved does not necessarily translate to financial return. With humans freed from arduous admin tasks, how can we unlock their full potential?

AI first? A strategy for your organisation

Is AI first the right strategy? How can you embed AI throughout your org?

Engaging the board (stakeholders) with AI

What questions do boards need to know, and how can you frame these? How can you effectively brief, without overwhelming? Briefing direction of travel, rather than rule detail. How to identify early warning signals and key strategic risks for the board?

Death by agents – when should you use?

Danger of empowering people to create hundreds of agents and ultimately, a mess to clean up. How can agents be the death of your business?

AI for AI’s sake – cutting through the hype

Not everything needs AI or even a top-of-the range model – how can you cut through the hype of AI implementation and decide what really benefits from AI