Archives: Agenda

• Product innovation vs margin optimisation
• AI in sales, origination and cross sell
• Pricing, personalisation and yield
• Separating real revenue from internal productivity gains

• New attack vectors
• Behavioural analytics and authentication
• Monitoring and customer harm reduction
• Collaboration with regulators

• Moving from experimentation to portfolio discipline
• Governance models that accelerate rather than obstruct
• What we report to the board
• What we have shut down and why

• Control taxonomy and ownership
• Evidence standards and documentation
• Embedding controls into tooling
• Making governance scalable

• Suitable task types vs unacceptable automation
• Control layers and approval workflows
• Accountability for agent actions
• Audit and rollback mechanisms

• Orchestration and model routing
• Logging, lineage and observability
• Guardrails and AI gateways
• Private AI vs public LLM trade offs

We move beyond demos and prototypes to examine what enterprise AI systems really look like under pressure, and whether firms are investing in the right problems at all.

• Where GenAI and agentic systems are genuinely delivering value today
• Why many AI programmes are optimising the wrong use cases
• The gap between lab performance and production reality
• What leading institutions are choosing not to build

Everyone’s talking about agents. We focus on what’s real, what’s working, and what still doesn’t hold up under pressure

• Where agentic capability is genuinely live in production
• Where positioning runs ahead of functionality
• The gap between demo environments and enterprise reality
• What buyers should be demanding as proof
• Technical and governance due diligence