- What “inevitable” actually means in AI adoption
- Separating signal from noise in vendor and internal claims
- Where to place bets and where to hold back
- Building institutions that can adapt, not just predict
- Data quality and availability challenges
- Governance and ownership issues
- Integration with legacy systems
- Building AI-ready data foundations
- API-first interaction models
- Structured vs conversational interfaces
- Authentication and identity challenges
- New service design principles
- Rise of agent-initiated interactions
- Detecting human vs machine traffic
- Redefining digital channels
- Implications for customer strategy
- Defining success and failure early
- When to stop investment
- Avoiding innovation theatre
- Reallocating capital to proven use cases
- Utility and bias testing
- Regulatory comfort levels
- Operationalising PETs
- Production examples
