October 28, 2026 | London | Hosted at Reckitt
AI is moving deeper into the operating model of the enterprise. The implications now extend beyond technology and models and data.
1. AI in Sales, Marketing & Commerce
Driving Growth with AI and the Build for Agentic Commerce
Enterprise AI value has largely been framed around productivity. The next frontier is growth: insight, concept development, personalization, autonomous execution and agent-to-agent commerce.
- Where is AI already producing measurable revenue impact rather than simply reducing the cost of existing work?
- Which parts of the commercial model need to be redesigned rather than simply AI-enabled?
- How do brands maintain differentiation and customer relationships when an AI agent becomes the intermediary?
- What happens when buying agents increasingly interact with selling agents?
2. Enterprise Context
What Must AI Understand About the Business and Best Approaches
Reliable agents need more than access to documents and databases. They need enterprise context: products, customers, policies, processes, business rules, decision rights, relationships, historical decisions and tacit knowledge.
- Does enterprise context become a proprietary layer of advantage when competitors use the same underlying models?
- How should structured data, unstructured knowledge, process, rules and human expertise be connected into usable context?
- Is this a data problem, a knowledge graph, an ontology, a semantic layer — or something genuinely new?
- Who owns and maintains that context as the organization changes?
3. The Hybrid Workforce
If AI Does the Work, How Do People Build Careers
As AI absorbs more knowledge work, the issue extends beyond job displacement to career formation, expertise and leadership development.
- Which skills become more valuable in a workforce of people and agents?
- How should hiring, learning, performance management and leadership models evolve?
- What changes when managers increasingly orchestrate outcomes across both human and digital labor?
- How do apprenticeship and career paths change as entry-level knowledge work compresses?
4. Enterprise AI in Practice
A dirt-in-the-fingernails perspective from Reckitt
A discussion with out host: Where value is becoming real, how work is changing, the constraints that emerge in production, the learning in the journey and the questions that remain unresolved.
Meeting Format
- This is a closed-door working session for Executive Technology Board members. Plan for granular discussions. Peer exchange, practical examples, lessons learned and open questions.
- As always, no marketing presentations. Chatham House Rules. Clear antitrust and anti-collusion guidelines. Written synthesis provided to members following the meeting.
- The agenda is being refined with participating members ahead of the session.