Course Objective & Scope
An in-depth programme for managers who already have basic AI awareness and now need to steer AI investment as a portfolio of value and risk rather than a series of isolated pilots. It covers the real capabilities and limits of LLMs and agents, build/buy/partner options, KPI and ROI frameworks, AI governance and the operating model in one coherent flow.
Workshops run on cases drawn from the organisation's own sector. By the end, participants assemble a management pack: an executive decision framework, a value and risk matrix, a prioritised use case portfolio and a first 90-day AI roadmap.
Who Should Attend?
- Deputy general managers, directors and business unit leaders
- Digital transformation, strategy and innovation managers
- CIOs, CDOs, CTOs and decision-makers in their teams
- Managers who will sit on the AI steering committee
- Prerequisite: basic AI literacy or the "AI for Executives" course is recommended
Key Takeaways
- Score AI opportunities on value, feasibility and risk to make portfolio decisions
- Distinguish where generative AI and agent-based solutions fit the organisation and where they do not
- Define measurable KPI and ROI hypotheses for AI investments
- Reflect EU AI Act, KVKK and ISO/IEC 42001 requirements in management decisions
- Draft a first design for the organisation's AI operating model and governance structure
- Build a 90-day roadmap with clear owners and milestones
Curriculum
Capability Limits of Generative and Agentic AI from an Executive View
- LLM, RAG and agent architectures explained in business terms
- Hallucination, data leakage and automation risks
- Sector case studies: successful and failed deployments
Value Pools and the Use Case Portfolio
- Scanning the value chain for AI opportunities
- Value–feasibility–risk scoring matrix
- Balancing quick wins and strategic bets
Investment Decisions: Build, Buy, Partner and Cost
- Off-the-shelf SaaS, cloud API and in-house model options
- Token economics and total cost of ownership
- Framing KPI and ROI hypotheses
AI Governance, Regulation and Responsible Use
- EU AI Act risk classes and KVKK obligations
- Designing a management system with ISO/IEC 42001 and NIST AI RMF
- Human oversight, approval points and accountability
Operating Model, Talent and Change Leadership
- Centralised, federated and hybrid AI operating models
- AI Center of Excellence and role design
- Adoption, communication and managing resistance
Capstone Workshop: 90-Day AI Roadmap
- Building the management pack on the organisation's case
- Milestones, ownership and budget assumptions
- Steering-committee style presentation and feedback
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