The Operating Layer
Artificial Intelligence for Enterprise Leaders β strategy, architecture and governance. A self-paced executive course on deciding where AI belongs, deploying it so it survives contact with a real company, and governing it under GDPR, HIPAA and the EU AI Act. Eleven modules, each producing an artefact you can take to a board.
Most organisations don't have an AI problem. They have a placement problem.
Roughly 95% of enterprise generative-AI pilots produce no measurable return, and Gartner expects more than 40% of agentic projects to be cancelled by the end of 2027. Read the post-mortems and the pattern is rarely that the model was incapable. It is that a model was given work a query, a rule or a scheduled script would have done more cheaply and more reliably β while the two steps that genuinely needed judgement were never identified, governed or measured.
This course teaches the discipline that prevents that: where AI belongs, how to connect it to systems you already own, how to govern it under GDPR, HIPAA and the EU AI Act, and how to redesign the organisation around what actually changed. It is written for people who will never write the code and are accountable for the outcome.
Frameworks, not features
Vendor landscapes date in months. A test for whether a step needs a model, and a control set that satisfies three regulatory regimes at once, do not.
Sourced, dated, falsifiable
Claims are cited and time-stamped β from Akerlof and Coase to the 2026 AI Act omnibus that moved the high-risk deadlines most course material still gets wrong.
Every module ships an artefact
A labelled portfolio, a no-list, an integration map, a control map, a scorecard, a layer audit β assembling into a board-ready twelve-month roadmap.
What you will be able to do
By the end of the course, participants will be able to:
- Explain the core principles and potential of Generative and Agentic AI
- Identify opportunities to apply AI for improved workflows and customer engagement
- Integrate AI into digital ecosystems using cloud, APIs, and enterprise tools
- Design agent-based workflows to enhance automation and decision-making
- Evaluate AI platforms for fit, value, and risk
- Address ethical and regulatory considerations, including GDPR and HIPAA
- Develop a strategic AI roadmap or executive adoption plan
- Differentiate between AI hype and strategic reality in business contexts
- Analyze the technological and economic foundations shaping modern AI strategy
- Evaluate AI as a source of competitive advantage within changing industry environments
- Assess organizational approaches to AI integration
- Design strategic approaches for aligning AI with organizational priorities
- Develop a strategic framework for redesigning organizational structures through AI integration
12 modules, about 21 hours
Each module states its objectives, works through the material, and ends in an exercise that produces something you keep. All 12 are published in full, with a single running case, cited sources and a capstone assessed against a public rubric.
- 01What the Machine Actually DoesA working mental model of generative and agentic AI for people who will never write the code β and never need to.You produce: A one-page explanation of your organisation's primary AI use case, written for a sceptical colleague1.5h
- 02Hype, Evidence and the Lemon MarketWhy the market behaves the way it does, and how to read a claim without a technical team.You produce: An evidence ladder, applied to a live proposal on your desk1.5h
- 03Placement: The Five-Question TestDeciding which steps of a process deserve a model β and defending the answer to a sceptical CEO.You produce: A labelled portfolio and a no-list for your own organisation2h
- 04Architecture: How AI Connects to the CompanyCloud, APIs, connectors and enterprise systems explained for decision-makers β enough to ask the right questions and price the real work.You produce: An integration map of your own stack, with the four layers and every boundary marked2h
- 05Designing Agentic WorkflowsTurning a real business process into a designed system: autonomy levels, approval gates, failure paths and evidence.You produce: A complete workflow specification with gates, failure paths and one measurable acceptance criterion2h
- 06Governance: Ethics, GDPR, HIPAA and the AI ActWhat actually constrains an AI deployment, which rules apply to you, and the control set that satisfies most of them at once.You produce: A control map for one real workflow, with named owners2.5h
- 07Evaluating Platforms and VendorsA procurement method for a market where claims are free and verification is expensive.You produce: A weighted evaluation scorecard, completed for two real options1.5h
- 08Advantage: Where AI Creates Moats and Where It Does NotWhy the model is never the advantage, what actually is, and how industry structure shifts underneath you.You produce: A one-page advantage thesis with a falsification clause1.5h
- 09Structure: Your Org Chart Is a FossilAI does not automate tasks so much as reprice coordination β and every structure built on the old price has to be recalculated.You produce: A layer audit of your own function, with one transport block scheduled for removal2h
- 10The Roadmap: Your Executive Adoption PlanSequencing, funding, metrics and the board conversation β assembling everything into a plan you can sign.You produce: A twelve-month roadmap with sequencing, funding model and metrics1.5h
- 11Capstone: The Twelve-Month RoadmapOne assessed deliverable, assembled from the artefacts you built along the way.You produce: The completed roadmap, assessed against a published rubric2h
- 12Appendix: The VocabularyEvery term the course uses, defined once and precisely β because most bad AI decisions start as a word two people understood differently.You produce: A shared vocabulary you can hold a vendor to0.5h
Vantis Diagnostics
A single running case, Vantis Diagnostics, threads through every module: a fictional Netherlands-headquartered laboratory diagnostics group with a US subsidiary, chosen because it exercises GDPR, HIPAA and the EU AI Act simultaneously.
One company, several systems, and deliberately different answers: an internal tool that is minimal-risk, and a patient-facing one that engages special-category data, automated-decision rules and possibly medical-device regulation. Seeing why the same organisation lands in different tiers is the point.
The question a client's chief executive asked mid-walkthrough. The honest answer β most of it, yes β is where this course starts, and why its first test is a test for saying no.
Built for the people who fund, govern and deploy β not build
None. No prior experience with AI or programming is required β only a strategic mindset and responsibility for decisions about technology.
C-suite executives
CEOs, CIOs, CTOs, CMOs and COOs making funding and governance decisions about AI integration.
Business leaders and function heads
Driving digital innovation in operations, marketing, product or strategy.
Managers and team leads
Modernising workflows and aligning teams with emerging technology.
Technical professionals moving into leadership
Taking ownership of digital transformation rather than implementation.
Consultants and advisors
Guiding clients through AI adoption and change management.
A timed exam, and a certificate worth having
25 questions in 40 minutes, drawn at random from a larger bank so every module is represented and no two papers are the same. 20 correct to pass. Pass and a signed certificate arrives by email.