Starting from zero
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AI Strategy Curriculum
Strategy should make the next decision easier, not create a longer list of technologies.
A business-led learning path for leaders who need to move from broad AI interest to a focused set of decisions, use cases, and practical next steps.
Programme architecture
A curriculum that meets people where they are.
- For
- Leadership teams, business owners, operating leaders, and technology sponsors.
- Format
- Leadership sessions, workflow interviews, and a working roadmap
- Typical shape
- Four facilitated modules plus a decision workshop
Already experimenting
Turn scattered AI activity into a common opportunity map, clearer ownership, and a more useful sequence.
Preparing to scale
Establish decision rights, portfolio guardrails, and a way to compare pilots before investment expands.
Sessions and working outcomes
The work is designed to leave something useful behind.
Leadership alignment
What do we want to improve, why now, and what must remain true for people, customers, and the business?
Working outcome: A shared strategic question and success criteria.Workflow opportunity mapping
Where is work repeated, delayed, difficult to find, or inconsistent enough that an improvement would matter?
Working outcome: A map of candidate workflows and points of friction.Use-case evaluation
Compare value, feasibility, readiness, information, risk, ownership, and adoption effort without pretending one score decides everything.
Working outcome: A prioritised use-case portfolio.Roadmap and governance
Choose the first learning moves, named owners, decision points, and evidence needed to continue, pause, or redesign.
Working outcome: A practical 90-day roadmap.What the organization keeps
Tools, decisions, and practices that can travel into the next phase.
- Leadership AI charter
- Workflow opportunity map
- Use-case decision record
- 90-day learning roadmap
- Decision-rights and governance outline
Find the right entry point
Start with a short practical check, then decide the right level of support.
The learning path
Four stages, designed to build on each other.
Frame
Establish a shared business question, desired outcomes, and the limits of the decision.
Map
Make work, friction, information, and affected people visible before comparing solutions.
Choose
Compare opportunities through value, feasibility, ownership, information, and responsible-use conditions.
Sequence
Define the first test, what evidence matters, and how the organization will decide what changes next.
What participants leave with
Work that can continue after the session.
- A leadership-aligned problem statement
- A prioritised opportunity map
- Named owners and decision boundaries
- A practical roadmap for learning, not a speculative technology plan
The thesis
The AI Strategy Thesis
Read the point of view behind this curriculum, the decisions it is designed to support, and the practices that make the work durable.
Download thesis outlineFind the right starting point