AI Strategy for Leaders

Develop a grounded view of what AI can do today and what leaders must own.

• Generative AI, predictive models, and automation: key differences
• Strengths and failure modes: hallucination, bias, inconsistency
• Hands-on comparison of assistants on a leadership task
• Separating vendor claims from evidence
• Accountability: what cannot be delegated to a tool

Hands-on lab: Run a briefing task in two assistants, assess the accuracy of each, and write a short note on what you would trust and what you would check.

Turn broad interest in AI into a ranked portfolio of well-defined use cases.

• Mapping value chains and pain points
• Defining a use case: problem, users, data, output, owner
• Scoring value, feasibility, data readiness, and risk
• Quick wins versus strategic bets
• Build, buy, or use existing tools
• Avoiding solutions in search of a problem

Hands-on lab: Score eight use cases from your organisation in a shared sheet and defend your top three in a live review.

Identify and manage the main risks of AI use before they become incidents.

• Privacy and confidential data: what may enter which tools
• Accuracy, hallucination, and consequences of unchecked output
• Bias and fairness in decisions affecting people
• Security, shadow AI use, and vendor due diligence
• Intellectual property and contractual terms
• Human-in-the-loop design for consequential decisions

Hands-on lab: Build a risk register for your top use case, assigning likelihood, impact, controls, and an accountable owner to each risk.

Create practical governance that enables safe use rather than blocking it.

• Roles and decision rights: sponsor, owner, reviewer, approver
• Acceptable-use policy contents and tiers of risk
• Approval workflow for new tools and use cases
• Awareness of relevant regulation and when to seek legal advice
• Documentation, audit trails, and incident reporting
• Reviewing policy on a regular schedule

Hands-on lab: Draft a two-page acceptable-use policy and approval flow, then test it against three realistic scenarios from your sector.

Plan the human side of adoption: trust, skills, roles, and communication.

• Common barriers: fear, unclear value, skills gaps, workload
• Stakeholder mapping and communication planning
• Training and support models for different roles
• Effects on roles and work design, handled transparently
• Building champions and feedback channels
• Fairness and inclusion in access to tools and training

Hands-on lab: Create a stakeholder map and a ninety-day communication and training plan for your pilot.

Design evidence-based pilots, judge tools and vendors with clear criteria, and sequence your roadmap for presentation.

• Baselines, success measures, and quality criteria
• Pilot design: scope, duration, sample, and stop rules
• Measuring quality, time, error rates, and user experience
• Vendor evaluation questions on data use, security, and support
• Total cost of ownership beyond licence fees
• Deciding to scale, adjust, or stop

Hands-on lab: Write an evaluation plan with a vendor question list for your pilot, then present your roadmap live to a peer acting as a sceptical board member and revise it.