📈 Enterprise Edition · Masterclass

Practical AI for CXOs & Business Leaders

A strategy and governance course for senior leaders who must set AI direction, allocate investment, manage risk and lead adoption — turning "we should do something with AI" into a clear, safe, value-driven enterprise programme.

This is not a technology briefing. It is a decision, value and governance course for enterprise AI.

Register your interest → See the 13 modules
13Modules + capstone
4h · £300or full day · £500
Board-readyGovernance & risk focus
Live onlineWeekend sessions
Curriculum draft — mirrors the enterprise masterclass format and is ready for your review and refinement.
Course overview

Leading AI in a regulated enterprise

Designed for the C-suite, directors, transformation and strategy leads, board members and heads of risk, governance and compliance who must shape and steer enterprise AI.

The course focuses on the leadership work required to move from AI ambition to a governed, value-driven programme. The Enterprise Edition assumes a regulated, multi-stakeholder environment where AI decisions must consider strategy, value, cost, model and data risk, security, responsible use, regulation, operating model, adoption and long-term ownership.

Who it's for

Built for decision-makers

🏢
C-suiteCEO, COO, CIO, CTO, CDO, CFO and CRO setting AI direction.
🧑‍💼
Directors & department headsAccountable for AI-enabled outcomes in their function.
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Strategy & transformation leadsShaping the enterprise AI agenda and portfolio.
⚖️
Board, risk & governanceSteering committee members and heads of risk, governance and compliance.
Learning outcomes

What leaders will be able to do

Course structure

13 modules, each with a concrete output

Every module builds toward an enterprise AI strategy & governance brief you can take to the board.

#TopicPurposeOutput
1AI for the enterprise — the strategic landscapeCut through the hype; understand what AI can and cannot do.Shared strategic vocabulary
2Where AI creates business valueIdentify high-value, defensible opportunities.Value opportunity map
3AI strategy and prioritisationAlign AI to business goals and the wider portfolio.AI strategy outline
4The economics of enterprise AIUnderstand cost, ROI and value realisation.Investment lens
5Build, buy or partnerMake sourcing, vendor and platform decisions.Sourcing decision guide
6AI risk, ethics and responsible useUnderstand model, data, reputational and regulatory risk.Risk appetite statement
7AI governance and operating modelEstablish oversight, roles and accountability.Governance framework
8Data, security and confidentialityUnderstand data readiness and protection at leadership level.Readiness & risk view
9Regulation and complianceNavigate the EU AI Act, sector rules and audit expectations.Compliance checklist
10Leading AI adoption and cultureDrive change, upskilling and responsible experimentation.Adoption plan
11Measuring success and valueDefine KPIs and value tracking for AI programmes.Value scorecard
12AI roadmap and portfolioSequence initiatives from pilot to scale.Enterprise AI roadmap
13CapstoneCreate a leadership-ready AI strategy & governance brief.Strategy brief
Detailed module outline

What's inside each module

1 AI for the Enterprise — the Strategic Landscape ▾
  • What AI, GenAI, LLMs, RAG, agents and copilots really are — without the hype.
  • What AI can and cannot reliably do in an enterprise context today.
  • How AI is reshaping industries, operating models and competition.
  • The leadership agenda: strategy, value, risk, governance and people.
2 Where AI Creates Business Value ▾
  • Efficiency, quality, risk reduction, capacity release and new capability — which value actually applies.
  • Spotting high-value, defensible use cases versus shallow "AI theatre".
  • Value, feasibility, data readiness and risk as prioritisation lenses.
  • Benchmarks and patterns from comparable regulated organisations.
3 AI Strategy and Prioritisation ▾
  • Aligning AI ambition to business strategy and enterprise priorities.
  • Deciding where to lead, where to fast-follow and where to wait.
  • Balancing quick wins against foundational investments.
  • Setting a clear, communicable AI vision and guiding principles.
4 The Economics of Enterprise AI ▾
  • Cost drivers: model usage, data preparation, integration, human review and ongoing run cost.
  • One-off pilot cost versus sustained operating cost at scale.
  • Framing ROI honestly and avoiding unrealistic baselines.
  • Funding models and investment governance for AI initiatives.
5 Build, Buy or Partner ▾
  • When to build, when to buy, when to configure and when to partner.
  • Evaluating AI vendors, platforms and models — capability, data policy and lock-in.
  • Contracting, data protection and exit considerations.
  • Balancing speed to value with strategic control.
6 AI Risk, Ethics and Responsible Use ▾
  • Hallucination, bias, confidentiality, explainability, accountability and model risk.
  • Reputational, legal and operational risk from AI misuse.
  • Responsible AI principles translated into leadership decisions and controls.
  • Setting a clear organisational risk appetite for AI.
7 AI Governance and Operating Model ▾
  • Establishing oversight: committees, roles, accountability and decision rights.
  • Policies, approval gates and escalation paths for AI use.
  • Centralised, federated and hybrid AI operating models.
  • Embedding governance without stifling responsible innovation.
8 Data, Security and Confidentiality ▾
  • Why data readiness determines AI success — at a leadership level.
  • Confidentiality, access control and preventing data leakage.
  • Security expectations for internal and vendor-hosted AI.
  • The questions leaders should ask about data before approving AI.
9 Regulation and Compliance ▾
  • The regulatory landscape: EU AI Act, sector-specific rules and emerging standards.
  • Risk classification and obligations for different AI use cases.
  • Audit, traceability and evidence expectations.
  • Preparing the organisation for scrutiny and assurance.
10 Leading AI Adoption and Culture ▾
  • Adoption as a leadership responsibility, not an IT project.
  • Upskilling, role change and responsible experimentation.
  • Overcoming fear, resistance and shadow AI use.
  • Sponsorship, communication and rollout sequencing.
11 Measuring Success and Value ▾
  • Defining KPIs and leading indicators for AI programmes.
  • Tracking value realisation from pilot through to scale.
  • Avoiding vanity metrics; connecting AI to business outcomes.
  • Reporting AI value and risk to the board.
12 AI Roadmap and Portfolio ▾
  • Sequencing initiatives from experiment to pilot to enterprise scale.
  • Managing an AI portfolio and balancing risk across it.
  • Capability, platform and talent foundations for the long term.
  • Building a resilient, adaptable multi-year AI roadmap.
13 Capstone — Enterprise AI Strategy & Governance Brief ▾
  • Create a leadership-ready brief for your organisation's AI direction.
  • Covers vision, priorities, value case, risk appetite, governance and operating model.
  • Includes sourcing approach, investment, adoption plan and roadmap.
  • Final review focuses on clarity, feasibility, governance readiness and board-worthiness.
Leadership examples & exercises

Board-level scenarios

Setting an enterprise AI vision & guiding principles Standing up an AI governance committee Evaluating a vendor AI platform decision Defining the organisation's AI risk appetite Approving a RAG assistant business case Portfolio prioritisation across departments Drafting a responsible AI policy Measuring ROI of an AI pilot EU AI Act regulatory readiness review
Capstone assignment

An enterprise AI strategy & governance brief

Each leader or group creates a brief practical enough to take to an executive committee or board.

  • AI vision & strategic priorities
  • Value opportunity map
  • Business & investment case
  • Build / buy / partner approach
  • Risk appetite & controls
  • Governance & operating model
  • Regulatory & compliance position
  • Adoption & change plan
  • Value scorecard & KPIs
  • Multi-year AI roadmap
Formats & pricing

Two live online sessions

Run at weekends, live online. Per-person pricing below — board briefings and private executive sessions on request.

Half day · 4 hours£300 per person

Leadership workshop

Senior leaders & decision-makers

Strategy, value, prioritisation, risk and governance essentials with a guided strategy exercise.

Full day · 8 hours£500 per person

Strategy intensive

Executive teams shaping a programme

Everything in the half-day plus operating model, regulation, adoption, roadmap and the capstone strategy brief.

Pre-work & take-aways

What you bring, what you keep

Optional pre-work

  • Your current strategic priorities and where AI might support them.
  • Known AI initiatives, pilots or vendor conversations in flight.
  • Your risk, regulatory and governance context.
  • One strategic question about AI you want answered.

Post-course assets

  • AI strategy outline template.
  • Value opportunity map.
  • AI governance framework & operating-model options.
  • Risk appetite & responsible-use templates.
  • Build / buy / partner decision guide.
  • Enterprise AI roadmap template.
  • Board question bank & glossary for leaders.
Pricing & dates

Bring this masterclass to your leadership

Pricing depends on the format, audience and level of customisation to your sector and strategy. Tell us a little about your leadership team and we'll come back with options and available dates.

£300 · 4-hour workshop  |  £500 · full day Per person, live online at weekends. Send the form for upcoming dates or to arrange a private board / executive session.

We’ll only use your details to reply about this masterclass.