Executive Programs
Chief AI Officer Program
A 12-week executive program for leaders responsible for making AI deliver value.
12 weeksAdvanced12 modules
About this course
A 12-week executive program for leaders responsible for making AI deliver value. You will align AI with business strategy, prepare the data and platforms it needs, choose and scale the right use cases, measure the value, and govern AI responsibly, finishing with an enterprise AI roadmap you present to an executive panel.
What you'll learn
- Align AI strategy with business goals.
- Assess your organization's AI maturity and readiness.
- Identify and prioritize measurable, high-value AI use cases.
- Create the data strategy and governance that AI needs.
- Make sound build, buy or partner decisions for AI platforms.
- Move AI from pilot to production and measure its value.
- Establish policies for trustworthy, secure and compliant AI.
- Build organizational support, skills and buy-in for AI.
Curriculum
12 modules
- Machine learning, generative AI and AI agents explained
- What AI can and cannot do
- Trends shaping the next three years
- The Chief AI Officer's role and mandate
- AI maturity models
- Assessing data, skills, technology and culture
- Quick wins versus foundations
- Setting the AI ambition
- Linking AI to strategic priorities
- Where AI creates value: revenue, cost, risk, experience
- Building the AI strategy on a page
- Funding and governance models
- Data as a strategic asset
- Data quality, ownership and governance
- Privacy and data protection
- When models meet changing markets
- Cloud AI services and foundation models
- Open and closed models
- Build, buy or partner decisions
- AI architecture and costs
- Prompting techniques for business tasks
- Building simple AI agents and automations
- No-code and low-code AI tools
- Evaluating AI output quality
- Use-case discovery workshops
- Value, feasibility and risk scoring
- Customer-facing versus internal use cases
- Building the AI portfolio
- MLOps and LLMOps basics
- Integrating AI into processes and systems
- Monitoring, quality and cost control
- Why pilots fail to scale
- AI business cases and KPIs
- Measuring productivity and quality gains
- Total cost of AI ownership
- Reporting AI value to executives
- Bias, fairness and explainability
- AI security and misuse
- Regulation and compliance, including the EU AI Act
- AI policies and governance committees
- AI operating models and centres of excellence
- Skills, roles and reskilling
- Change management for AI adoption
- Working with HR, legal and IT
- Sequencing initiatives and investments
- Governance and reporting rhythm
- Communicating the AI vision
- Capstone presentations to an executive panel
Who it's for
Technology, data and digital leaders, innovation and transformation heads, and executives who will own AI in their organization.
Before you start
No formal prerequisites. Bring curiosity and a willingness to practise.
Let's plan your next step together.
Tell us the course or certification you have in mind and we'll send the outline, upcoming dates, fees and private-team options.