AI strategy glossary
Key terms from this course, in plain English.
- AI literacy
- The knowledge and skills people need to use AI effectively and responsibly, and to understand its limits.
- AI system inventory
- A register of the AI systems an organisation uses or builds, with owners, purposes and risk ratings.
- Baseline
- The measured performance before a change, used to judge whether the change worked.
- Build vs buy
- The decision whether to develop an AI capability in-house, build on a platform, buy a product or partner.
- Business case
- A structured argument for an investment: what changes, benefits, full costs, risks and how success will be measured.
- Centre of excellence (CoE)
- A central team that sets AI standards, runs shared platforms and supports business units.
- Change management
- Helping people and processes adapt to a new way of working so the benefits are realised.
- Feasibility
- How achievable a use case is, considering data, technical complexity, integration, risk and change.
- Hub and spoke
- An operating model where a central hub provides platforms and standards and business-unit spokes deliver use cases.
- KPI
- Key performance indicator: a measure that tracks progress towards an important objective.
- Lock-in
- Dependence on one vendor that makes switching costly or difficult.
- Operating model
- How an organisation structures teams, decisions, processes and platforms to deliver AI.
- Pilot
- A time-boxed trial with real users and data, designed to test a hypothesis and support a scale, iterate or stop decision.
- Portfolio
- The full set of AI initiatives, managed together to balance value, risk and learning.
- Proportionate governance
- Oversight matched to the risk of each AI use, so low-risk uses move quickly and high-risk ones get deeper review.
- Quick win
- A use case with high value and high feasibility — a good place to start.
- Risk appetite
- The level and type of risk an organisation is willing to accept in pursuit of its goals.
- Roadmap
- A plan sequencing initiatives over time, often in horizons such as now, next and later.
- ROI
- Return on investment: the benefits of an initiative relative to its costs.
- Scorecard
- A concise report of key measures used by leadership to steer a programme.
- Shadow AI
- Staff using AI tools that haven't been approved, often with company data, outside governance.
- Strategic bet
- A high-value but harder use case that needs foundations or investment before it can succeed.
- Use case
- A specific business problem or opportunity where AI is applied, with users, data and a measurable outcome.
- Value lever
- A way AI creates value: productivity and cost, revenue and growth, experience, or risk and quality.
- Vanity metric
- A number that looks good (such as logins) but doesn't show whether outcomes improved.