AI adoption glossary
Key terms from this course, in plain English.
- Acceptable-use policy
- Rules telling staff which AI tools they may use, for what, with which data, and how to check and disclose AI output.
- ADKAR
- A change model: Awareness, Desire, Knowledge, Ability, Reinforcement.
- Adoption curve
- The pattern by which new tools spread: early enthusiasts, a pragmatic majority, then sceptics.
- AI champion
- A volunteer in a team who receives extra training and time to help colleagues adopt AI and feed back issues.
- AI literacy
- The skills, knowledge and understanding needed to use AI effectively and responsibly; required of AI providers and deployers under Article 4 of the EU AI Act.
- Automation bias
- The tendency to accept automated output without sufficient scrutiny.
- Case for change
- A clear explanation of why change is needed, what will change and what won't.
- Change management
- Structured methods for helping people and organisations move to new ways of working.
- Community of practice
- An open group where people share techniques, examples and lessons about a topic.
- Deskilling
- Loss of skills when a task is routinely done by automation, making it harder to check or take over.
- Guiding coalition
- In Kotter's model, a group with the influence and commitment to lead a change.
- J-curve
- A dip in performance during the learning period before improvements appear.
- Kotter's 8 steps
- A model for organisational change, from creating urgency to anchoring change in culture.
- Prompt library
- A shared collection of tested prompts and examples for common tasks.
- Psychological safety
- A shared belief that people can take risks, ask questions and admit mistakes without punishment.
- Pulse survey
- A short, frequent survey to track sentiment and identify issues.
- Reinforcement
- Actions that sustain a change, such as recognition and building it into processes.
- Shadow AI
- Use of unapproved AI tools, often with company data, outside governance.
- Task analysis
- Breaking a job into its component tasks to decide which AI should support, automate or leave alone.
- Workflow redesign
- Changing how a process runs — steps, handovers and checks — to use AI effectively.
- Works council
- A body representing employees that, in some countries, must be consulted on changes affecting work.