Generative AI
The broader term for any AI system that produces new content, such as text, images, audio, code, or video, based on patterns learned from training data. Large language models are one specific type of generative AI, built for text and language generation specifically.
Defined in 3 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in The AI Lobbyist: Certified AI Policy Strategist.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
The broader term for any AI system that produces new content, such as text, images, audio, code, or video, based on patterns learned from training data. Large language models are one specific type of generative AI, built for text and language generation specifically.
AI that creates new content, text, images, audio, code, or video, by sampling learned patterns rather than retrieving existing content. The most variable capability; as of 2026, video generation is a mainstream production capability, not an experiment.
AI that creates new content (text, images, code, audio, video) based on patterns learned during training.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- What is AI? Definitions, History, and Types · AI Fundamentals, Certified AI Practitioner: Workplace Foundations
- What AI Really Is: No Hype, No Myths, No Fear · Foundations of AI for Lobbyists, The AI Lobbyist: Certified AI Policy Strategist
- The AI Technology Stack Decoded · AI Literacy for Decision Makers, Certified AI Transformation Professional (CATP)
Where it shows up at work
A definition is where Generative AI starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Uses generative AI tools daily, knows what a model can and cannot do, and can say where an output should not be trusted.
2 lessons on this page teach it as a primary outcome.
Decides where AI should be used, where it should not, and which use cases create measurable value, tied to the organization's priorities.
One lesson on this page teach it as a primary outcome.
Designs role-based AI training that measures skill, not attendance, with approved-use guidance, office hours and communities of practice.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- AI Adoption and Enablement Leadneeds it at depth
- AI Literacy Leadneeds it at depth
- Operations Manager, AI-readyneeds it at depth
- Chief AI Officerneeds it at depth
- Chief Information Officer, technology leadership editionneeds it at depth
- AI Program Managerneeds working knowledge · 11 open postings this week
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
Where the frameworks place it: EU AI Act Article 4; DOL AI Literacy Framework.
One interview question about it
Walk me through a task you now do with an AI tool. Where did you stop trusting its output, and how did you know?
Asked of candidates for working ai fluency. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- Recent graduate in law, policy, business or data carries it as a claim to back up: Most graduates already use the tools daily.
- Teachers, trainers and instructional designers carries it as a claim to back up: Most educators are already using AI in preparation.
- A business, MBA or technology management degree carries it as a claim to back up: Strategy and opportunity triage are the core of the degree.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.