Discovery
The active legwork of finding the AI systems an organization runs, using invoices, interviews, tool audits, vendor questions, and shadow-use surveys together. Discovery precedes every other governance activity, because risk classification, evaluation, logging, and incident response all operate only on systems that are known.
Defined in 3 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in Certified AI Governance Professional (CAIGP).
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 active legwork of finding the AI systems an organization runs, using invoices, interviews, tool audits, vendor questions, and shadow-use surveys together. Discovery precedes every other governance activity, because risk classification, evaluation, logging, and incident response all operate only on systems that are known.
The formal process, within a PUC or other regulatory docket, of requesting and compelling disclosure of information from another party, most often the utility, to build the evidentiary record.
A cheap, bounded exercise testing the prediction a systemic cause makes, run before a class fix is funded so that the funding rests on evidence rather than on a pattern.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Meet your systems: mapping the AI your own organization already runs · Taking Command, Certified AI Governance Professional (CAIGP)
- Energy and Utilities: PUC Dockets, FERC, NERC, and Grid Narratives · Sector Playbooks, The AI Lobbyist: Certified AI Policy Strategist
- Remediation design · Findings, Issues, Root Cause, and Remediation, Certified Enterprise Governance, Risk and Compliance Professional (CEGP)
Where it shows up at work
A definition is where Discovery 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.
Finds every AI system in use, records owner, purpose, data and risk tier, and keeps the record alive as tools change.
One lesson on this page teach it as a primary outcome.
Tracks the policy fight over AI infrastructure: data center siting, grid interconnection, energy and water duties, and who pays for the buildout.
One lesson on this page teach it as a primary outcome.
Finds unapproved AI use, sets which tools are approved and what may be pasted, and detects leakage without policing every keystroke.
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 Governance Managerneeds it at depth
- AI Governance Analystneeds working knowledge · 3 open postings this week
- AI Governance Coordinatorneeds it at depth
- Governance Analystneeds working knowledge · 6 open postings this week
- Chief Audit Executive, AI audit editionneeds working knowledge
- Chief AI Officerneeds working knowledge
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: NIST AI RMF MAP 2; ISO/IEC 42001 Annex A; EU Energy Efficiency Directive data centre reporting; ISO/IEC 27001 Annex A.
One interview question about it
How would you find every AI system in use across an organization, including the ones nobody registered, and keep that inventory current?
Asked of candidates for ai inventory and use-case intake. 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.
- A cybersecurity or information assurance degree carries it as a claim to back up: Data leakage control is familiar; shadow AI is its new form.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.