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Vendor lock-in

A condition in which an agency's data or systems become dependent on a single AI vendor's proprietary format or platform in a way that makes switching vendors difficult or costly, a condition M-25-22 specifically directs agencies to avoid through data portability and interoperability contract terms.

Defined in 3 GAGE programs, which carry 4 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 AI Lobbyist: Certified AI Policy Strategist

A condition in which an agency's data or systems become dependent on a single AI vendor's proprietary format or platform in a way that makes switching vendors difficult or costly, a condition M-25-22 specifically directs agencies to avoid through data portability and interoperability contract terms.

Certified AI Transformation Professional (CATP)

The condition where switching away from a vendor is prohibitively costly (proprietary data formats, deep integration, platform-only skills, no portability terms), so an organization keeps paying unfavorable terms because leaving costs more.

Certified AI Practitioner: Workplace Foundations

Becoming trapped with a provider because your data lives in a proprietary format or the switching cost is prohibitive; prevented by confirming data ownership, export ability, and an exit path before you depend on a tool.

The AI Lobbyist: Certified AI Policy Strategist

The condition of excessive, costly dependency on a single vendor due to proprietary data formats or licensing terms,

Where it is taught

The exact lessons this term appears in. The first module of every program is free with a free account.

Where it shows up at work

A definition is where Vendor lock-in 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.

Tracks executive orders, OMB guidance, agency rules and the state patchwork, and knows which state laws reach hiring, insurance and consumer decisions.

One lesson on this page teach it as a primary outcome.

Plans for a vendor failure, an unsafe model change or a suspended service: rollback, manual fallback, data export and safe decommissioning.

One lesson on this page teach it as a primary outcome.

Interviews, facilitates, challenges and secures action across legal, security, product and business teams without owning every decision.

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.

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.

“state ai law”“colorado ai act”“nyc local law 144”“executive order”“federal ai policy”“state legislation”

Where the frameworks place it: OMB M-25-21 and M-25-22; Colorado SB 24-205; NYC Local Law 144; DORA.

One interview question about it

A US company operates in several states. How do you track which state AI laws apply to which systems, and what changes when a new one passes?

Asked of candidates for us federal and state ai regulation. 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.

Terms it appears with

Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.