System card
A document describing a deployed AI system rather than a single model: the model or models plus the application layer of prompts, retrieval, filters, human oversight, and deployment context. It documents what the deployed system actually does, which is a narrower and different thing from what the underlying model can do.
Defined in 2 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.
A document describing a deployed AI system rather than a single model: the model or models plus the application layer of prompts, retrieval, filters, human oversight, and deployment context. It documents what the deployed system actually does, which is a narrower and different thing from what the underlying model can do.
A structured document published by an AI developer describing a specific model's intended use, known limitations, and evaluation results, one of the primary sources this topic's Section 3D and Section 3E rely on for traceable, checkable claims.
A document describing a deployed system built around one or more models, including guardrails, filters, human-oversight steps, and residual risks after mitigation. Where a model card describes the model, a system card describes the product a user actually touches. (see Topic 10.3)
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Model cards and system cards for your own systems, written so an outsider could act on them · Evidence Engineering, Certified AI Governance Professional (CAIGP)
- Reading the primary source: a model card, a system card, and what they do not say · Staying Current: The Frontier Discipline, Certified AI Governance Professional (CAIGP)
- Holding the Room with Engineers: The Technical Credibility Defense · Technical Credibility Deep Dive, The AI Lobbyist: Certified AI Policy Strategist
Where it shows up at work
A definition is where System card 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.
Explains training, tokens, context windows, embeddings, retrieval and fine-tuning well enough to ask an engineer a precise question and spot weak evidence.
One lesson on this page teach it as a primary outcome.
Reads and applies content provenance infrastructure: C2PA content credentials, watermarking, machine readable AI labels, and the transparency duties that now require them.
One lesson on this page teach it as a primary outcome.
Reads bills and rules like a practitioner, compares options with costs and unintended effects, and writes briefs a decision-maker can act on.
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.
- Chief Technology Officer, AI engineering editionneeds it at depth
- AI Security Architectneeds it at depth · 8 open postings this week
- AI Evaluation Specialistneeds it at depth · 6 open postings this week
- AI Governance Engineerneeds it at depth · 7 open postings this week
- AI Model Validatorneeds it at depth
- AI Policy Analystneeds it at depth · 7 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 50; C2PA Content Credentials; California SB 942.
One interview question about it
Explain how a large language model produces an answer, at the depth a governance decision needs and no deeper.
Asked of candidates for how models work, at a governance depth. 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.
- Data analysis, stewardship and business intelligence carries it as a claim to back up: SQL and analytical fluency make the technical layer approachable.
- Model risk, credit risk and quantitative analysis carries it as work you can show: Quantitative fluency is demonstrated in your work.
- A computer science or software engineering degree carries it as work you can show: You have trained or integrated a model in coursework or a project.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.