Trust boundary
The point at which one organisation's agent identity infrastructure stops being able to directly verify a claim and must instead rely on an external mechanism, such as a decentralised identifier or a trusted agent registry, to confirm who or what it is dealing with. Identity design gets materially harder at every trust boundary an agent crosses.
Defined in 3 GAGE programs, which carry 6 distinct definitions of it. The wording above is taught in Certified Agentic AI Governance Professional (CAAGP).
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 one-page artifact this topic produces for an AI system. It is an explicit, decision-by-decision line marking each decision "the system may decide and act alone," "a human must sign before it takes effect," or "do not ship," with every human-signs decision naming who signs and the conditions that make the signature real. It is one of the three artifacts Module 4 hands forward.
A point in an estate where an agent's action crosses from a system, team, or organization it is native to into one it is not, such as an agent acting on a different team's database or a partner organization's data feed. Actions crossing a trust boundary warrant full four-field logging under this topic's tiering guidance, regardless of how routine the action might otherwise seem.
The point at which one organisation's agent identity infrastructure stops being able to directly verify a claim and must instead rely on an external mechanism, such as a decentralised identifier or a trusted agent registry, to confirm who or what it is dealing with. Identity design gets materially harder at every trust boundary an agent crosses.
The line separating a system's owner or authenticated source from any other party or content source; a protocol that carries information across a trust boundary without marking which side it came from cannot support a downstream decision about how much to trust that information.
The line separating what a claim about a system is supported by verified evidence versus what it is supported by only where the system sits, who can reach it, or how long it has operated without incident. Mapping this boundary explicitly, for any node, is the practical mechanics behind the evidence-versus-position test.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- The Parts That Make an Agent Act · The Agent, Deconstructed, Certified Agentic AI Governance Professional (CAAGP)
- Agent Identity · Bounding by Design, Certified Agentic AI Governance Professional (CAAGP)
- The agent's trail: who acted, on whose authority, using what, and why, recorded for every autonomous touch of your estate · Access and the Keys, Certified AI Data Governance Professional (CADGP)
- Your lineage map under attack: the red team finds the gap you papered over · Adversarial Data Governance, Certified AI Data Governance Professional (CADGP)
- Red-teaming your own system: attacks a motivated user will find · Evaluation and Trust, Certified AI Governance Professional (CAIGP)
- The trust boundary: what this system may decide alone and where a human signs · Evaluation and Trust, Certified AI Governance Professional (CAIGP)
Where it shows up at work
A definition is where Trust boundary 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.
Defines who reviews AI outputs, what they check, when they can override, and how to keep review from becoming a rubber stamp.
One lesson on this page teach it as a primary outcome.
Decides what a person affected by an AI decision must be told, how an output can be explained, and how they can challenge it.
One lesson on this page teach it as a primary outcome.
Knows when to trust, verify, escalate or override an AI recommendation, and stays accountable for the 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.
- AI Product Manager, responsible product editionneeds it at depth · 3 open postings this week
- Ethical AI Specialistneeds working knowledge · 5 open postings this week
- Responsible AI Leadneeds it at depth · 7 open postings this week
- AI Model Validatorneeds working knowledge
- VP of AI Governance and Ethicsneeds working knowledge
- Autonomous Systems Governance Lead, robotics and physical AI editionneeds 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: EU AI Act Article 14; ISO/IEC 42001 Annex A; EU AI Act Articles 13 and 50; NIST AI RMF trustworthiness characteristics.
One interview question about it
Design the human oversight for an AI system that approves refunds. What does the reviewer see, and what stops rubber-stamping?
Asked of candidates for human oversight design. 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.
- Operations, claims, customer service and administration carries it as a claim to back up: Deciding when to escalate a case is judgment under uncertainty.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.