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Systemic risk

A risk specific to the high-impact capabilities of general-purpose AI models, having a significant impact on the Union market due to their reach, or due to actual or reasonably foreseeable negative effects on public health, safety, public security, fundamental rights, or society as a whole, that can propagate at scale across the value chain (Article 3(65), Regulation (EU) 2024/1689).

Defined in 3 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in EU AI Act Implementation Expert.

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.

EU AI Act Implementation Expert

A risk specific to the high-impact capabilities of general-purpose AI models, having a significant impact on the Union market due to their reach, or due to actual or reasonably foreseeable negative effects on public health, safety, public security, fundamental rights, or society as a whole, that can propagate at scale across the value chain (Article 3(65), Regulation (EU) 2024/1689).

Certified AI Governance Professional (CAIGP)

A larger, related fear than aggregation: aggregation describes many similar claims from one shared cause, while systemic risk describes those claims cascading into market-wide instability and drawing coordinated regulatory intervention across a sector. It is the version of correlated AI risk that can make a peril effectively uninsurable rather than merely expensive.

The AI Lobbyist: Certified AI Policy Strategist

the EU AI Act's classification for the most capable general-purpose AI models, triggering the highest tier of GPAI obligations, including mandatory model evaluation and incident reporting, on top of the baseline GPAI transparency duties.

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 Systemic risk 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.

Reviews purpose, data, affected people, accuracy, bias, security, oversight, vendors and law for a use case, scores likelihood and impact, and documents residual risk.

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

Keeps the living record: each risk with a named owner, rating, treatment, residual risk, monitoring metric, threshold and review date.

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.

“risk assessment”“impact assessment”“algorithmic impact”“fundamental rights impact”“risk classification”“risk tiering”

Where the frameworks place it: NIST AI RMF MAP and MEASURE; ISO/IEC 42005; EU AI Act Article 27; NIST AI RMF MANAGE.

One interview question about it

Take me through an AI risk and impact assessment you would run for a hiring tool. What do you assess, and who signs?

Asked of candidates for ai risk and impact assessment. 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.