Risk tiering
The practice of scoring every distinct task type an agent performs against a fixed set of questions, severity of impact, reversibility, and feasibility of human oversight in the Dayos method, and grouping task types with similar scores into named tiers, each carrying a defined reasoning strategy and autonomy decision.
Defined in 4 GAGE programs, which carry 4 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 practice of scoring every distinct task type an agent performs against a fixed set of questions, severity of impact, reversibility, and feasibility of human oversight in the Dayos method, and grouping task types with similar scores into named tiers, each carrying a defined reasoning strategy and autonomy decision.
Sorting an agent's task types by severity of impact and reversibility of action, then assigning each tier a matching level of autonomy (full automation, automation with mandatory human sign-off, or no autonomous execution at all). Dayos's published case study is the framework's worked model of this practice.
Sorting work into levels (for example low, standard, high) by the consequence of an error, and attaching the appropriate review to each tier, with explicit triggers that let members self-sort.
Sorting AI systems into risk categories (for example, the EU's unacceptable / high-risk / limited-risk / minimal-risk) so obligations scale with risk. The first question of the regime reader.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Setting AI Usage Expectations Within Teams · AI in the Workplace and Team Leadership, Certified AI Practitioner: Workplace Foundations
- Risk Tiering in Practice · Capability and Autonomy, Certified Agentic AI Governance Professional (CAAGP)
- The Singapore stack: voluntary on paper, adopted in practice · The World's Rulebooks, Certified AI Governance Professional (CAIGP)
- Transforming Across the Regulatory Map · Lab: Regional and Geopolitical AI, Certified AI Transformation Professional (CATP)
Where it shows up at work
A definition is where Risk tiering 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.
Sets expectations for AI use on a team, reviews AI-assisted work, delegates to agents deliberately and keeps accountability with people.
One lesson on this page teach it as a primary outcome.
Classifies models by tier, sets validation requirements, challenges data, methodology and performance evidence, and reports aggregate exposure.
One lesson on this page teach it as a primary outcome.
Briefs a model like a good manager: context, constraints, examples, verification, and knows when to stop delegating.
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.
- Operations Manager, AI-readyneeds it at depth
- AI Adoption and Enablement Leadneeds working knowledge
- VP of AI Governance and Ethicsneeds working knowledge
- Model Risk Managerneeds it at depth
- AI Model Validatorneeds it at depth
- Chief Audit Executive, AI audit 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: SR 11-7; NIST AI RMF MEASURE.
One interview question about it
How do you lead a team that uses AI daily, and what do you hold people accountable for that the tool cannot be?
Asked of candidates for leading a team that works with ai. 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: Team leads and supervisors already manage reviewed work.
- Model risk, credit risk and quantitative analysis carries it as work you can show: Validation reports and model inventories are your record.
- A computer science or software engineering degree carries it as work you can show: Prompting and tool workflows are already in your daily work.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.