Risk cost
The cost of the harm a system can do, read through named scenarios (a typical case and a specific worst case) rather than a single averaged expected value, because AI risk is usually tail shaped and an average washes out the rare severe failure that matters most. The hardest cost to quantify and the most dangerous to ignore, because it is where a system with tidy operating numbers hides a catastrophic tail. (see Topic 8.4)
Defined in 2 GAGE programs, which carry 2 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.
The cost of the harm a system can do, read through named scenarios (a typical case and a specific worst case) rather than a single averaged expected value, because AI risk is usually tail shaped and an average washes out the rare severe failure that matters most. The hardest cost to quantify and the most dangerous to ignore, because it is where a system with tidy operating numbers hides a catastrophic tail. (see Topic 8.4)
The estimable cost of carrying a hazard today, including insurance premiums tied to a task's hazard class, expected injury-claim and lost-work-time cost based on incident history, and regulatory exposure. The relevant status quo cost category for safety-driven robot projects, discussed in Section 3G's Hard Case 1.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Build, buy, or kill: the quarterly portfolio review with real numbers · The Money: Budgets, ROI, and Risk, Certified AI Governance Professional (CAIGP)
- Scope a robot to a dollar-denominated problem, or do not build it · The Economics of Robots, the Business Case, Engineering Judgment and Professional Formation
Where it shows up at work
A definition is where Risk cost 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.
Builds an honest value model: baseline, measured change, cost, risk, and the projects that should be stopped.
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 AI Officerneeds it at depth
- AI Adoption and Enablement Leadneeds working knowledge
- AI Program Managerneeds working knowledge · 11 open postings this week
- Operations Manager, AI-readyneeds working knowledge
- Chief Information Officer, technology leadership editionneeds working knowledge
- AI Product Manager, responsible product editionneeds working knowledge · 3 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.
One interview question about it
How would you measure the return on an AI deployment honestly, including the costs people prefer to leave out?
Asked of candidates for roi and value measurement for 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.
- A business, MBA or technology management degree carries it as a claim to back up: Value and return measurement are a course you passed.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.