Expected value
The probability-weighted sum of the three scenario outcomes: (P-conservative x Value-conservative) + (P-moderate x Value-moderate) + (P-aggressive x Value-aggressive). A single summary number that respects the uncertainty; healthy cases have an expected value near the moderate scenario rather than propped up by the aggressive tail.
Defined in 3 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in Certified AI Transformation Professional (CATP).
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 probability-weighted sum of the three scenario outcomes: (P-conservative x Value-conservative) + (P-moderate x Value-moderate) + (P-aggressive x Value-aggressive). A single summary number that respects the uncertainty; healthy cases have an expected value near the moderate scenario rather than propped up by the aggressive tail.
The sum of each possible outcome multiplied by its probability. Meaningful as a description of what happens to you only over enough repetitions for the average to be collected, which is why a ruin outcome cannot be included in one.
Probability times severity, summed across scenarios; the correct method for representing low-frequency, high-severity tail costs without overstating the typical case.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Workslop Cost Quantification: Hidden Productivity Losses · Bonus: AI Leadership Accelerator, Certified AI Practitioner: Workplace Foundations
- Value Creation and ROI Modeling: Your Three-Scenario Value Model · The Economics and the Business Case, Certified AI Transformation Professional (CATP)
- Mission, strategy, and risk-adjusted decision making · Enterprise Governance, Strategy, and Decision Rights, Certified Enterprise Governance, Risk and Compliance Professional (CEGP)
Where it shows up at work
A definition is where Expected value 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.