Sensitivity analysis
Recomputing a projected return under stressed assumptions (for AI, typically double cost, half adoption, two-thirds benefit) to produce a defensible range and a stated breakeven, rather than a fragile point estimate.
Defined in 3 GAGE programs, which carry 4 distinct definitions of it. The wording above is taught in AI Literacy & Professional Conduct.
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 testing how a calculation's outcome changes when its key uncertain assumptions are varied, typically presented as a pessimistic, base case, and optimistic scenario. Produces a defensible range instead of a single fragile point estimate.
Recomputing a projected return under stressed assumptions (for AI, typically double cost, half adoption, two-thirds benefit) to produce a defensible range and a stated breakeven, rather than a fragile point estimate.
Varying a key assumption (usually AI accuracy) to find the break-even point below which an automation loses money or trust. It answers "how good does the AI have to be for this to be worth it?" before any spend.
Varying one input at a time to find which assumption moves the answer most, revealing where to focus measurement effort and which number a skeptic is most likely to attack.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- ROI Calculation Tools and Templates · AI in the Workplace and Team Leadership, AI Literacy & Professional Conduct
- AI Investment Analysis and ROI Measurement · Bonus: AI Leadership Accelerator, AI Literacy & Professional Conduct
- Current-State Process Mining · Diagnose the Organization, Business AI Transformation
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.