Happy path
The single most common route through a process, the clean sequence people picture when they describe it. On a real discovery map it is usually the central spine, and the diagnostic question is what share of cases actually follow it (a small share is a warning).
Defined in 2 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 single most common route through a process, the clean sequence people picture when they describe it. On a real discovery map it is usually the central spine, and the diagnostic question is what share of cases actually follow it (a small share is a warning).
The input or scenario a system handles well, which a demo is built around. Real use includes the unhappy paths (rare, messy, adversarial inputs) that a demo avoids and an evaluation deliberately seeks out.
The normal, everything-goes-right route through a process. Easy to describe and easy for AI to handle, and almost never where automation projects fail; the failures live in the exceptions, variations, and edge cases outside it.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Distrust is a skill: why demos convince and evals do not lie · Evaluation and Trust, Certified AI Governance Professional (CAIGP)
- Current-State Process Mining · Diagnose the Organization, Certified AI Transformation Professional (CATP)
- Process Discovery and Documentation · Process and Operations Redesign, Certified AI Transformation Professional (CATP)
Where it shows up at work
A definition is where Happy path 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.
Knows why rollouts stall, separates a skills problem from a trust problem, builds champion networks, and measures adoption honestly.
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.
- AI Adoption and Enablement Leadneeds it at depth
- Operations Manager, AI-readyneeds working knowledge
- Chief AI Officerneeds it at depth
- Chief Information Officer, technology leadership editionneeds working knowledge
- AI Program Managerneeds working knowledge · 11 open postings this week
- Data Governance Leadneeds working knowledge · 2 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 do you get a team that fears an AI tool to use it well, and how do you know adoption is real and not reported?
Asked of candidates for adoption and change management. 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.
- Human resources and people operations carries it as a claim to back up: Change programs run through HR.
- Project and program management carries it as a claim to back up: Rollout and adoption planning are usually included.
- A business, MBA or technology management degree carries it as a claim to back up: Change management was taught in cases, not yet led.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.