I keep seeing references to “the 4 stages of an AI workflow” without a clear consistent definition of what those stages actually are.
Different sources define them slightly differently and i can’t find anything that nails it down concisely. Curious if there’s a standard breakdown people in this space generally agree on, or if it’s just a loose framework that varies by who’s explaining it.
The framing also shifts depending on whether someone’s talking about a development lifecycle (build, test, deploy, monitor) versus an operational workflow (trigger, process, decide, act). Those are genuinely different 4-stage breakdowns answering different questions.
In practice for business automation specifically, the stages that matter most are trigger (what starts it), AI processing (the actual intelligent step), human review (if any), and output. That’s the version that’s actually useful for designing something rather than just describing one abstractly.
honestly i wouldn’t get too hung up on memorizing a specific 4-stage framework. understanding the general pattern (something triggers it, AI does a task, the result goes somewhere) matters more than which exact named stages a particular article uses.
There isn’t one single standardized definition, you’re right that it varies by source. The most common version I’ve seen breaks it into roughly: data/input gathering, processing (the AI step itself), decision or output generation, and action/delivery.
For client presentations I use trigger, process, decide, deliver, mostly because it’s easy to explain to non-technical stakeholders. The specific labels matter less than having a consistent mental model you can apply to whatever you’re building.