Workflow fit
Is there a repeated, valuable workflow where AI has a real job to do?
AI workflow readiness check
Answer a short diagnostic and see whether one of your workflows is ready for an AI prototype, needs cleanup first, or should start with simpler automation.
A business is ready for AI when at least one real workflow has clear inputs, repeated work, human ownership, measurable risk, and a review path. This check turns that into a practical readiness read.
Start the check
Eleven answers plus optional docs get you an AI-readiness report with matched real-world AI patterns.
Workflow
Pick the closest shape. The result is about workflow readiness, not whether AI is fashionable.
The scoring is based on practical AI adoption patterns: useful AI starts with a repeated workflow, reachable inputs, clear failure cost, human review, and an owner who can test it.
Is there a repeated, valuable workflow where AI has a real job to do?
Can the team explain the current steps and exceptions before automating them?
Are the inputs accessible, permissioned, and reliable enough for a prototype?
What happens if AI is wrong, and which guardrails need to exist first?
Who reviews outputs, approves actions, and owns the final decision?
Is there a decision owner, feedback loop, timeline, and appetite to iterate?
Built from practical AI readiness signals
The model reflects the same themes that show up across enterprise AI adoption and AI-risk guidance: map the workflow, govern sensitive data, measure failure modes, keep humans accountable, and prototype before platform spend. The example matches use a curated source set from Google Cloud real-world gen AI use cases.
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