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
Nine decisions plus optional docs get you an AI-readiness report. Each answer gives you a practical signal on the way.
Use case
Pick the closest workflow. This gives the report both the business job and the likely AI pattern.
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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