Readiness is specific to an initiative: identify the missing condition that would stop this workflow from operating reliably.
Begin with a defined use case
An AI readiness assessment is more useful when it examines a specific workflow than when it produces a general enthusiasm score. Describe the task, its inputs, the people performing it, and the outcome you want to improve. Identify the consequence of an incorrect result.
Microsoft’s readiness assessment includes business strategy, governance and security, data, organizational culture, infrastructure, and model management. That breadth is a reminder to look beyond the model itself. The checklist below is our practical way to apply that thinking to a bounded initiative.
Check the data and access path
Identify the information the workflow needs, where it lives, and who owns it. Assess completeness, freshness, and the permission model. Ask how the system will handle a missing record, conflicting source, or change in access.
Do not assume that technical availability means approved use. Confirm the environment and information-handling expectations with the responsible owners. Readiness includes permission to perform the work as designed.
Check the system and review boundaries
Map the applications involved and the actions the AI-enabled workflow could take. Identify integration dependencies, logging needs, fallback behavior, and the human checkpoints. Decide where a suggestion ends and an operational action begins.
Test whether the team can evaluate the output. Build a set of representative cases and specify the acceptance criteria. Include examples where the correct behavior is to ask for clarification or decline to proceed.
Check ownership and adoption
Name the business owner, technical owner, and the people responsible for review. Confirm that users can explain how the workflow helps them and when they should intervene. Plan training around their real responsibilities.
Allocate time for evaluation, feedback, and maintenance. A pilot can stall when everyone supports the idea but nobody has capacity to operate it. Treat those constraints as part of the readiness result, not as issues to solve after launch.
Translate the assessment into a next decision
Classify the gaps by what must be resolved before testing, what can be learned during a bounded pilot, and what must be addressed before scaling. Give each action an owner and an evidence standard.
SolutionStream’s AI strategy work connects assessment to a Solution Map and an implementable next step. You should leave readiness work knowing what to do, who must act, and what would justify the next investment—not simply receiving a score.
Decision frameworks and recommendations are SolutionStream’s editorial perspective.
What single readiness gap would prevent your proposed pilot from becoming a dependable workflow?
