What leaders need to decide
Teams often start with tools instead of decisions. This assessment keeps the focus on the operating conditions that make an AI initiative worth funding: a real workflow, an executive owner, a measurable outcome, data access, and a responsible way to operate the result.
AI readiness checklist
| Area | Question to answer | Evidence of readiness |
|---|---|---|
| Workflow | Is there a repeatable, high-friction decision or process? | A named workflow owner and a baseline for time, quality, cost, or risk. |
| Data | Can the team lawfully access sufficiently useful inputs? | Known systems, data boundaries, quality issues, and retention constraints. |
| Ownership | Who can make scope and operating decisions? | An executive sponsor and a day-to-day accountable owner. |
| Governance | What must remain under human review? | Clear approval, escalation, audit, and exception paths. |
| Delivery | Can a first implementation be measured and operated? | A bounded pilot, success criteria, and an owner after launch. |
A weak answer is not a reason to abandon AI. It is a dependency to resolve before committing to a production build.
A practical sequence
- 01
Choose one operating problem
Start with a workflow where delay, inconsistency, manual effort, or missed knowledge creates a measurable cost or risk.
- 02
Map the decision environment
Identify the systems, data inputs, handoffs, people, policies, and downstream consequences involved.
- 03
Decide the next smallest commitment
Select discovery, a roadmap, a technical audit, or a thin pilot based on the evidence, not enthusiasm.
Move from analysis to a 90-day plan
When your team needs a prioritized portfolio, architecture direction, governance boundaries, and a first pilot scope, the AI Opportunity & Execution Roadmap turns this framework into an implementation-linked engagement.
Explore the AI Opportunity & Execution RoadmapFrequently asked questions
How long does an AI readiness assessment take?
A focused assessment can be completed in a week when the workflow and stakeholders are available. Wider portfolio assessments need more discovery because the work is comparing opportunities, not simply scoring one idea.
Is readiness only about data quality?
No. Data is necessary but not sufficient. Ownership, operating constraints, human review, success measures, and delivery capacity determine whether a use case can become a responsible business capability.