12 questions. 5 minutes. A score from 0–100 across the four dimensions that predict whether an AI initiative succeeds or stalls.
Workflow · Data & Systems · Governance · People-Readiness
Progress
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01 of 04 — Workflow Leverage
Where AI could create the most time and money back.
We’re looking for high-volume, repetitive work that is currently draining your team and could be handled by a goal-driven agent.
Q1How clearly can your team identify the top workflows that consume the most manual time each week?
1Not at all
2Roughly
3Clearly
4Mapped & measured
No visibilityFully mapped
Q2What percentage of your team’s daily work involves answering the same questions or executing the same steps repeatedly?
1Under 20%
220–40%
340–60%
4Over 60%
Low repetitionHigh repetition
Q3Has your organization previously attempted to automate any of these workflows?
Yes — and it worked
Yes — it stalled
In progress
Not yet
02 of 04 — Data & Systems
Whether your data is where AI can actually reach it.
Agentic AI is only as capable as the data and systems it can access. This dimension is often the hidden blocker — organizations discover it too late.
Q4Do you know where your key operational data currently lives — and whether it’s accessible via API or integration?
1No idea
2Partially
3Most of it
4Fully mapped
UnknownFully mapped
Q5How clean and consistent is your operational data? (Duplicates, gaps, inconsistent formatting.)
1Messy
2Some issues
3Mostly clean
4Very clean
Needs workProduction-ready
Q6Does your organization operate under regulatory requirements governing data use? (HIPAA, SOC 2, FINRA, etc.)
Yes — actively managed
Yes — but loosely
No, but security matters
No requirements
03 of 04 — Governance
Whether your organization is set up to let AI act — safely.
Without governance, autonomous AI creates risk. With it, it creates leverage. This is the dimension that separates pilots from production systems that actually scale.
Q7Does your organization have a defined policy for how AI tools can be used internally?
1None
2Informal
3Written, not enforced
4Active policy
No guardrailsFully governed
Q8Is there a clear escalation path when an AI system encounters something outside its defined scope?
Yes — documented
Partly defined
No
Q9Who currently owns AI decisions in your organization?
1Nobody yet
2IT only
3IT & Ops
4Cross-functional team
UnownedAligned leadership
04 of 04 — People-Readiness
Whether your team will actually use what you deploy.
This is the dimension that kills 70% of AI initiatives — after the technology is already live. Most organizations skip it entirely and wonder why adoption disappoints.
Q10How would you describe your team’s current sentiment toward AI adoption?
1Resistant
2Cautious
3Open
4Pushing for it
ResistantChampions
Q11Has your organization clearly communicated to staff what AI will and won’t change about their roles?
1Not at all
2Minimal
3Some comms
4Clear & documented
No commsFully communicated
Q12Does your organization measure adoption after a technology rollout — beyond just “did we train everyone?”
Yes — tracked with metrics
Informally
No
Almost there
Get your full readiness report.
Enter your details below and we’ll calculate your score across all four dimensions — plus one specific action for each area.
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Your Readiness Report — AI Change Agency
Here’s where you stand.
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Overall Readiness Score
Workflow Leverage
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Data & Systems
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Governance
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People-Readiness
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