The free AI readiness diagnostic
Most companies guess. drivechange.ai measures it: a free diagnostic instrument — a self-paced interview — that maps how your people actually use AI, benchmarks you against your industry, and turns the result into a ranked list of opportunities instead of a grade.
drivechange.ai · by AInvirion
The problem
"How ready are our people, actually?" Self-assessments say everyone is doing fine. Real behaviour says otherwise, and the gap between the two is where budgets get wasted.
Skills and institution get conflated. The most common finding in the field is skilled people inside an unprepared institution. It is also the most fixable one, if you can see it.
Reports without next steps. A maturity grade tells you a number. It doesn't tell you what to automate, who to train, or what policy is missing.
What the diagnostic measures
AI literacy isn't one number. Every person is located on a five-level maturity scale, profiled across five skill vectors, and the results are read at three organizational layers, so findings point at specific actions rather than vague averages.
Understands what AI is and how it works.
Sees what in their own work could be automated. This is where ROI comes from.
How often, and how substantively, AI shows up in real work.
Range of tools across categories, not one favourite.
Knowing when not to use AI: privacy, hallucination, verification.
The three layers
Each person's real understanding and behaviour with AI, measured through what they do rather than what they claim.
Whether skills spread or stay islands of excellence. Team views show the whole distribution, not just the average.
Governance, data readiness, infrastructure and funding: the institution that either enables people or holds them back.
"Skilled people, unprepared institution" is the single most common finding, and the most fixable. Seeing the layers side by side is what tells you where to invest first.
Methodology
This is a specialized quantitative analysis, not a questionnaire that counts and averages answers. The level model adapts Bloom's cognitive taxonomy and established technology-adoption research; behaviour is scored across five weighted vectors against role-specific baselines, then rolled up statistically from individual to team to organization.
No "rate your AI skill 1–5". Every question asks what you actually do, because people overrate themselves, and the gap is itself a finding.
An engineer and an operations manager are held to different expectations. Scores are read against role-specific baselines, never one bar for everyone.
The output is a ranked list of things worth automating, augmenting or training: capability gaps to close, not people to rank.
Grounded in published research the boardroom already trusts — the US Census, the Federal Reserve, McKinsey, BCG and Deloitte among them — and fully public: every level, rubric and aggregation rule is documented, justified, and illustrated with graded examples. Nothing about the score is a black box.
What you get
See at a glance whether your people or your institution is the constraint. That finding decides where to invest first.
Spot internal champions and quiet gaps, and see how you compare against the benchmark for your industry and size.
Concrete automation, augmentation, training and governance moves, scored by impact and feasibility, drawn from your own team's answers.
Re-run any time. Every engagement is versioned, so you can measure progress after each initiative and watch the trend move.
The AI-readiness quadrant
Anchored to published research. Sector by sector, from sources the boardroom already trusts: US Census, Federal Reserve, McKinsey, Deloitte, NVIDIA, Rockwell, AMA, Thomson Reuters, GAO and more. A bank compares against banking; a hospital against healthcare. We show where every number comes from.
It gets more real on its own. As more organizations complete the diagnostic, each industry's benchmark evolves from research-based to real anonymized peers, automatically. Every participant makes the comparison stronger for the next one.
Never exposes anyone. Peer data appears only in aggregate or as anonymized, offset points, never as a named company.
Your data stays yours
Individual, team and organization answers are encrypted per client, isolated and protected by design.
Benchmarks draw on published industry research and, as engagements accumulate, aggregated de-identified data. Never your individual answers.
Respondents join by your invite or link; you decide who sees dashboards and results. Benchmark participation is opt-out at any time.
How it works
Sign up free at drivechange.ai and set up your organization in minutes.
Email invites or a shareable link; everyone gets a role-appropriate questionnaire.
~30 minutes each. Behavioural questions, not a quiz. Nothing to study for.
Levels, layers, benchmarks and your ranked opportunity list, live on your dashboard.
Early access · founding participants
The offer. Run the diagnostic free with your organization or your clients. Full readiness picture, industry benchmark and opportunity report included, plus direct influence on where the product goes.
For partners and advisors. A ready-made door-opener: walk into AI conversations with data instead of opinions. Our diagnostic, your advisory work on top.
Why now. Every participating organization deepens the benchmark. When an industry reaches critical mass, its comparison becomes real peer data, and early participants are already on the map.
Not a beta. A founding position in the readiness benchmark for your industry.
Find out where you stand
When you're ready to move on the opportunities, the AInvirion team is behind the tool, with training, automation and AI governance engagements built directly on your results.
Start free at drivechange.ai →drivechange.ai · the free AI readiness diagnostic · by AInvirion · © 2026