A two-minute self-check
Twelve sentences. Tick the ones you have actually said.
Adoption problems announce themselves in plain language long before they show up in a usage report. Each sentence below belongs to one of the twelve domains of the AI Adoption Gap Diagnostic™. Whichever pillar collects the most ticks is the one holding you back.
Why a readiness score will not tell you what to do
A score compresses four unrelated problems into one number. A company stalled because its managers cannot translate the direction, and a company stalled because nobody checks output before it reaches a customer, can land on the same score and need opposite interventions.
Location beats magnitude. The useful question is not how ready you are out of a hundred. It is which pillar is under strain, because that is the one that decides what happens on Monday.
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The twelve sentences
Tick honestly rather than generously. A sentence counts if you have said it out loud, thought it in a meeting, or heard it from someone who reports to you.
What each pillar means when it is the one under strain
P · People
Sentences one through three. The constraint is human, and it sits above the workforce rather than inside it. People do not feel safe saying what is not working, or the leadership team privately treats this as a phase that will pass, or nobody has asked whether these executives and managers can run a company that operates this way. Nothing downstream holds until that changes, because a manager who is quietly unconvinced will teach their team to wait it out without ever saying so.
Start here: the leadership team, not the workforce. Ask each executive and manager what they think will still be true in three years, and listen for the ones describing today.
A · Adaptive Culture
Sentences four through six. The direction was announced and the organization did not move. This is the most commonly misdiagnosed pillar, because working around a change looks like resistance, and resistance gets treated with more communication. More communication does not change a reward system. If what gets someone promoted on Friday contradicts what was announced on Monday, the organization is behaving rationally.
Start here: write down what actually gets a person promoted, praised, or protected in your company. Put it beside what you announced. The gap is the work.
C · Capability
Sentences seven through nine. The tools arrived and the work did not change shape. Roles were never redrawn around what the software now does, or nobody can name who checks output before a customer sees it, or people are already pasting company information into tools that were never approved. Shadow AI is the one that surprises owners most, and it is happening whether or not a policy exists.
Start here: an amnesty, not a policy. Ask what people are already using, with no consequence attached to the answer. You cannot govern what you cannot see.
E · Evidence
Sentences ten through twelve. The work may be going fine and still not survive the next budget conversation. Clients are beginning to ask about AI in their questionnaires, the leadership team is pulling in different directions, and nobody can produce a number that shows a return. Evidence is the pillar that decides whether any of the other three get funded again.
Start here: one process. Measure it before, change it, measure it after. A single traceable number beats a dashboard nobody trusts.
AI moves at the speed of
the pillar with the most
resistance.
What to do with the answer
This page asks twelve questions of one person. The AI Adoption Gap Snapshot™ asks the same twelve domains of your organization, which is usually where the two answers stop matching. That difference is itself the finding.
If the pillar you landed on is already obvious to you and the real question is what to do about it, book a call instead. Thirty minutes, and you leave with the first two moves written down whether or not we work together again.
Twelve ticks will point at a pillar. They will not tell you which of the twelve domains inside it is carrying the strain, and they cannot tell you what your people would say if somebody outside the company asked them.
That is the difference between a signal and a measurement. The full diagnostic counts it across all four pillars, and the number is one you can re-run later to see whether anything moved.
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You know which pillar is under strain now. Every week or two I publish one piece on what actually moves each of them, built from the research and from what shows up inside real leadership teams.
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Frequently asked questions
How do I know if my AI rollout is failing?
Listen for the sentence rather than the metric. Adoption problems show up in ordinary language before they show up in usage data, and the sentence tells you where the problem lives. “My team won’t get on board” and “I can’t show the board a return” are both failure, and they need opposite work.
Why does an AI adoption score not help?
Because it compresses four unrelated problems into one number. Two companies can post the same score and need entirely different interventions. Location is more useful than magnitude.
Is shadow AI one of the twelve sentences?
Yes, and it is the most common Capability finding: employees using AI tools the organization never approved, usually with company information pasted into them. It exists whether or not there is a policy. The first move is an amnesty rather than a rule, because governance cannot cover what leadership cannot see. The fuller answer on shadow AI, and who should own it, is here.
Who is behind this?
Accorda Advisory LLC, Camas, WA. Lesley Bodine has spent 15+ years in organizational and leadership development, building programs from the ground up, developing managers across distributed and multi-site organizations, and advising alongside CEOs, COOs, and sales leaders. She is certified in AI leadership and cultural adoption, and trained as a neurolinguistic coach, which is where the resistance work comes from.
She is not from human resources, and says so on the record rather than letting people assume. HR owns policy and people processes. This work is about the operating logic of how decisions get made, which does not sit cleanly inside any one function. The full background, including what she is not trained in.