We'd rather tell you you're not ready than watch you spend like you are.
A guided assessment of whether your organization is actually ready to put AI to work — run by us, with your leadership and the people who do the work. We examine five areas, rate each one on evidence we can show you, and hand you a verdict you can act on. Even if the verdict is wait.
A guided engagement · weeks, not quarters · your industry's language
Advisory firms. Financial services. Insurance. Legal. Logistics. Anywhere the thing you sell is expertise — because that's exactly what AI reaches for first. Our healthcare instruments have their own pages. This one is for everyone else: not a questionnaire about your organization — an examination of it.
The pattern we keep finding: the leadership team is enthusiastic, the tools are already half-bought, and somewhere below the org chart, someone has quietly built their own workaround because nobody asked them what they needed. Enthusiasm at the top, improvisation at the bottom, and nothing in the middle that says who is allowed to use what, on which data, with whose sign-off. That middle is what we assess.
The most expensive sentence in AI is "we're ready."
Self-assessments have a structural flaw: they can only read what you already believe. The file estate nobody has looked at in years, the knowledge that lives in one partner's head, the rule that exists in a policy document but not in anyone's behavior — none of that shows up when you grade your own homework. It shows up later, as the reason the deployment stalled. We go looking for it first, and when the evidence is thin, we say "not enough to go on" rather than inventing a rating.
A strength in one area can hide a failure in another until it's expensive. So nothing averages.
Who decides what AI gets to decide?
Not the policy PDF — the working reality. Who can approve a new AI tool, who can stop one, what data it may touch, and what happens the first time it's wrong. If the answer is "it depends who you ask," that's the finding.
Can your people find and trust what your firm already knows?
Every firm says its expertise is its edge. Fewer can retrieve it. We examine whether prior work is findable, whether people trust what they find, and whether the best of it lives in systems — or in the heads of the three people everyone asks.
Can the files you actually have carry AI?
Different question from knowledge: this is the estate itself. What exists, where it lives, how old it is, what's duplicated, what's sensitive, and what would happen if an AI tool could suddenly read all of it. We look at the real thing, not the system diagram.
Where does judgment actually live, day to day?
AI lands on specific work, done by specific people, in a specific order. We walk the workflows to find where automation would genuinely help, where it would quietly break things — and where your people have already built workarounds that tell you what they actually need.
Who wants this — and who would quietly kill it?
Adoption isn't a training problem; it's a trust problem. We map who's eager, who's skeptical for good reasons, and whose daily judgment the AI would absorb. High appetite with weak rules isn't readiness. It's exposure with momentum.
This is what makes the assessment different, so it's worth being specific about.
Behind each rating is a register of claims: who said it, what document or demonstration backs it, and how strongly it's corroborated. Each claim carries a consequence — what the report is allowed to conclude from it, and what it isn't. One person's opinion is recorded as one person's opinion.
Each question we ask must trace to a specific judgment it settles — which area it reads, what would move the rating, and who can actually answer it. A question that can't prove why it exists gets cut. That's why the interviews feel short and land deep.
Before a single interview, the question set is run against simulated respondents playing your roles — cold, with no knowledge of what we meant. Every hesitation or misreading is treated as a defect in the question, never in the respondent. Your people's time is too expensive for first drafts.
Every major conclusion is red-teamed before it reaches you: what would make this wrong, what evidence cuts against it, whose view we might be over-weighting. And when two of your leaders answer the same question differently, we don't average it — we flag it. That disagreement is usually the most useful thing we find.
The result: a leadership team that can interrogate the assessment — and watch it hold up.
An assessment that can't show its evidence
is an opinion with a cover page.
Ours shows who said it, what was demonstrated, and how strongly it's corroborated.
where you stand, and how we know ↓
All five areas, rated and traced. Verbatim voices from your own organization. The ranked list of AI opportunities that fit you — scored with risk and readiness weighted ahead of value, because that's the order reality enforces. Plus the working artifacts most firms need immediately: an interim AI-use policy and a vendor evaluation checklist, ready to adopt.
what to do, in what order ↓
A sequenced program, not a wishlist: what to fix first, what to pilot, what to defer — with decision gates that release the next phase only when the last one earned it. Costed, owned, and honest about what it excludes. It deliberately refuses to hide the hard decisions inside the appendix.
what leadership must decide ↓
A short deck built to be argued with — every slide title makes its case standing alone, and it ends in the explicit decisions your leadership has to make, each with an owner. No charts doing the arguing. No decision hiding in a footnote.
One rule across all three: no claim reaches the front of the room without evidence behind it.
Interviews across your leadership and the people who do the work — each answering only what they own. Under a confidentiality agreement before anything is discussed.
Documents, systems, and a read of the file estate you actually have — not the one the diagram describes. Nothing leaves your environment.
Five areas rated on the evidence, weakest first. Findings red-teamed against themselves before they're written down as findings.
The report, the roadmap, and the executive read — delivered and defended in the room. Your leadership decides with gates, not vibes.
In a recent engagement, the honest verdict was: ready for controlled AI adoption — not ready for AI search across its own files. The gate wasn't appetite. It was permission. That distinction saved the client from funding the wrong first project.
Our healthcare instruments start with a free self-check, because a leader can answer questions about their own organization. This assessment reads things a questionnaire can't reach — your documents, your systems, the disagreements between your leaders. Evidence doesn't self-serve. So the front door here is a conversation, and we'll tell you within one call whether the engagement is worth your money.
The ARC Adoption Assessment comes out of Artha Consulting Lab, built by Ankur Jain, Esq. — fifteen years inside healthcare and enterprise transformations, watching confident readiness claims fund failed deployments. The method was forged in live engagements: the evidence registers, the question discipline, and the three-document anatomy exist because a real leadership team once needed to interrogate every one of our findings — and could.
It's not a certification, and we won't call you "validated" — no honest assessment can. It's not a vendor recommendation, a legal opinion, a security audit, or an implementation project. And a strong rating is never permission to deploy — it means fewer things standing in your way, and the report names exactly which things remain.
Sometimes the verdict is "wait." When it is, the roadmap says what to fix before spending — which is cheaper than learning it from a stalled deployment. We don't sell the AI tools we'd be assessing, so we have no reason to inflate the answer.
It's built for exactly that case. The engagement is sized to your organization, the interviews are short by design, and the questions arrive already translated into your industry's language — deals, claims, matters, shipments — not ours.
A confidentiality agreement first. Then a handful of interviews with the people who own the answers, the documents that describe how you say you work, and read-only visibility into how you actually store what you know. No patient, customer, or deal data is ever needed to leave your environment.
Weeks, not quarters — typically four to six, depending on size. The pace is set by your calendar, not our process.
It stays yours. The engagement runs under a confidentiality agreement, findings are delivered to you alone, and anything we ever say publicly about our work is described by sector only — never named, never identifiable.
One conversation to find out if the assessment is worth your money. If it isn't, we'll say so on the call.
In healthcare? Start with the ARC Readiness Assessment or the ARC Governance Diagnostic →
Thirty minutes, on your calendar, no forms in between.
Prefer email? ankur.jain@arthaconsultinglab.com