About 35 questions, written for your kind of healthcare organization. ARC reads your data, your change management and your AI governance, sets your stage by the weakest of the three, and gives you three decisions and a 30, 60 and 90 day plan.
The ARC framework
Free · about 35 questions · scored in your browser · self-reported
ARC, the AI Readiness Continuum framework by Ankur Jain, reads an organization on three pillars and places it on one of five stages.
Where your data lives, how many systems one request touches, who owns what counts as accurate, and what keeps it current once a tool is live.
Whose judgment the tool takes over, who’s accountable for adoption, how concerns raised during evaluation get written down, and what happens the first time the tool is wrong.
Who reviews AI and how often, whether a person can stop a tool before its output is used, what gets logged, and how your setting’s own rules apply.
Each pillar is scored on its own, and your overall stage comes from the lowest of the three rather than the average. A 4 on data and a 2 on change management reads as a 2, because a deployment fails through its weakest part. The report says which pillar set your stage and shows the answers behind it.
Your free result is marked self-reported, and the evidence and limits page says what ARC can and can’t conclude from your answers.
In your organization’s own language.
Data, Change Management and AI Governance, each on its own.
No averaging. The lowest pillar decides.
One of five, read from that pillar.
The stage, the area to strengthen first, three decisions and a 30, 60 and 90 day plan.
Built to absorb the next model as well as this one.
Data, people, and rules working as one system.
Real plans, real owners, early discipline.
Pockets of progress, nothing connected.
Every team solving AI on its own.
The scale is a reference. It isn’t a safety rating or permission to expand AI.
Score a 4 on data and a 2 on change,
and you’re a 2.
The deployment that fails will fail through the 2.
The same three pillars and five stages, asked in the language of your setting. The actions in your plan come from the ARC content pack for your type, so a hospital’s first move won’t read like a pharmacy’s.
Don’t see yours? Talk to us about the guided assessment.
The report opens the moment you finish. Each page names the answers that drove it, and every pillar has a “Show supporting evidence” link.
The first area to strengthen in one sentence, the answers that put it there, and three decisions required.
Your stage on the ARC scale, each pillar’s score, and which pillar set the overall result.
What each pillar means for day-to-day work, and what would show each action is done.
The tools you listed, live or planned, placed against your setting’s workflows, with the approval, monitoring and independent-check records each one still lacks.
Proposed actions by phase, each with an owner, date, evidence to produce and completion status, all marked proposed until you confirm them.
What ARC can conclude from your answers, what it can’t, and whether anything is unresolved.
One job only. If you agree, an AI model may choose and reorder the items under “Where to look first.” Every item is reviewed wording built from your answers by fixed rules. Your scores, notes, goals, name and email are never sent to the AI service.
The free check tells you where to look. The guided assessment works out what to do about it, with the people who’ll do it.
ARC, the AI Readiness Continuum, is the framework of Ankur Jain, Esq., founder of Artha Consulting Lab, built after fifteen years inside biopharma, pharma and health-system work. The free check runs the same questions we use in paid engagements.
It isn’t a certification, a vendor recommendation, a legal opinion or an implementation plan. Your free result is self-reported and marked that way. A higher stage means fewer things in your way, and the report names the ones left.
Whoever owns the AI question: strategy, operations, informatics or quality. It’s built for one respondent. “Not sure” and “belongs to someone else” are real answers, and the report treats them as findings.
Enough to know where to look. The questions are written for your type of organization and the result is set by your weakest pillar, so they’re built to find the constraint. One respondent can’t cross-check their view against the rest of the team. The guided assessment adds that.
They’re scored in your browser and they produce your report. There’s no public benchmark, directory or sharing. The questions are about your organization, so no patient data is involved. If you turn on the optional AI ordering, your scores, notes, goals, name and email are never sent to it.
No. A higher stage means fewer things in your way, and the report names the ones left. The ARC scale is a reference. It isn’t a safety rating or permission to expand AI.
It’s a useful time to take it. The AI tools page reads what’s live and what’s planned, and mid-deployment is when the weakest pillar starts to show.
Written for your kind of organization, scored in your browser and marked for what it is.
Readiness asks whether you can start. The AI Governance self-check asks 37 questions on how your AI tools are approved, checked, stopped and explained, with answers linked to the published AIUC-1 requirements. Free, and no score. AIUC-1 is named only to identify the standard. Artha Consulting Lab is not affiliated with or endorsed by the Artificial Intelligence Underwriting Company. Only AIUC issues AIUC-1 certificates.
Thirty minutes, on your calendar, no forms in between.
Prefer email? ankur.jain@arthaconsultinglab.com