Ankur Jain | Founder
Artha Consulting Lab

Ankur Jain is the founder of Artha Consulting Lab, an independent advisory practice focused on how healthcare organizations actually adopt artificial intelligence. He is the author of the AI Readiness Continuum (ARC), a vendor-neutral framework for healthcare AI adoption, and the host of The Hub Brief. With more than fifteen years across biopharma, specialty pharmacy and patient services, he works on the part of healthcare AI that decides whether a deployment survives contact with the people who run the work. Most of that experience sits inside hub services, the patient-support operation that stands between a prescription and a first dose. He has worked across the full span of it: enrollment and intake, benefits verification, prior authorization and appeals, copay, patient assistance and alternative funding, field reimbursement coordination, specialty dispensing and REMS-governed therapies, site-of-care and infusion scheduling, and adherence and refill management. He has operated inside every structural model the industry uses to deliver that support, from fully outsourced hubs to hybrid and manufacturer-internal builds and lighter digital front doors, and he has designed the case-management and patient-access platforms those operations run on. His argument about hub operations comes out of that span. The technology gap in patient support closed years ago, and a governance and ownership gap opened in its place. A single patient's path to therapy can run more than twenty steps and more than a dozen handoffs across systems that hold no shared record of who that patient is, and the delay accumulating in those seams is invisible to every dashboard that measures one function at a time.  The Hub Brief platform (Podcasts and Newsletter) brings biopharma, payer, provider and technology leaders into that cross-stakeholder conversation, and his long-form series takes up the governance question the market has been slow to ask. Controls for the model are now standard. His concern is the human reviewing the model's output, and what happens over time to a reviewer who stops disagreeing with it. He is a New York-admitted attorney, non-practicing, and holds an MBA and an LL.B. He speaks to healthcare executives who have heard the AI keynote and want an operating answer instead. He applies a single test to any healthcare AI deployment: did the patient wait less.