Former Dell executive launches healthcare AI startup to fix how enterprises deploy AI—most bolt it onto broken processes instead of redesigning them.

What happened: The author, an 11-year Dell veteran, left enterprise technology to start a healthcare AI company after observing that MIT researchers found 95% of enterprise generative AI pilots produced no measurable return. The core insight: organizations were bolting AI onto existing workflows without rethinking those processes.

Why it matters: Healthcare exposes the problem fastest because stakes are high—a slow drug approval decision costs health plans $4–7 million in unnecessary hospitalizations, and prior authorization consumes an average of 13 hours of physician and staff time every week while delaying patient care. Gartner predicts more than 40% of agentic AI projects will be canceled by the end of 2027, citing inadequate risk controls and unclear value as primary causes. The same pattern—automation without redesign—is now spreading across finance, insurance, energy, and government.

What to watch: The company demonstrated a drug approval assessment that normally takes six or seven specialists working over 60 to 90 days at roughly $100,000 per drug can be completed in four to eight hours with coordinated AI, cutting direct labor cost by 97% and preserving full audit trails. A large pharmacy benefit manager runs 200 to 300 of these assessments yearly, making the workflow redesign economically material.