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MIT research shows 95% of enterprise AI pilots fail, not from weak technology, but from a lack of trust. Babylon Health’s $4.2B collapse proves that trustworthiness is the missing metric for adoption, ROI, and long-term growth.

Trust has always been the foundation of health care, determining whether patients seek care, follow treatment, or participate in research. As AI enters the system, the same truth applies: without trust, even the most advanced tools will fail. Building trust means more than technical accuracy; it demands transparency, rigorous validation, stakeholder collaboration, and a clear commitment to augmenting, not replacing, the human workforce.

As AI transforms health care, trust is the deciding factor. Patients like Maria, already carrying fears, may feel alienated when technology replaces empathy. Studies show many worry AI will erode compassion, yet trust grows when doctors are directly involved in its use and development. Building AI with patients and clinicians through transparency, privacy safeguards, and shared responsibility is essential to unlock its true potential.

AI’s potential in medicine is enormous, but without trust, it risks deepening the divide between technology and the people it is meant to...

"As we focus on building clinically sound AI, we risk eroding the very foundation of medicine—the patient-physician relationship"

Achieving equity in health AI can be effectively navigated through the 3 D’s: Data, Design, and Deployment.