AI in Healthcare

57% of Health Executives Say AI Is Priority #1 — But 57% of Patients Still Do Not Trust It. That Gap Is the Real Story.

By BHC, Editor in Chief · March 31, 2026 · 5 min read

BHC, Editor in Chief — 57% of Health Executives Say AI Is Priority #1 — But 57% of Patients Still Do Not Trust It. That Gap Is the Real Story.

Summary

  • While 57% of healthcare executives rank AI as their top priority, 57% of patients say they do not trust AI enough for clinical use. This analysis unpacks the gap and what it means for Indian healthcare founders.

There is a number that has been circulating in global healthcare conversations this week — and it is the same number on both sides of the debate. According to Sage Growth Partners, 57% of healthcare executives have ranked AI-based clinical solutions as their top technology initiative for the next two years. According to a separate survey by Hyro and Pixel Health, 57% of patients believe that AI is not yet at the level where healthcare professionals should trust it. Two studies. Same number. Opposite conclusions.

"2026 will mark the turning point — healthcare leaders move from asking 'Could AI help?' to realising it already is, in dramatic ways."

This is not a statistical coincidence — it is a precise summary of where healthcare AI stands in 2026. The technology is advancing rapidly, enterprise adoption is accelerating, and the gap between what healthcare organisations are deploying and what patients are willing to accept has never been wider.

**What Healthcare Executives Are Doing With AI

The enterprise side of healthcare AI in 2026 is moving from experimentation to infrastructure. More than half of healthcare systems now report a return on investment of at least 2x on AI solutions, according to research from Eliciting Insights. AI is being deployed across clinical workflows — ambient scribing that captures consultation notes automatically, prior authorisation automation that reduces denial rates and administrative burden, AI-assisted chart review that moves from periodic sampling to continuous monitoring of every patient record.

BCG's global healthcare team describes this as the emergence of agentic AI — systems that can autonomously observe, plan, and act across complex healthcare workflows with minimal human oversight. Anurag Mehta, CEO and Co-Founder of Omega Healthcare, describes 2026 as the year AI transitions from a cost-cutting tool to a strategic driver of innovation — with the combination of AI and analytics empowering healthcare organisations to move from insight to foresight.

Managers are now spending significant time supervising AI agents alongside human staff. New practices are being built from scratch around AI — enabling patient panel sizes three to five times larger at equal or higher quality and lower cost. The infrastructure shift is real, measurable, and accelerating.

**Why Patients Remain Unconvinced

But patients, who ultimately bear the outcomes of these AI-driven decisions, are significantly more sceptical. The Hyro/Pixel Health survey is striking not because it shows patient resistance to technology in general — patients widely use health apps, telemedicine, and digital health tools — but because it shows specific scepticism about AI in clinical decision-making. Patients are asking: who is accountable when AI gets it wrong? Is the AI trained on data that represents people like me? Can my doctor override it?

These are not irrational concerns. Healthcare AI systems have produced well-documented cases of bias — models trained on predominantly Western, male, or higher-income patient populations that perform significantly worse for underrepresented groups. And the lack of transparent explainability in many AI clinical tools makes it difficult for patients to understand, let alone trust, the recommendations they receive.

**The Indian Context

For Indian healthcare founders and hospital operators, the global AI trust dynamic has specific local dimensions. India's patient population is extraordinarily diverse — across language, literacy, income, and prior healthcare experience. AI tools built and validated primarily on Western patient data may perform poorly or inequitably on Indian populations. And in a healthcare system where doctor-patient trust is often built on personal relationships and community reputation, introducing AI without a clear communication strategy risks undermining the very trust that makes care effective.

At the same time, India's healthcare workforce shortage creates a compelling case for AI adoption. More than half of healthcare systems globally report 2x ROI on AI solutions. In a resource-constrained system like India's — where doctor-to-patient ratios are far below global norms and administrative burden is enormous — AI that can automate documentation, triage, and follow-up has transformative potential.

**BHC Perspective

At Bengaluru Health Community, we believe the executive-patient trust gap is the most important strategic challenge in healthcare AI right now — and the biggest opportunity for founders who solve it well. The startups that will win in Indian healthcare AI are not those with the most sophisticated models. They are the ones that invest as seriously in patient trust-building, explainability, and cultural adaptation as they do in model performance. The gap between 57% and 57% is a product to be built.

**Frequently Asked Questions

Q: What percentage of healthcare executives prioritise AI?
A: 57% of healthcare executives rank AI-based clinical solutions as their top technology initiative for the next two years, according to Sage Growth Partners research.

Q: Why do patients not trust AI in healthcare?
A: 57% of patients believe AI is not mature enough for healthcare professionals to trust, citing concerns about accountability, bias, explainability, and whether AI systems are trained on data representative of their own populations.

Q: What is agentic AI in healthcare?
A: Agentic AI refers to AI systems that can autonomously observe, plan, and execute complex healthcare tasks — such as chart review, prior authorisation, and patient follow-up — with minimal human oversight.