The real test for AI in healthcare is making care more human

In 1991, Mark Weiser, the then head of Xerox PARC said that the most profound technologies are those that disappear.

“They weave themselves into the fabric of everyday life until they are indistinguishable from it,” Weiser wrote.

Today, that assertion feels more relevant – and more aspirational – than ever, particularly in the global healthcare market.

The healthcare AI market is on track to reach $491 billion by 2032, growing at a compound annual rate of 43%. New tools are launching faster than health systems can evaluate them, and the promise is genuine. But when technology is deployed without a guiding purpose, efficiency quietly overtakes empathy.

Too often, the rush is less about delivering better care than about competitive pressure, fear of being left behind, or the allure of a near-term return. But the leaders who will shape a responsible future for healthcare AI won't be the ones who rush to bring technology to market. They'll be the ones who pause to ask whether AI is truly delivering value – and not just the appearance of it. The ones who ask: Does this make the healthcare experience more human?

The pattern is familiar: a new technology arrives, the instinct is to optimize for what's measurable while harder to quantify metrics fall by the wayside. In healthcare, that often includes relationships, continuity of care and trust. Patients experience this in real-time: chat-only front doors replacing relationship-based intake, patients at their most vulnerable routed through impersonal workflows and forced to retell their stories.

Trust – healthcare's most precious currency – erodes at every step.

Healthcare has been here before. The Electronic Health Record wave arrived with extraordinary promise but made things worse on the dimensions that mattered most, with studies showing that physicians now spend nearly twice as much time on EHR tasks as they spend on patient care. The lesson isn't that the technology was inherently bad. It's that deploying powerful tools without a grounding human purpose generates unintended consequences – and that in healthcare, there are no quick fixes.

So how in this AI age do we avoid repeating the mistakes of the past: deploying powerful technology in pursuit of the wrong goals, over-rotating on the promise of a magical fix and wondering later why the outcomes don't match the promise? Across the industry some clear principles are emerging.

The highest-value AI applications in healthcare target the rote, transactional work that was never directly serving patients or providers: authorizations, lab orders, scheduling logistics. Tasks that require speed and accuracy, not the human touch.

Every administrative burden lifted from a care team is attention and presence returned to the patient. AI that filters the noise of healthcare operations creates more space for listening, empathy and human connection.

What does this look like in practice? At Foodsmart, a foodcare platform, AI clears everything that gets in the way of the member relationship – the prep, the administrative load – so dietitians can focus their energy on empathy and expertise, not paperwork. The result isn't fewer humans in the loop; it's dietitians with more time to hear a patient's full story, understand their barriers to behavior change and deliver guidance that fits their life. Foodsmart’s goal isn't to automate the dietitian out of the equation, but to give them their full attention back.

Healthcare already generates nearly a third of all the world's data, and that volume is growing at 63% annually. Making that data useful in the moment by surfacing the right information, for the right person, at the right time is the crucial challenge. AI is uniquely positioned to solve this.

When it works well, AI surfaces a patient's full context before a conversation begins – ensuring that the care team member starts informed. This matters especially in health journeys that are longitudinal rather than episodic, where each interaction is one chapter in a longer story.

Fertility care is a clear example. These patients are not moving through isolated transactions – they are navigating complex, multi-step journeys that cross life stages. AI-generated summaries of prior interactions give care advocates a deeper understanding of what happened in previous conversations, so each successive touchpoint builds on the last rather than resetting. The next call is smarter. The care gets more personal over time.

That continuity changes what's possible in a single moment. When a member indicates she has experienced a failed cycle, her advocate already understands her journey – the prior treatments, the emotional weight she's been carrying, what she needs right now. She doesn't have to retell her story. The conversation can begin where it should: with empathy, not discovery.

When the purpose is clear and the technology is genuinely in service of it, something else becomes possible – something AI is uniquely suited to deliver, with the right human hand at the till: a system that learns how to do better over time.

Every interaction generates a signal: what a patient needed, where the care fell short or exceeded expectations. AI that can capture and iterate on those signals over time and at scale doesn't just improve efficiency; it builds a progressively deeper understanding of individual patients and aggregate populations.

Unlike quality assurance of the past, this isn't about measuring quality after the fact and selectively – it's about designing forward-looking systems that learn from every interaction to strengthen human connection and improve outcomes over time.

Healthcare leaders from every sector are being asked to place significant bets on AI right now. But the most important measure of success won't be deployment speed or automation rates. It will be whether patients feel more understood, more supported and more connected to their care.

By making the technology disappear into the experience, just as Mark Weiser envisioned, the healthcare sector can make room for the human relationships that are the foundation of good health outcomes.