Healthcare Leaders Are Not 'Behind' on AI—They're Just Starting Out

Why the AI Hype Isn't Equal to Impact

As artificial intelligence continues to dominate headlines, one refrain keeps echoing across healthcare executive suites: "We're behind." But in a recent conversation with Newsweek, Dan Shoenthal, chief innovation officer at MD Anderson Cancer Center, challenged that narrative head-on. "A lot of providers feel like they're behind," he told us. "I don't know why. We're all in the same place."

"We're all in the same place. Sharing lessons learned along the way is another element."

This assertion cuts to the heart of a widespread misconception: that AI adoption is either happening or not happening, with no in-between. In reality, the journey toward meaningful AI integration is complex and ongoing—particularly in healthcare, where patient safety, data privacy, and human workflows are paramount.

Technology That Evolves Faster Than Us

The rapid evolution of AI presents a unique challenge for hospitals. Unlike traditional software that stabilizes over years, AI systems often undergo drastic changes within months. "We're used to technology that we implement and it's stable for five to 10 years outside of upgrades," Shoenthal noted. "Not technology where yesterday's version is nothing like today's version."

This volatility demands a new approach to adoption—one that's both strategic and patient-centered.

The Trust Factor: How Providers Embrace AI

For AI to be effective in healthcare, it must be trusted by clinicians. Shoenthal emphasized the need for a deep collaboration between technology vendors and providers. "We've always needed collaboration, but it has to be deeper now with the pace that things are moving," he said.

The challenge isn't just technical—it's emotional. "How do we help guide the change for all of our teams? Thinking about our nursing teams, they've been practicing the same way for years... now we're asking them to trust technology more to do some of those tasks," Shoenthal explained.

Value That Takes Time to Realize

Vendors often promise quick wins—reduced staff time, optimized workflows—but the actual impact of AI can take much longer to materialize. "The time to realize it is longer than what I think they realize," Shoenthal noted.

He used ambient technology as an example: early on, providers may see time savings, but that time is often redirected toward other tasks, not necessarily reduced. "What's the value of those new things that I'm actually able to do with the time?" he asked. This shift in focus is crucial for providers who want to understand true ROI beyond simple cost-cutting.

Striking the Right Balance: Governance and Experimentation

MD Anderson approaches AI through a dual lens of governance and experimentation. "We've come at it from both sides of the coin," Shoenthal said, describing a structured process for evaluating new technologies.

Their approach includes cross-functional teams—technology, ethics, clinical staff, legal, compliance—to review potential tools. This layering ensures that AI projects align with broader organizational goals and patient outcomes.

"We can't be looking for perfect," he emphasized. "Some of this technology... we have to allow for experimentation. You can write it down on paper and plan all you want, but until you actually get your hands on the technology and experiment with it, you're never going to know."

Patient-Centric AI: The Human Connection Reimagined

What sets healthcare AI apart from other sectors is its focus on human interaction. Shoenthal believes that AI can actually enhance—not replace—the human connection.

"I think we're starting to see for the first time that the technology is being reductive in nature in terms of how dependent we will be on computers," he said, envisioning a future where nurses and providers are freed from routine tasks. "Why do we need that cart? There's going to be automation that will be able to bring supplies and medication. We'll be able to do documentation on the fly. Information that they need as part of the care is going to be on their phone."

For Shoenthal, the goal is to allow clinicians to focus more on what matters most: engaging with patients.

Building a Shared Vision

The key to successful AI integration isn't just choosing the right tools—it's building shared understanding between providers and vendors. "Do you have a shared vision on what that end experience should be?" he asked.

That shared vision, combined with a focus on workflow improvement rather than technology first, is critical for long-term success.

Why the Perception of Being Behind Is Wrong

One of the most compelling insights from Shoenthal's perspective is that the perception of being behind is largely mental. "We're all in the same place," he reiterated. "Instead of feeling this need to play catch-up with one another, it would be an interesting discussion about: How do we share what good looks like?"

This call for collaboration echoes a broader need in healthcare—to move from competitive silos to shared learning. "We're not a competitive industry," Shoenthal said. "We all have the same aim, which is bettering human life."

The Future of AI in Healthcare: A Patient Perspective

Finally, Shoenthal highlighted what he sees as an under-discussed dimension of AI adoption: the patient perspective. "I don't know that I've seen enough on what's actually the patient's perspective of this whirlwind of technology and emerging data," he noted.

As AI becomes more integrated into care delivery, understanding how patients experience it will be essential—not just for trust, but for effective implementation.