| | | Healthcare may finally have struck a healthy balance between AI hype and AI reality, according to a report from impartial observers who are also, indirectly at least, healthcare AI stakeholders. The group is the international strategic-communications agency Norvell Jefferson, which sells no healthtech products but serves clients who do. In early March the agency’s people descended on HIMSS25 in Las Vegas to conduct conversations, gather insights and interview healthcare leaders on healthcare technology. In its report on the business intel project, released in April, Norvell Jefferson frequently homes in on AI. Here are seven key excerpts. 1. AI has the potential to revolutionize diagnostics, workflow automation and personalized care. But it cannot function in isolation. Healthcare systems must have real-time interoperability, trust in data security and infrastructure capable of supporting AI-driven decision-making, the report’s authors state. ‘Without these attributes, AI adopters risk becoming inefficient silos rather than connected, intelligent ecosystems.’
2. The rise of ambient intelligence signals a shift from AI as a tool to AI as an invisible but indispensable assistant in healthcare.“AI is shifting from an external tool that clinicians have to interact with manually to an embedded, invisible intelligence”—one that automatically processes conversations, extracts relevant data and executes administrative tasks, Norvell Jefferson reports. ‘This shift was one of the most defining themes at HIMSS25.’
3. Healthcare AI’s success depends entirely on the quality and accessibility of data. While adoption rates for AI-powered healthcare solutions are rising, fragmented IT infrastructures, legacy systems and lack of standardized data-sharing practices are impeding progress. “Interoperability is no longer an IT challenge,” the agency writes. “It is a fundamental business and patient care necessity.” More: ‘Organizations that fail to prioritize seamless data exchange risk limiting AI’s effectiveness, creating inefficiencies and missing out on the full potential of real-time, AI-powered healthcare.’
4. AI is a double-edged sword. AI is not just an enabler of healthcare innovation—it is also being used by cybercriminals to develop more sophisticated attacks, the authors note. “As healthcare becomes increasingly digital, cybersecurity is evolving from a reactive defense mechanism into a proactive enabler of innovation, trust and patient safety.” ‘Security must evolve alongside the technologies driving modern healthcare. And security teams must stay ahead by using AI-driven cybersecurity tools.’
5. Rigid, outdated technology is one of the biggest barriers to AI and interoperability adoption. Healthcare providers that continue to rely on legacy IT infrastructures face slow AI adoption, high cybersecurity risks and bloated operational costs, Norvell Jefferson observes. ‘Tech debt is slowing down progress at a time when healthcare is under immense pressure to improve efficiency, reduce costs and enhance patient care.’
6. The smart hospital concept is evolving. ‘AI is no longer just improving hospital workflows—it is transforming healthcare beyond hospital walls, from remote patient monitoring to AI-assisted virtual care.’
7. The challenge is no longer whether to innovate—but how to do so responsibly, securely and efficiently. ‘The next era of healthcare will be defined by organizations that take proactive steps now to future-proof their IT, align AI with real clinical needs and prioritize security and compliance.’
Access the full report here. |
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| | | Buzzworthy developments of the past few days. - Bill Gates wasn’t just wrong to suggest AI will make physicians unnecessary. He was reckless. Gates made the comment in a recent appearance on “The Tonight Show.” Two subject matter experts made the fiery rebuttal in The Hill. “The Gates narrative that doctors will soon be obsolete creates a dangerous distraction from the work healthcare leaders should be focused on right now: scaling AI that works in partnership with clinicians, not in place of them,” write Jesse Ehrenfeld, MD, MPH, a former president of the American Medical Association and Elad Walach, CEO and co-founder of Aidoc. “Doctors are not a bug in the system. They are the system. And AI, when used correctly, makes them better. Faster. More informed. Less burned out.” Hear them out.
- If you like structured medical reports, you’re going to love structured medical timelines. The latter are a work in progress at the National Library of Medicine, where a team led by Jeremy Weiss, MD, PhD, is using large language models to show patients’ care events in sequence and with timestamps. Weiss and team are now focusing on “improving the accuracy and usability of their framework, including refining how it understands different ways we express time, incorporating human feedback to fine-tune their accuracy and tailoring the tool for specific medical fields,” NLM’s news operation reports. “These advancements could bridge the gap between free text and structured timelines, paving the way for smarter and more efficient health care tools—all to ultimately better serve patients and their providers.”
- Tariffs focused on pressuring China to trade more fairly are a good thing for healthcare AI. How so? By “creating unique pressures on the U.S. healthcare system that will accelerate the adoption of AI automation to cut costs.” That’s the opinion of Mika Newton, chief executive officer of the healthcare AI supplier xCures. Making his case in Health Tech World, Newton suggests sustained inflationary pressures and other factors are “compounding to create a perfect storm” in which healthcare administrators “are left with no choice but to rely on innovation.” The duress, he believes, will end up “making AI more of a necessity than simply a feature of new capabilities.”
- When it comes to regulating AI for use in healthcare settings, U.S. states are all over the map. Pun unintended but irresistible. The global law firm Morgan Lewis has compiled an easily navigable grid for getting a quick look at legislation in each state, complete with links to bills. The authors comment that, as states continue to refine their regulatory frameworks regarding AI in clinical settings, “the balance between innovation and patient protection is likely to remain a critical focus for legislators. Absent federal preemption, divergent state frameworks may create compliance complexities for multi-state providers and insurers.” With increasing regulatory fragmentation, they add, healthcare providers “will need to implement additional compliance infrastructure and training to navigate disparate requirements across states.” Browse their helpful work here.
- The American Hospital Association has noticed an uptick in the volume of AI tools coming to market for nurses. In an April 29 post, the organization looks at a few examples and quotes a leader in the field. Nurses will always need to apply clinical judgment and critical thinking in how they care for their patients, says Kay Burke, RN, vice president and chief nursing informatics officer at UCSF Health in San Francisco. “Every AI tool,” she adds, “necessitates the clinician to review and validate what was suggested.”
- Healthcare AI is nothing to be afraid of. But misperceptions around AI proponents’ intent can be quite frightening indeed. So Steven Bernstein, MD, chief research officer at Dartmouth Health in New Hampshire, probably spoke for many at an April 18 symposium on precision health and AI. “My biggest fear around the use of AI in healthcare would be a mistaken impression on the part of healthcare leaders that AI can allow you to reduce your workforce,” Bernstein told attendees. “The reality, of course, is AI will never be able to deliver care itself. I think there’s enormous promise in the careful use of AI for diagnostics and prognostics, but the actual on the ground, at the bedside will always be in the province of human beings.” Symposium coverage here.
- Understand the limitations of AI tools. That’s one of 10 tips gathered from experts by TechTarget. Expounding on the point, Michael Matheny, MD, MPH, recommends technology leaders remind algorithm users that AI is fallible. “It may be wrong sometimes, and you may need to override it,” he says. To this reporter Brian Eastwood adds: “The consequences of being wrong also need to be considered. An AI system booking two appointments at 11:30 is far different from an AI system prematurely shutting off a patient’s ventilator.” Get the other nine tips here.
- Count healthcare reporters among the humans worried about AI coming for their jobs. Especially if their main beat is healthcare AI. Which is to say that I can’t help but think such thoughts when I come across a decently written article bylined to an AI bot and headlined something like “The Future of Healthcare AI Is Happening Now.” Well played, Nucleus_AI. Or whatever the other writer bots call you.
- Recent research in the news:
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