Heading into the brand new 12 months, I’ve been the recipient of a lot of predictions from distributors, well being system execs, consultants and enterprise capitalists. A lot of the predictions deal with the place folks assume AI adoption is headed within the new 12 months. I believed I might pull a few of these collectively right here so readers may begin figuring out patterns and customary themes. Glad New Yr!
Keith Figlioli, managing accomplice at enterprise capital agency LRVHealth, has his finger on the heartbeat of well being system transformation and the digital well being startup setting. Right here is one in all his AI predictions:
“Actuality will hit laborious in 2026 as folks begin to acknowledge how tough it would really be to ship on all of the desires and guarantees of AI in healthcare. There’ll proceed to be vital good points and utilization throughout healthcare, however many lofty initiatives will fall flat and extra tempered approaches will prevail. Many AI pilots will advance and we’ll proceed to see extra AI in manufacturing environments, however we nonetheless received’t see the true affect of AI for some time. In healthcare, will probably be a few years earlier than most organizations can calculate even baseline ROI and earlier than predictions of job replacements come to fruition. “Subsequent 12 months we’ll begin to see glimmers of hope the place AI shall be utilized to thoroughly new workflows and capabilities in healthcare. Work areas that had been both too costly or not doable earlier than the introduction of LLMs and brokers shall be imagined, and reimagined. For instance, we’re already beginning to see issues like automated scheduling and the subsequent evolution of the digital entrance door, automated radiology reads utilizing agentic AI, and automatic specialty drug enrollment.”
David Dyke is chief product officer at Relatient, which provides self-scheduling, affected person messaging, chat, digital registration and cost options. One among his AI predictions is that well being techniques shall be betting on expertise over startups:
“This 12 months introduced a surge of latest entrants into the healthcare IT house, just like what we noticed throughout COVID, with many rising distributors stepping in to fulfill rising demand and the inexperienced house for healthcare AI. As we transfer into 2026, organizations will undertake extra focused and complex AI performance, most frequently by means of the digital well being companions they already depend on. These entrenched distributors have been on this house and perceive the intricacies of healthcare, and that provides them a basis that solely time can present. Because the preliminary novelty of AI wears off, many organizations will look to deepen their funding in trusted companions slightly than tackle new, one-off options that require extra carry, integration, or oversight.”
Arcadia President and CEO Michael Meucci had two AI-related predictions, one for suppliers and one for payers:
“Suppliers are balancing operational constraints with rising competitors from consumer-first healthcare fashions. That makes this second each a expertise problem and an operational one. 2026 will nonetheless really feel like a part of the “12 months of AI,” however we’ll be previous the early experimentation section. The actual differentiator shall be embedding these instruments the place they will drive significant outcomes.”
“Payers are heading into 2026 below intensifying strain. Medical value pattern stays elevated, competitors is accelerating, and each payers and suppliers are quickly deploying AI throughout cost integrity, coding, and income workflows. The problem isn’t whether or not AI will matter as a result of it would. The problem is separating what AI can repair from what it can’t. AI alone isn’t going to unravel anybody’s pattern drawback. It should assist, nevertheless it’s not a silver bullet. What payers actually want is transformation: higher networks, aligned incentives, and a shift in technique that connects AI to measurable efficiency.”
The next is a prediction from Heather Trimble, healthcare strategic advisor for analytics and enterprise intelligence software program vendor SAS:
“AI productiveness stacks turn into the norm. By the top of 2026, each main enterprise could have an AI productiveness stack. The identical approach each enterprise immediately has cloud and buyer relationship administration (CRM), LLMs stitched into deterministic engines will run the whole lot from advertising copy to medical billing. Generative AI will get the headlines, however deterministic AI writes the checks. Collectively they make the trendy enterprise sooner, leaner, and extra inhumanly environment friendly. The losers shall be clinging to the phantasm that AI is one other ‘tech wave.’”
Lynne Nowak, M.D., chief information and analytics officer at Surescripts, provided this commentary:
“Knowledge insights and using AI have unbelievable potential to proceed bettering how affected person care is delivered. I predict that in 2026, organizations, clinicians and care managers will work to make sure that these instruments are utilized in essentially the most accountable approach—coaching not simply within the mechanics but additionally the moral use of latest AI expertise—to maintain help care selections and enhance affected person care.”
Eric Prugh, chief product officer at affected person engagement platform Authenticx, has an fascinating take:
“One of many greatest alternatives for AI in 2026 shall be using AI in management. A lot of the main focus has been on changing or augmenting frontline, particular person contributor work – customer support reps, word takers and so forth. However the actual untapped potential lies in instruments that assist leaders make higher, sooner, extra knowledgeable selections.”
This closing prediction is from Sachin Gupta, founder and world CEO of IKS Well being. His firm’s platform combines AI and human experience to attach medical, operational, and monetary workflows.
“In 2026 we’ll see continued growth of a platform method enabled by agentic interconnected workflows with acceptable human-in-the-loop. There shall be recognition that AI is far more of a platform play than the purpose solution-oriented method that healthcare IT and well being techniques have historically taken. That platform play goes to be deeply enabled by interconnected agentic workflows. These workflows will actually display that the worth of the entire is far higher than the sum of the person elements, particularly when chores of healthcare are delegated to a platform that alleviates the burdens on caregivers and their care groups.”
