AI’s role in 2026: Expert predictions

What will the role of artificial intelligence (AI) be in 2026?

In this article, originally published by our sister publication, Healthcare Innovation, Contributing Senior Editor David Raths discusses what vendors, health system execs, consultants, and venture capitalists think AI’s influence will be in 2026. Read the full article from Healthcare Innovation below.

Industry insiders' bold predictions about AI’s impact in 2026

Heading into the new year, I have been the recipient of lots of predictions from vendors, health system execs, consultants and venture capitalists. Most of the predictions focus on where people think AI adoption is headed in the new year. I thought I would pull some of these together here so readers could start identifying patterns and common themes. Happy New Year!

Keith Figlioli, managing partner at venture capital firm LRVHealth, has his finger on the pulse of health system transformation and the digital health startup environment. Here is one of his AI predictions:

“Reality will hit hard in 2026 as people start to recognize how difficult it will actually be to deliver on all the dreams and promises of AI in healthcare. There will continue to be significant gains and usage across healthcare, but many lofty initiatives will fall flat and more tempered approaches will prevail. Many AI pilots will advance and we’ll continue to see more AI in production environments, but we still won’t see the true impact of AI for a while. In healthcare, it will be many years before most organizations can calculate even baseline ROI and before predictions of job replacements come to fruition. 

“Next year we’ll start to see glimmers of hope where AI will be applied to entirely new workflows and capabilities in healthcare. Work areas that were either too expensive or not possible before the introduction of LLMs and agents will be imagined, and reimagined. For example, we’re already starting to see things like automated scheduling and the next evolution of the digital front door, automated radiology reads using agentic AI, and automated specialty drug enrollment.”

David Dyke is chief product officer at Relatient, which offers self-scheduling, patient messaging, chat, digital registration and payment solutions. One of his AI predictions is that health systems will be betting on experience over startups:

“This year brought a surge of new entrants into the healthcare IT space, similar to what we saw during COVID, with many emerging vendors stepping in to meet rising demand and the green space for healthcare AI. As we move into 2026, organizations will adopt more targeted and sophisticated AI functionality, most often through the digital health partners they already rely on. These entrenched vendors have been in this space and understand the intricacies of healthcare, and that gives them a foundation that only time can provide. As the initial novelty of AI wears off, many organizations will look to deepen their investment in trusted partners rather than take on new, one-off solutions that require additional lift, integration, or oversight.”

Arcadia President and CEO Michael Meucci had two AI-related predictions, one for providers and one for payers:

“Providers are balancing operational constraints with rising competition from consumer-first healthcare models. That makes this moment both a technology challenge and an operational one. 2026 will still feel like part of the “year of AI,” but we’ll be past the early experimentation phase. The real differentiator will be embedding these tools where they can drive meaningful results.”


“Payers are heading into 2026 under intensifying pressure. Medical cost trend remains elevated, competition is accelerating, and both payers and providers are rapidly deploying AI across payment integrity, coding, and revenue workflows. The challenge isn’t whether AI will matter because it will. The challenge is separating what AI can fix from what it cannot. AI alone is not going to solve anyone’s trend problem. It will help, but it’s not a silver bullet. What payers truly need is transformation: better networks, aligned incentives, and a shift in strategy that connects AI to measurable performance.”

The following is a prediction from Heather Trimble, healthcare strategic advisor for analytics and business intelligence software vendor SAS:

“AI productivity stacks become the norm. By the end of 2026, every major enterprise will have an AI productivity stack. The same way every business today has cloud and customer relationship management (CRM), LLMs stitched into deterministic engines will run everything from marketing copy to medical billing. Generative AI gets the headlines, but deterministic AI writes the checks. Together they make the modern enterprise faster, leaner, and more inhumanly efficient. The losers will be clinging to the illusion that AI is another ‘tech wave.’”
Lynne Nowak, M.D., chief data and analytics officer at Surescripts, offered this observation:

“Data insights and the use of AI have incredible potential to continue improving how patient care is delivered. I predict that in 2026, organizations, clinicians and care managers will work to ensure that these tools are used in the most responsible way—training not just in the mechanics but also the ethical use of new AI technology—to keep support care decisions and improve patient care.”

Eric Prugh, chief product officer at patient engagement platform Authenticx, has an interesting take:

“One of the biggest opportunities for AI in 2026 will be utilizing AI in leadership. So much of the focus has been on replacing or augmenting frontline, individual contributor work – customer service reps, note takers and so on. But the real untapped potential lies in tools that help leaders make better, faster, more informed decisions.”

This final prediction is from Sachin Gupta, founder and global CEO of IKS Health. His company's platform combines AI and human expertise to connect clinical, operational, and financial workflows.

“In 2026 we'll see continued development of a platform approach enabled by agentic interconnected workflows with appropriate human-in-the-loop. There will be recognition that AI is much more of a platform play than the point solution-oriented approach that healthcare IT and health systems have traditionally taken. That platform play is going to be deeply enabled by interconnected agentic workflows. These workflows will truly demonstrate that the value of the whole is much greater than the sum of the individual parts, especially when chores of healthcare are delegated to a platform that alleviates the burdens on caregivers and their care teams.”