Three healthcare trends that will shape 2026

Three healthcare trends that will shape 2026

As we head into 2026, it’s clear that AI will be a defining feature of the year. I’ve called it a make-or-break moment not only for healthcare, but for the broader economy. But AI isn’t the whole story. What matters more are the structural shifts that AI is accelerating — in how data moves, how patients interact with the system, and how organizations operate.

There are three areas I’m watching closely. They’re interconnected, and each one raises questions the industry will likely confront this year.

1. The shift from portals to platforms

Across the payer-provider landscape, I’m seeing a gradual move toward true platform thinking. Payers in particular are beginning to recognize the limitations of portal-based workflows. Healthcare is still 10 to 15 years behind other parts of the economy in this regard. Many practices log into multiple portals, retrieve files manually, or navigate systems that don’t really talk to each other.

In a platform model, that friction goes away. Travel is a helpful analogy: consumers used to visit several sites to plan a trip. Now platforms like Google Flights orchestrate the experience end-to-end. Healthcare rarely functions this way, but there are early signs of change. The CMS requirement for electronic prior authorization at the end of 2026 is one signal. TEFCA is another. So are emerging efforts around the National Provider Directory and aligned-network concepts.

The question for this year is whether these platform signals begin to add up. There’s still a tremendous opportunity to “platformatize” data exchange and make it fully digital. A platform-first mindset would allow services to be exposed as APIs and transactions, not portals. Over time, AI agents could carry out the majority of these interactions, with humans stepping in primarily for audit or transparency needs.

At athenahealth, we’re preparing for that world through our API-first architecture and TEFCA participation. But the real transformation requires the entire ecosystem to move in that direction.

By the end of 2026, we’ll have some clear takeaways about when and where AI interactions are actually beneficial — and where even a small dose of human empathy remains essential.

2. Finding the line between AI efficiency and human connection

2026 may also bring clarity on what I call the “virtual doctor” question. The core issue is how much of healthcare requires human interaction versus how much value can be delivered through efficient, AI-driven service.

Medicine has long recognized the “laying of hands,” the idea that human connection plays a role in the experience of care beyond diagnosis or treatment. The open question is how far synthetic interactions can go before they diminish — or replace — that human element, and in which cases efficiency is enough. This isn’t only a clinical consideration. Administrative and service interactions also shape how people feel about their care. If an AI agent helps them accomplish what they need, does it matter that it wasn’t a person? And when does it matter?

Patients have been consulting “Dr. Google” for years. Nearly one in four respondents have turned to ChatGPT and other AI tools for health-related inquiries.¹ By the end of 2026, I think we’ll have some clear takeaways about when and where AI interactions are actually beneficial to patients, clinicians, and staff — and where even a small dose of human empathy remains essential.

3. The rise of service-as-software operations

Many parts of healthcare don’t operate in a traditional SaaS model. That’s changing quickly, and AI is accelerating the shift. In the EHR and RCM market, I expect to see a clearer distinction between traditional software and what I think of as “service as a software”: outcomes delivered through AI-enabled services rather than through tools users manage manually.

Payers are already using AI to manage claims. Providers are using their own tools to keep pace. It sometimes feels like a “Spy vs. Spy” dynamic. However, some of the experiments now underway, such as claims adjudication off clinical records, could reshape payer–provider relationships entirely, and make the system actually more productive.

For healthcare organizations, the bigger shift is operational. To take advantage of service-as-software models, they’ll need the infrastructure to operate fleets of AI models or agents. Last year, many discussions centered on experimentation. This year, I expect to see the first signs of operational use.

At athenahealth, we’re developing a Model Context Protocol (MCP) layer that allows AI agents to interoperate and function as both an interoperability mechanism and an operational tier. It’s a way for organizations to move from one-off experiments to consistent, scalable use. The organizations that prepare for this shift will adapt more easily. Those that don’t may face significant change-management challenges.

A year that sets direction, not final answers

These shifts don’t stand alone. They’re unfolding during a period of uncertainty in coverage, enrollment, and reimbursement — shaped by exchange dynamics, Medicaid shifts, and rural health transformation. AI is part of the story, but so are policy changes, payer strategies, and rising patient expectations.

I don’t think 2026 will resolve the big questions. But I do think it will clarify where the industry is heading — and which organizations are preparing for that future. Those that approach these shifts thoughtfully, build for interoperability, and understand where humans matter most will be in the strongest position in the years ahead.

Michael Palantoni is athenahealth's chief strategy and corporate development officer.