Insights from Laurel Salvati, Director of Product Management at b.well
Walking the floor at AHIP 2026 this June, I kept hearing the same conversation over and over, in keynotes, in breakout sessions, in hallway conversations between sessions. The message was consistent, almost urgent: health plans want to move faster on AI. They want to deploy digital quality measures, unify fragmented data, and close care gaps at scale. Running through all of it is a relentless pressure on affordability, from drug pricing to unit cost to the sustainability of benefit design.
But what struck me most is that almost every breakthrough discussion eventually circled back to the same bottleneck. Data is messy, siloed, and inconsistent.
At AHIP 2026, Good Intentions Keep Hitting the Same Wall
The sessions and the conference floor had the same conversations and topics as previous years: AI-driven risk prediction, real-time care gap identification, and smarter member engagement. But ask health plan leaders what’s actually slowing them down, and the answer is almost always the same. Their claims systems don’t talk to their clinical data. Their behavioral health records are isolated. Their pharmacy data lives separately. These systems were often built decades apart, on incompatible architectures, with different standards. Now, with AI in the conversation, the “sense of urgency” felt much more pressing.
Sessions on affordability, from drug pricing conversations with health plan and pharma leaders to broader cost management discussions, all circled back to the same conclusion that you can’t manage costs you can’t accurately measure and attribute. Cost reduction and data quality are the same problem.
AI is only as good as the data underneath it. Every conversation about AI in healthcare eventually hits the same wall of siloed, inconsistent legacy data. Plans making real progress aren’t starting with the model; they’re starting with the foundation. Clean, connected, interoperable data is the prerequisite. That’s exactly what the b.well Data Refinery is built for.
The Architecture That Actually Works
What I found most encouraging at AHIP 2026 was seeing how some health plans are actually solving this. The ones with real momentum aren’t trying to boil the ocean. They’re being methodical.
They’re standardizing data models (often using FHIR as the backbone). They’re investing in data integration platforms that can speak multiple languages—claims, clinical, behavioral, and pharmacy. They’re treating data governance not as a one-time project, but as a continuous discipline. Plans that standardized and validated their provider data reported that everything downstream got faster: claims processing, quality reporting, member engagement, and provider contracting conversations.
The conference showcased many vendors and approaches to solving pieces of this puzzle, but the overarching theme wasn’t about any particular tool. It was to fix your data foundation first, then everything else becomes possible.
From Compliance Checkbox to Competitive Advantage
Digital quality measures (dQMs) kept coming up as a significant opportunity. The premise is that instead of measuring quality based on data from months ago (Star ratings released in October for year-long performance), what if health plans could identify care gaps in real time and act on them before the reporting window closes?
dQMs turn compliance into a continuous feedback loop. Digital quality measures shift quality reporting from a retrospective exercise into real-time intelligence, giving health plans the signal they need to identify care gaps before they become missed stars, missed revenue, or missed member outcomes.
But dQMs only work if you have connected data. You need clinical data (did the member get screened?), claims data (was it paid?), and engagement signals (did outreach happen, and how did the member respond?). All of it, in sync. Which brings us back to the Data Refinery.
The Interoperability Mandate is Your Forcing Function
The CMS interoperability mandate came up constantly, sometimes framed as a regulatory burden, increasingly as a strategic opportunity.
The insight that resonated: The CMS interoperability mandate is a strategic opportunity, not just a compliance checkbox. Health plans that treat CMS requirements as the forcing function to unify fragmented data will be the ones positioned to act on it.
The mandate requires health plans to exchange member data with providers and other plans in standardized formats. Plans that build this infrastructure thoughtfully aren’t just checking a compliance box; they’re creating networks that pull supplemental clinical data across the care system, giving them a complete, longitudinal picture of the patient.
Plans that build this infrastructure right are positioning themselves for a competitive advantage. That complete view is what powers smarter digital quality measures, tighter care gap closure, and a member experience built on accurate, connected care.
The plans still treating it as ‘we have to comply’ are building minimal infrastructure. The plans treating it as an opportunity are building competitive moats, and The Payer’s Guide to CMS Health Technology Ecosystem Readiness is a good place to start.
The Engagement Bottleneck: Knowing vs. Doing
A consistent theme throughout the conference was member engagement, or more precisely, the gap between insight and action.
Health plans have more data than ever about care gaps. We’ve said for years that we, as an industry, are data-rich yet insight-poor. Because we’ve learned that data alone doesn’t close gaps. One plan described having detailed intelligence on hundreds of thousands of care opportunities, but only a fraction of them are being addressed—not because they don’t want to help, but because the engagement tools haven’t caught up with the insights.
Digital experiences for members with next best actions close the last mile. Across the industry, health plans have access to more data than ever, but knowing a care gap exists is not the same as closing it. Most plans are still working to bridge the distance between insight and action. When AI-driven guidance reaches members at the right moment through a portal that’s personalized, simple, and connected to their care team, that gap finally closes.
The most effective approaches combine:
- Personalization: Tailored guidance based on the member’s specific situation and care team recommendations
- Simplicity: Portals that don’t require members to navigate endless screens
- Connection: Care teams can see what actions were offered and taken, so follow-up feels coordinated, not repetitive
Most plans are still working to bridge the distance between insight and action. When AI-driven guidance reaches members at the right moment through a portal that’s personalized, simple, and connected to their care team, that gap finally closes.
The Prior Authorization Reckoning
Prior authorization was the other major flashpoint at the conference, and it connects directly to the data conversation in ways that deserve more attention than it usually gets.
A new AHIP-BCBSA coalition at the conference committed to meaningful PA reduction and reported early progress: an 11% drop in prior auth volume across participating plans, including more than 15% in Medicare Advantage. The industry momentum here is real.
But the harder question surfacing in sessions: how do you automate PA decisions in a way that’s defensible, safe, and consistent? Plans moving toward automated authorization are quickly running into the same wall as AI adoption broadly. The clinical criteria, member history, and evidence base must be connected and up to date. Automated PA built on incomplete data doesn’t reduce administrative burden; it just moves the error earlier in the process.
Prior authorization reform and data infrastructure are the same conversation. Reducing administrative burden requires the same connected, accurate data foundation that powers quality measurement and member engagement. Plans that clean up their data foundation first will be the ones that can actually deliver on their prior auth commitments, and do it safely.
The Population That Matters Most
The final theme that kept surfacing—and the one that felt the most urgent—was Medicaid and complex populations.
Medicaid and complex populations demand better infrastructure, not more complexity. Rising costs, behavioral health gaps, and policy turbulence mean the members with the greatest need are also the hardest to reach. Integrated data, digital quality measures, and proactive care management workflows are how health plans meet that challenge at scale.
Behavioral health integration kept coming up as critical. Plans that successfully combined behavioral health data with medical and claims data reported being able to identify members at the highest risk of hospitalization and offer proactive support before a crisis. That kind of integrated care management—managing the whole person, not fragmented parts—only works with connected data infrastructure.
Plans can only improve what they can measure, and they can only measure what their data infrastructure lets them see.
The Uncomfortable Truth
The real conversation at AHIP 2026 kept coming back to the same unglamorous question: How do we actually integrate our fragmented systems?
It’s not a new question. It’s not a sexy question. It won’t generate a killer press release.
But it’s the question that separates health plans that are genuinely moving the needle on affordability, quality, and member experience from those that are executing interesting pilots that never scale.
The plans making progress start with their data. They invest in the unglamorous work of standardization, integration, and continuous governance. They treat interoperability not as compliance overhead but as the foundation for everything else. They build portals and workflows that connect insights to actions. They focus on the populations that need help most.
Start with the data foundation. Everything else becomes possible.
That’s the message from AHIP 2026. The plans that take it seriously will lead the industry in the years ahead.
What’s Coming After AHIP 2026
If you attended AHIP 2026, what stayed with you? What are the real bottlenecks you’re seeing in your organization? How are you thinking about data, interoperability, and member engagement in your 2026 roadmap?
The work isn’t easy. But the opportunity is clearer than ever.
