ViVE 2026: 4 Themes Through the Eyes of a CMO Data Geek
Dr. Niki Panich, MD, CCFP, FCFP, MBA, MS. (MDSA), MSCP
Chief Medical Officer, Penguin Ai
ViVE 2026 made it official: healthcare AI has moved from "is this possible?" to "how do we operationalize it?" Across three days in Los Angeles, the conversations that mattered weren't about what AI can do. They were about governance frameworks, workforce adoption, data architecture, and measurable ROI. Here are the four themes that stood out to me from a CMO data perspective, and what they mean for the executives making decisions right now.
Theme 1: Prior Authorization Automation Has Reached Its Inflection Point. And Penguin Ai Is Exactly Where the Market Is Landing.
Every CMO in that convention center has been burned by prior auth. ViVE 2026 made the scale of the problem, and the opportunity, undeniable.
The number that should be in every board presentation: only 40% of prior authorization transactions were handled electronically in 2024, up from 35% in 2023 and 31% in 2022. Which means 60% of prior auth is still manual, phone-based, fax-dependent friction. In 2026. The estimated cost savings from fully automating prior auth alone is $50 to $60 million.
This is precisely the problem Penguin Ai was built to solve. While most vendors at ViVE were showing point solutions (automate the intake, or automate the eligibility check, or automate the status update) Penguin Ai's agentic platform attacks the entire prior auth workflow end to end. The clinical data gathering, the medical necessity mapping, the payer-specific rule logic, the routing, the human escalation triggers. It's not a tool that assists the UM nurse. It's a system that handles the case and surfaces it to the clinician only when judgment is genuinely required.
What sets Penguin Ai apart in this conversation is the CMO-facing data layer. The pitch isn't "we automate prior auth." It's "here's your overturn rate by service line, here's your median turnaround time by payer, here's where your physicians are losing the most hours, and here's what that costs you in MLR." That's the language that moves health plan and health system executives from curious to committed. Our work with a major regional health plan has demonstrated exactly this: 87% faster processing times, 95% accuracy rates, and MLR improvements that translate directly to financial performance.
As a CMO, the ViVE 2026 takeaway on prior auth is simple: the gap between where the industry is (60% manual) and where it needs to be is a massive, quantifiable opportunity. The organizations that close that gap fastest will win on cost, on physician retention, and on patient experience simultaneously. Penguin Ai is built for that moment.
Theme 2: Agentic AI Is No Longer a Pilot. It's a Production System.
The most significant signal at ViVE 2026 is that agentic AI has crossed the threshold from proof-of-concept into enterprise deployment. This isn't ambient listening or a chat interface. These are AI systems that take action across disconnected workflows.
The data that stops you mid-sip of your coffee: UiPath reported that after deploying their Medical Records Summarization solution, one healthcare organization reduced average summary review time from 70 minutes to six. A 90% improvement. For those of us who've watched our physicians spend half their day in chart review, that number deserves to be laminated and hung in every C-suite.
The real CMO question isn't "does this work?" anymore. It's "where do I start, and what does my governance framework look like?" The vendors who are winning are the ones who come in with audit-ready, traceable outputs, not just faster outputs.
Theme 3: Workforce Adoption Is the Real Implementation Problem. Not the Tech.
ViVE 2026 featured a refreshingly honest reckoning: the technology is often ready before the clinical culture is. Nursing leaders took the main stage and said the quiet part loud.
The analogy that nailed it: Whitney Staub-Juergens, VP and COO of Transformation Operations at HCA Healthcare, described having to explain nurse handoff to technologists "six ways to Sunday" because what looks like a simple shift exchange is actually a 12-hour care planning exercise involving high-order strategic thinking.
Saad Chaudhry offered what might be the best metaphor of the entire conference: "Implementing AI is like buying a smart thermostat only to discover your home lacks a central air conditioning system. The 'human' side of the equation, standardizing workflows and redefining how tasks are performed, is the expensive, time-consuming 'HVAC installation' that must happen before the technology can actually function."
Dr. CT Lin's sepsis story drove this home with hard outcomes. When his team first turned on their sepsis AI model, the high rate of false positives destroyed clinician trust. So they stopped sending alerts and instead rerouted the data to a virtual health team that combines AI signals with other patient observations. By figuring out the right human-plus-AI approach, they're now saving 1,000 lives per year. That's what getting adoption right looks like.
For CMOs, this is the implementation risk that doesn't show up in the vendor pitch deck. The data-driven lesson: track adoption curves by workflow type, not just by technology deployed. A 95% accurate AI that only gets used 20% of the time delivers 19% of the promised value. Physician and nursing champions, workflow co-design, and embedding tools into existing patterns (not bolting them on) are the difference between a successful rollout and a very expensive shelf product.
Theme 4: Interoperability Has Gone From Aspiration to Mandate. Now It's a Competitive Edge.
TEFCA and CMS data-sharing rules have shifted interoperability from a nice-to-have to a compliance floor. ViVE 2026 showed that the organizations pulling ahead are treating it as a strategic advantage, not a checkbox.
Helen Waters didn't mince words: "Healthcare has only earned a C-minus for its interoperability efforts. We must fix this, as data liquidity is the only way to unlock the full value of AI." A C-minus. For the foundational infrastructure that everything else depends on.
The operational reality: agentic systems can pull data from EHRs, payer portals, lab systems, and internal databases, then act on it to complete entire workflows. This solves what the industry has started calling the "last mile" problem of healthcare data. Manual re-entry, portal hopping, and record matching are where time and accuracy die.
Dr. Rob Bart offered a pragmatic path forward: "Solid data architecture is the foundation of AI, but that doesn't have to mean a total 'rip and replace' of your current EHR. Instead, we can treat existing interfaces as a middle layer and build a modern UI on top of them." For organizations with heavy legacy investments, that's a much more realistic path to innovation.
The CMO lens on this: interoperability isn't an IT project. It's what determines whether your clinical intelligence is real-time or 48 hours delayed, whether your utilization management team has complete data or is making decisions on partial charts, and whether your AI tools are actually learning from your population or operating on generic training sets. Organizations that control their data pipelines will have a measurable advantage in care quality metrics within 18 to 24 months.
The Bottom Line
From a CMO data perspective, ViVE 2026 confirmed that the "AI in healthcare" era has officially ended and the "AI operations in healthcare" era has begun. The questions have shifted from "is this possible?" to "what's my governance framework, what's my adoption strategy, and how do I measure ROI at the workflow level?"
Those are exactly the right questions. And finally, there's enough real data to answer them.
For those of us building and deploying these systems, that's not just an exciting moment.