Closing the AI Adoption Gap in Healthcare

Taco Thursday. The phrase I heard at a health leadership conference last month that I cannot get out of my head: "Think like a human, act like an agent." A health tech vendor said it about their AI platform. The audience nodded. Nobody asked what it meant. Here is what it should mean: AI tools in clinical settings need to process information at machine speed and output decisions in a format a clinician can act on without additional translation. That is hard to build. Most of what gets sold does not do it. Here is what it usually means in practice: the vendor wants you to feel comfortable while they replace a clinical workflow with something that has not been validated in your patient population. The difference between those two things is the only due diligence question that matters: does this tool fit the actual workflow, or does it require the workflow to fit it? AI type matters less than fit. Fit matters less than governance. Governance matters less than accountability. Start with accountability. What is the best (or worst) AI product pitch line you have heard this year? Drop it below.

Experience management firm Qualtrics has completed the acquisition of healthcare experience business Press Ganey Forsta for $6.75bn: https://lnkd.in/e8DcDYj5 #mrx

The way consumers decide to seek care is shifting, and many of those decisions are now happening before anyone clicks a website. Patients are increasingly arriving with AI‑informed questions about symptoms, urgency, and next steps. That dynamic has real implications for how health systems show up, communicate clearly, and support informed decision‑making long before care begins. I’m looking forward to joining a panel at The Health Management Academy’s CMO Forum & Consumer Collaborative (June 3–5, Carlsbad, CA) to discuss what the move from SEO to AEO means in this new, AI‑influenced decision journey. My role isn’t clinical, but I’ve been learning directly from providers ahead of this conversation to understand better what they’re seeing today and to connect that perspective with the digital and AI shifts shaping consumer behavior. As co‑leader of the Cone Health Office of Experience, I see this as a human experience issue as much as a growth one. As AI is influencing decisions upstream, experience needs to be intentionally designed earlier, with a clear focus on guiding people to the right care at the right time in support of value‑based outcomes. Looking forward to the dialogue.

Big moment for Advantage! Excited to see Bethany Miles step into the Chief AI Officer role, a well-earned move at exactly the right time for where we’re headed. What stands out most is the impact her leadership has already had. Over the past several months, we’ve moved from being a tech-first enterprise to an AI-accelerated enterprise, driving faster decisions, removing friction from our workflows, and putting better insights into the hands of our teams. That shift doesn’t happen without strong leadership, clear vision, and the ability to execute at scale. Beth has been at the center of that. I’m excited to continue working alongside her as we push this next phase forward, scaling AI across the business, unlocking real value, and building a more intelligent, faster organization. Big congratulations, Beth.

Advantage Solutions, the partner of choice for the world’s leading brands and retailers, is doubling down on our position at the forefront of AI-powered commerce.   Today, we’re pleased to announce the appointment of Bethany Miles as Chief AI Officer, reporting to our CEO.  Prior to joining Advantage, Beth spent more than a decade leading technology and corporate transformation at global software firms, including senior roles at Sage and Cerner (now Oracle Health). She will lead our enterprise AI strategy: embedding AI across operations, sharpening the insights we deliver to clients, and building the capabilities that drive measurable performance for the brands and retailers we serve.   This appointment reflects a deliberate investment in the leadership, talent, and infrastructure needed to turn AI into a durable advantage for Advantage and for our clients.   #TeamADV #AILeadership

What does it say about a system when 75% of the work is cleanup?  According to Healthcare Financial Management Association (HFMA)'s new report, revenue cycle teams currently spend three-quarters of their time fixing problems created upstream. Only 25% is preventative. Their survey of 95 healthcare finance professionals shows both the scale of the opportunity and the distance still to close. McKinsey projects AI could reduce cost to collect by 30–60%. But just over 7% of organizations describe their teams as "very prepared" for what that transition requires. The leaders getting this right are learning a hard lesson early: AI layered on top of a broken process doesn't fix it. Mayo Clinic's revenue cycle chair said it directly — you never put automation on top of broken workflows or undertrained staff. The organizations positioned for this shift are building toward prevention, not reaction. Fewer vendors. Upstream problem-solving. Workflows designed for accuracy before automation is applied. The RCM market is projected to nearly quadruple by 2030. Getting there depends less on which AI tools health systems adopt and more on whether they build the right foundation underneath them. Full story here: https://lnkd.in/gaVmiBqg

Friday traditions carry on – let's dive in! We continue our Friday series where we review and announce studies that we find interesting and that we recommend investors and founders pay attention to. Today, we will be providing an overview of the paper “Gen AI amplified: Scaling productivity for healthcare providers” published by Accenture. The healthcare industry is facing a crisis that no amount of traditional hiring or training can solve. Demand is surging as the population ages, with the number of people aged 60 to 90 expected to grow by nearly half over the next two decades. At the same time, the workforce is shrinking at an alarming rate. The United States alone is projected to face a shortage of up to 139,000 physicians by 2033, while nearly 900,000 registered nurses are expected to leave the profession by 2027. Globally, the nursing shortfall could reach 13 million. However, 70% of healthcare workers' tasks could be reinvented through automation or augmentation, not by replacing humans but by giving them time back to focus on what only humans can do. In nursing alone, automation could free up one-fifth of repetitive, lower-complexity tasks, unlocking nearly $50 billion in annual value in the United States. Much of this opportunity lies in language-based work. Roughly 40% of the healthcare industry's total working hours are devoted to tasks like clinical documentation, note summarization, inbox management, and appeals processing. Of that, 17% can be fully automated and another 23% can be augmented by AI working alongside clinicians. However, a dangerous gap has emerged between ambition and action. While 83% of healthcare executives are piloting generative AI in pre-production environments, fewer than 10% are investing in the infrastructure necessary to support enterprise-wide deployment. Only half of IT executives in healthcare report strong alignment between technology initiatives and overall business strategy, which leads to poor conversion of funded pilots into real-world impact. The report outlines what healthcare providers must do to move from pilots to scale. First, they need to build a reinvention-ready digital core that integrates cloud platforms, seamless data access, and strong governance. Second, they must strengthen data quality and strategy, because generative AI is only as reliable as the data it learns from. Third, responsible and secure AI deployment must be embedded from the beginning, with continuous monitoring, tailored large language models, and a workforce trained in safe AI use. Our Venture Builder is looking for projects in the digital health market and is ready to help founders develop them. If you have such a project, please send your investment deck to us hello@4pmventures.com

#HMPS26 day 1: Budget Cuts and AI Impact Over the past 2 years, 68% of healthcare CMOs are dealing with budget cuts, 52% with staff reductions. Most marketing teams are being asked to do more with less Leaner teams. Tighter budgets. Three ways to be budget-saavy: - Align marketing priorities directly with executive priorities - Stop acting like an order-taker, operate as a growth partner - Scrutinize spend like finance would But the bigger opportunity is being overlooked: Most organizations are still over-indexing on acquisition Meanwhile: Existing patients are ~80% cheaper to reach They represent ~90% of your actual base Activation existingn patients is under-leveraged. If you want to prove ROI to the C-Suite: - Use control groups (the golden standard) - Prove incremental impact - Stay conservative on attribution Then there’s AI Patients are learning without visiting your website They’re getting answers from AI summaries first They show up later. More informed. Harder to influence. Your website is no longer just for humans: it also needs to be interpretable by machines At the same time, teams are adjusting internally: - AI is accelerating content, analytics, workflows - Governance is emerging, but often slowing progress - Teams are moving from pilots to scaled use cases Curious how others at HMPS are thinking about this Where are you seeing the most pressure right now? Thanks to the speakers who shaped these takeaways: Jim Blazar, David A. Feinberg, Andrew Chang, Suzanne Bharati Hendery, MA, APR, CPXP, Hernando Ruiz-Jimenez, Don Stanziano, Chris Boyer, Vanessa Hill, Jessica Holton, Mark Bohen, Kathy Smith, Rose Glenn, Tom Lawry, Blaze DiStefano, John Davey, Travis Waters, Bryce Cannon, Aaron Watkins

"This type of transformation isn’t just happening at large health systems. Across the country, hospitals of all sizes are accelerating revenue cycle technology adoption, driven largely by AI advancements. " https://lnkd.in/guKkCBB8

AI Pricing Optimization in Healthcare: Transforming Financial Strategy for CFOs In today’s rapidly evolving healthcare landscape, CFOs face the dual challenge of managing costs while maximizing revenue streams. AI-powered pricing optimization is emerging as a game-changer, enabling healthcare organizations worldwide to set more accurate, dynamic pricing models that reflect market demands, patient demographics, and regulatory frameworks. Recent advancements in AI algorithms allow real-time analysis of vast datasets—from historical billing records to competitor pricing and patient outcomes—unlocking opportunities to enhance price transparency and patient satisfaction without sacrificing profitability. According to a 2024 report by Deloitte, healthcare providers implementing AI-driven pricing strategies have seen an average revenue increase of 7-12% alongside improved operational efficiency. For CFOs, the integration of AI in pricing means not only smarter pricing decisions but also enhanced forecasting capabilities and risk mitigation. This strategic approach supports better contractual negotiations with insurers and drives financial sustainability amid shifting reimbursement models and rising care costs. Are you leveraging AI to optimize pricing in your healthcare organization? What challenges or successes have you encountered? Let’s discuss how CFOs can harness AI to redefine financial leadership in healthcare. #HealthcareFinance #AIinHealthcare #PricingOptimization #CFOInsights #NewGenIT.ai