1. A Systems Of Record Shakeout

The dominant software systems in healthcare (think EHRs, CRMs, QMS) have long been the "systems of record” (SoR). That’s where the work gets done and the data lives. SoRs were fundamentally created to mirror workflows, and inadvertently started to dominate them. Now, "systems of action" (SoA) are emerging as overlays that allow work to flow more naturally, including fundamentally rethinking workflows. The key questions are: will these systems of action get absorbed into the system of records, or will they become the new center of gravity? We believe that SOAs will win where they unite workflows currently stretching multiple SoRs/paper and where they can generate unique data sets - with the specific answer likely varying by market depending on the incumbents’ strength, tech orientation, system and customer fragmentation, and more.

2. Labor Productivity Supercharged

AI is automating (white-collar) work across providers and life sciences, and is now increasingly being adopted by payors. For example, we see dramatic changes to workflows in revenue cycle management, utilization management, and hub services. And, we don’t believe this will necessarily mean fewer jobs. Rather, we will see an era of abundance where we can do more than was ever cost-effective before. Clinicians working at the top of their license. Admin teams processing 10x the volume. It will lead to massive gains in labor productivity and the emergence of agentic and hybrid workforces. We are seeing the line between services and software rapidly blur (and not mattering). And we will see both first order business directly driving productivity gains as well as a generation of infrastructure companies emerge.

3. Unbundling of Insurance

In a world of high deductibles and ever rising premiums, consumers are saddled with multiple thousands $ in out-of-pocket spend before insurance kicks in. How do we enable folks to access healthcare affordably in such a world? What are the offerings and infrastructure that is required? New savings vehicles, payment options, provider models, and preventive care offerings. We're looking for businesses that help consumers navigate healthcare when insurance doesn't cover the first dollar.

4. Payments Shift To Real Time

Healthcare payments are complicated, intransparent, and after the fact causing long delays, uncertainty, and endless back-and-forth. We believe that payment will "shift left" meaning knowing what you owe before the visit and getting paid in milliseconds, not months. This reduces waste, frees up working capital, and lets consumers actually shop for care. RCM and payments have been a special focus for BHI from Day 1. We're continuing to invest across the payment infrastructure stack (including RCM, payment integrity, fiduciary compliance for employers).

5. The Algorithmic Medicine Stack

AI is getting good enough to support clinical decision-making, and to make clinical decisions (see ARPA-Hs ADVOCATE program, for example). This doesn’t mean replacing doctors, but rather augmenting routine decisions. This unlocks productivity and creates opportunities to improve care for millions of people (think: rural care, for example), but also raises new questions: What tools do we need to evaluate and surveil clinical AI? How are we reimbursing and paying for it? We're interested in both first-order applications and second-order enabling infrastructure.

6. The R&D Automation Wave

Automation and AI already make an impact on discovery. Yet clinical development and clinical operations, i.e., the space between discovery and commercialization, have remained manual, bespoke, and artisanal. We’re seeing this change now. Leaders are fundamentally rethinking trial design, protocol optimization, and the bridge from science to scaled manufacturing. The FDA just added fuel to the fire by opening the door to Bayesian approaches and thus modern statistics. As a result, clinical dev, clinical ops, and scale-up will look radically different in 10 years. Not just automated, but scaled and high frequency. Our portfolio company Quant Health exemplifies this: they help biopharma simulate hundreds of clinical trials in silico before running a single real one. What once took years and millions now happens computationally.

7. A New BioPharma Commercial Model

Biopharma commercialization will operate quite differently in 2040. Commercial leaders are exploring new avenues from direct-to-patient models (see also theme 3 ‘unbundling of insurance’), find new and more effective ways for HCP engagement, and are thinking about the future of the field force. BioTech sales leaders are exploring AI sales forces. Market access teams are navigating ever-more-complex contracts, often quite manually. Patient Services leaders are exploring the power of innovative payment models and AI automation. And everyone is asked to find savings. Together, these factors will drive the emergence of new commercial models.

We're eager to meet founders and leaders building in these spaces. If you're working on something that fits these themes (or if you want to challenge them), we'd love to hear from you.

Thanks to those who directly contributed (Andrea Coravos Manuela Thomys) and all of the founders, operators, and experts who inspired our thinking through countless conversations.