What Actually Needs Building: Ten Healthcare Companies for 2026
Abstract
The healthcare investment landscape entering 2026 reveals clear consensus around several fundamental shifts despite surface-level disagreement on timing and magnitude. Major themes emerging from year-end reviews include the maturation of AI from experimental to operational deployment, the breakdown of traditional payment models creating monetization opportunities, the collision of consumer expectations with legacy infrastructure, and the persistent reality that software alone cannot fix broken workflows. This synthesis identifies ten specific company archetypes that thread through multiple investor theses: revenue cycle automation that captures real cash for providers, clinical decision support that reduces liability exposure for physicians, logistics platforms for specialty pharmacy, API infrastructure for prior authorization, ambient documentation that actually works in specialty settings, patient acquisition engines for elective procedures, care navigation for Medicare Advantage plans facing margin compression, AI coding compliance tools, longitudinal care coordination for behavioral health, and workforce optimization software for non-physician providers. Each opportunity represents a clear buyer with an acute pain point and measurable ROI, validated by current market behavior rather than hypothetical future states.
Key Themes from 2025 Year-End Reviews
- AI deployment moving from pilots to production with clearer ROI metrics
- Payment model disruption creating monetization windows (GLP-1s, Medicare Advantage margins, specialty pharmacy)
- Infrastructure plays around data movement and API standardization gaining traction
- Clinical workflow automation showing actual time savings in specific use cases
- Consumer expectations forcing transparency and convenience upgrades
- Regulatory environment creating compliance technology opportunities
- Behavioral health and specialty care coordination emerging as priority areas
- Workforce shortage driving non-physician provider enablement tools
Market Signals Validating These Opportunities
- Provider systems cutting vendor contracts while increasing spend on automation
- Payer margins compressing forcing efficiency plays and care management investments
- Specialty pharmacy volume growing 15-20 percent annually with logistics bottlenecks
- Prior authorization volumes up 30 percent creating API infrastructure demand
- Elective procedure volumes recovering but patient acquisition costs rising
- Medicare Advantage plans scrambling for care coordination tools as Star ratings matter more
- Medical coding compliance becoming existential risk as audits intensify
- Psychiatry and specialty practice no-show rates hitting 25-30 percent
The Ten Companies That Need Building
Revenue cycle automation capturing actual cash
Clinical decision support reducing malpractice exposure
Specialty pharmacy logistics and patient support
Prior authorization API infrastructure and workflow tools
Ambient documentation for specialty practices
Patient acquisition and conversion for elective procedures
Care navigation platforms for MA plans
AI-powered medical coding compliance
Longitudinal behavioral health care coordination
Workforce optimization for nurse practitioners and physician assistants
The Consensus Nobody Wants to Admit
Reading through a dozen year-end healthcare predictions from investors ranging from early stage specialists to growth equity firms to strategic consultancies reveals something genuinely interesting. Everyone agrees on the same fundamental shifts while carefully hedging their language to sound differentiated. The consensus position has become that AI will matter enormously but probably not as fast as everyone hoped six months ago, that payment models are breaking in ways that create actual business opportunities rather than thought experiments, and that the companies winning right now are solving very specific workflow problems rather than reimagining healthcare from first principles.
Townhall Ventures puts it plainly when they note that 2026 will be the year healthcare AI moves from science projects to actual deployments with measurable outcomes. They are not alone. Bessemer predicts AI scribes will be table stakes by end of year. Seven Wire expects ambient documentation to hit critical mass. The pattern holds across every major thesis. Everyone spent 2024 funding experimental AI companies and watching pilots that showed promise but limited scale. The shift for 2026 involves backing companies that can demonstrate concrete savings or revenue increases within 90 days of implementation.
What makes this consensus interesting rather than boring involves the specific mechanisms people expect to drive results. Sequoia argues in their rethinking people spend piece that the real opportunity lies not in replacing humans but in making expensive humans more productive. A16z counters that the breakthroughs will come from AI agents that can actually complete entire workflows without human intervention. Both camps agree that healthcare workflows are wildly inefficient and ripe for automation. They just disagree on whether the path forward runs through augmentation or replacement.
The payment model discussion reveals similar underlying agreement wrapped in different framing. Multiple sources highlight GLP-1 medications as a forcing function that will reshape obesity care delivery, diabetes management, and downstream chronic disease prevention. EY and Deloitte both point to Medicare Advantage margin compression as an existential crisis forcing plans to find new ways to manage costs. PitchBook notes that fee-for-service is dying faster than anyone expected, with bundled payments and value-based arrangements growing 40 percent year over year. The common thread suggests that companies solving acute payment problems for specific stakeholders will find eager buyers in 2026, while companies still pitching the promise of value-based care will struggle.
The infrastructure conversation follows a predictable pattern where everyone agrees that data interoperability remains terrible and that APIs will matter more, but nobody can quite articulate which specific data movement problems are worth billions versus millions. Bessemer talks about the need for better prior authorization infrastructure. A16z highlights the continued importance of healthcare data platforms. Seven Wire predicts that synthetic data generation will become critical for AI training. These are all correct observations about real problems. The challenge involves figuring out which infrastructure plays have actual business models attached rather than just solving annoying technical problems that nobody will pay to fix.
Consumer expectations creating forcing functions represents another consensus position that manifests in different ways depending on who is writing the prediction. MedCity News quotes VCs predicting that patients will demand Amazon-like convenience in healthcare. Chief Healthcare Executive highlights how AI-powered chatbots will become standard for patient communication. Hospitalogy notes that transparency requirements will force price visibility across the system. The unifying insight suggests that healthcare has run out of rope on the consumer experience dimension and that companies making it meaningfully easier for patients to access and navigate care will capture disproportionate value.
What nobody wants to say directly but everyone implies involves the recognition that most healthcare innovation over the past decade solved problems that did not matter very much or created new problems worse than the ones being fixed. Digital health had its moment. Telehealth proved useful for some things and actively harmful for others. Remote patient monitoring generated lots of data that nobody knew what to do with. Care navigation created another layer of bureaucracy between patients and care. The companies that will win in 2026 are the ones that learned from these expensive mistakes and are building tools that slot into existing workflows rather than requiring everyone to change how they work.
The timing question lurks underneath every prediction. Vinod Khosla says we are getting closer to AI-powered healthcare and gives it another five to ten years before general purpose medical AI assistants can replace most routine physician work. Others argue the transformation is already happening and will accelerate dramatically in 2026. The reality probably splits the difference. Narrow AI tools that do one thing extremely well in a specific clinical context are already showing value. General purpose AI that can reason across complex medical problems and make high-stakes decisions remains further out. The companies that need building in 2026 should focus on the narrow applications with clear ROI rather than swinging for transformational breakthroughs.
Revenue Cycle Automation That Captures Actual Cash
