What’s Slowing AI Adoption in Healthcare?

Good morning, ! This week we’re diving into the $14B sports medicine market, why trust remains the biggest barrier to AI adoption in healthcare, and how adoption is evolving differently across healthcare verticals. 

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DATA DIVE

From Sidelines to Center Stage

The Sports Medicine market is quietly becoming one of healthcare’s more dependable growth stories. Valued at $6.4B in 2025, it’s projected to nearly double to $14B by 2035—an 8.1% CAGR that’s less hype, more structural tailwind.

What’s driving it? A mix of rising injury rates, aging-but-active populations, and a global shift toward preventative care. Notably, higher spend per patient—via minimally invasive procedures and advanced devices—is doing as much heavy lifting as volume.

Regionally, North America (47%) still dominates, but Asia-Pacific (16%) is emerging as the growth engine.

Bottom line: This is no longer a niche. It’s a scaled, fragmented market—making it prime territory for platform plays and consolidation. (More)

HEALTHTECH CORNER

AI Becomes Healthcare’s Operating System

Healthcare AI is graduating from pilot mode to core infrastructure. Today, it touches less than 15% of the market—but that’s expected to surpass 30% by 2030. The shift isn’t incremental; it’s systemic.

Adoption is being led by MedTech (~45%), where imaging, diagnostics, and device analytics are already AI-native. Close behind, consumer health, digital health, and services (~40%) are scaling quickly as care moves closer to the patient.

Meanwhile, pharma, payers, and providers (~30–35%) are moving slower—less due to skepticism, more due to regulation and legacy infrastructure.

The result: a two-speed market where AI is either a competitive requirement or an untapped edge.

Bottom line: AI is no longer a feature—it’s becoming the backbone of healthcare delivery. (More)

PRESENTED BY EXACT INSIGHT

Traditional expert calls were built for access. PE needs more than access.

One-off expert calls can be useful. But many PE workflows require more than a single conversation.

Commercial diligence, market sizing, operator validation, and portfolio monitoring often depend on research that is not only fast, but also verified, repeatable, and scalable. That is where the traditional model starts to break down.

Exact Insight helps solve that with invitation-only panels, AI-powered matching and fraud detection, human verification, and 80%+ recontact success, giving firms the ability to build on prior research instead of starting from zero each time.

This is not just expert access. It is Data Quality as a Service for Private Equity.

COMPLIANCE CORNER

Outsourced Vendor Oversight Is the Compliance Frontier in 2026

Regulators increasingly hold healthcare organizations accountable for the compliance of outsourced services from clinical operations and billing to technology platforms and offshore support. Federal agencies, led by OCR and FDA, demand documented, risk-based supervision of third parties, underscoring that delegated functions do not delegate accountability.

HIPAA's evolving Security Rule requirements emphasize thorough vendor risk assessments, multi-factor authentication, encryption, and continuous monitoring, especially for vendors handling protected health information. The FDA's new Quality Management System Regulation, effective February 2026, mandates stringent oversight of device-related and technology suppliers through supplier audits and documented risk management aligned with ISO standards.

For billing vendors, compliance risks carry steep financial penalties under the False Claims Act, making robust documentation and independent audits critical. Offshore vendors bring additional scrutiny given expanding cyber threats and complex cross-border regulations.

Bottom line: Healthcare leadership must implement full lifecycle third-party risk management, integrating legal, clinical, IT, and procurement teams. Regular audits, centralized risk data, and timely contract updates are non-negotiable to meet intensifying federal and state expectations in 2026. (More)

COMPETITIVE LANDSCAPE SNAPSHOT

TREND TO WATCH

Healthcare AI Has a Trust Problem, Not a Budget Problem

Generative AI enthusiasm across healthcare remains high, but executive priorities are shifting from experimentation to risk control. According to McKinsey, the top concern among U.S. healthcare leaders is model inaccuracies, bias, and flaws, cited by 66% of respondents. That outranks security risks (60%), regulatory compliance (52%), and ethical/privacy concerns (49%).

The message is clear. Healthcare leaders are not primarily worried about adoption. They are worried about reliability. In most industries, imperfect AI can create inconvenience. In healthcare, it can create denied claims, missed diagnoses, workflow disruption, or liability. That raises the deployment bar materially higher than in retail, finance, or media.

This also explains why many provider systems remain stuck in pilot mode. Boards may approve AI strategy, but operational leaders need evidence that outputs are accurate, auditable, secure, and compliant before scaling into clinical or administrative workflows.

For investors, the implication is important. Value is likely to accrue less to broad AI wrappers and more to infrastructure players solving validation, governance, security, and workflow integration. For operators, 2026 may become the year healthcare shifts from buying AI tools to buying AI assurance.

Bottom line: In healthcare, trust is becoming the real adoption curve. (More)

"The secret to getting ahead is getting started."

Mark Twain