Where AI dollars are reshaping healthcare

If the healthcare sector had a dating profile, its current interests would include long walks past stacks of regulatory paperwork, discussions of billing codes over a candlelit dinner, and partners with a serious commitment to artificial intelligence. The latter has become particularly irresistible, as venture capitalists poured $11 billion into healthcare AI last year alone. Unlike tech’s typical moon shots, this cash isn’t chasing holographic doctors or robot surgeons, it’s funding a quieter revolution in the industry’s least attention-grabbing corners—insurance forms, drug development math, and cybersecurity shields.

In 2024, one in every four dollars invested in healthcare ventures flowed to AI-driven companies—a 54% increase from 2023 levels. This surge reflects growing confidence in AI’s capacity to address systemic challenges, from cybersecurity threats to drug discovery bottlenecks. While biopharma AI continues to dominate headlines with its promise of accelerating therapeutic breakthroughs, the majority of capital (60%) is funneled into administrative and clinical optimization tools that deliver near-term returns.

Simultaneously, investors are seeding innovations in areas such as clinical trial design and electronic health record (EHR) interoperability, driven by regulatory tailwinds and the urgent need to mitigate rising operational costs. Below we highlight five key functions absorbing AI investment:

Cybersecurity

The February 2024 ransomware attack on Change Healthcare—which disrupted close to 40% of U.S. claims processing—accelerated investments in AI-powered threat detection. More than half of respondents reported an increase in cybersecurity spending by their organization (survey). For those organizations spending more on cybersecurity, 57% are adding new tools, including AI-enabled ones, to shore up their defenses.

The 34% of survey respondents who confirmed their organizations are deploying AI cybersecurity technology have good reason to do so. Healthcare organizations leveraging security AI and automation could identify and contain data breaches nearly 100 days faster than those who don’t employ AI, according to IBM’s 2024 Cost of a Data Breach Report. Time isn’t the only thing they saved—healthcare organizations lost $2.22 million less per data breach on average, a 45.6% difference, when they deployed AI and automation resources evenly across key cybersecurity functions (prevention, detection, investigation, and response).

Prior Authorization and Claims Management

At 60%, administrative and clinical use cases account for the largest share of healthcare AI funding, as they face fewer regulatory hurdles compared to clinical tools. Investors prioritize solutions that streamline prior authorization, claims adjudication, and revenue cycle management (RCM).

Electronic Health Record (EHR) Interoperability

A critical differentiator for administrative AI startups is compatibility with dominant EHR systems like EPIC, which holds nearly 40% market share among U.S. providers. Companies offering AI tools that integrate seamlessly with EPIC’s ecosystem—such as ambient documentation assistants or predictive discharge planners—secure preferential access to health system clients.

At the same time, EPIC itself continues to make a substantial investment in AI technology across its platform, leading to benefits such as improved clinician workflows, enhanced patient experiences, and streamlined revenue cycle processes. The company’s efforts include collaboration with tech giants such as Microsoft to help it optimize AI implementation.

Mega-Deals and Therapeutic Advancements

The biopharma AI sector secured $5 billion in venture capital (VC) funding in 2024, representing a 300% year-over-year increase and surpassing 2021’s peak by nearly $2 billion. This growth is propelled by “mega-deals” exceeding $100 million, which accounted for 71% of total biopharma AI investment. Companies leveraging machine learning for target identification, compound screening, and clinical trial design are attracting outsized checks, particularly in oncology and central nervous system disorders—areas with high failure rates and complex biological mechanisms.

 Clinical Trial Optimization

AI’s role in clinical research extends beyond drug discovery. Sponsors and contract research organizations (CROs) are deploying algorithms to enhance trial design, patient recruitment, and endpoint analysis. This year, 823 Phase I and 1,102 Phase II trials are slated to begin, with AI tools increasingly used to stratify participants using real-world data and optimize dosing protocols.

However, macroeconomic headwinds—including potential regulatory shifts in the wake of the 2024 U.S. elections—have tempered investment growth in traditional trial infrastructure, redirecting capital toward AI-driven efficiency gains.

Balancing Promise and Pragmatism

The AI investment landscape in healthcare reflects a nuanced calculus: while breakthroughs in drug discovery capture the imagination, the bulk of capital flows to applications delivering measurable, near-term ROI. Administrative AI’s dominance underscores health systems’ urgency to reduce overhead amid labor shortages and margin pressures.

However, the next phase of growth hinges on overcoming adoption barriers—clinician trust, interoperability hurdles, and equitable access—to unlock AI’s full potential. As generative models mature and regulatory frameworks evolve, 2025–2030 could see a rebalancing toward clinical AI tools that enhance both efficiency and outcomes, provided investors sustain patience amid healthcare’s long innovation cycles.