Why AI Matters in Healthcare

Artificial intelligence is reshaping healthcare, and Barclays’ latest thematic report (March 2025) frames both the promise and the practical realities of this transformation. The report maps 50 AI applications across the healthcare value chain and highlights more than 35 public companies poised to benefit.

The healthcare sector faces pressing challenges: workforce shortages, rising costs, and demand for more personalized care. With the WHO projecting a shortfall of 11 million healthcare workers by 2030, AI could help close the gap through automation, improved scheduling, and clinical decision support. The National Bureau of Economic Research estimates AI adoption could save the U.S. healthcare system 5–10% annually—over $200 billion.

AI promises dual benefits: better patient outcomes and improved business efficiency. Unlike traditional cost-cutting, AI-enabled optimization can reduce administrative burdens while expanding access to care.

Three Near-Term Focus Areas

Barclays identifies three areas likely to see the earliest adoption:

  1. Provider Care Optimization
    • Automating documentation, scheduling, and patient communications.
    • AI-powered clinical decision support and personalized treatment plans are expected to follow.
    • Companies like Oracle (Cerner EHR integration) and Microsoft (Nuance DAX Copilot) are building healthcare-specific solutions.
  2. Medical Devices
    • AI-enhanced imaging dominates today, but expansion into monitoring, surgery, and hearing aids is accelerating.
    • Philips, Siemens Healthineers, Sonova, and GN Store Nord are among early movers.
    • FDA approvals of AI-enabled devices remain concentrated in imaging, but the addressable market is far larger.
  3. Drug Development
    • AI is already cutting time and costs in discovery and clinical trials.
    • Firms like Relay Therapeutics, ICON, and IQVIA use AI for target identification, trial design, and patient recruitment.
    • Efficiency gains could shrink the traditional 10-year, $2.6 billion development cycle dramatically.

Adoption Hurdles and Key Indicators

The path forward depends on four critical factors:

  • Regulation: Only 30 countries currently have binding AI-specific healthcare laws; the EU AI Act is among the most advanced.
  • Data Integration: With 80% of healthcare data unstructured, quality, interoperability, and privacy safeguards remain major challenges.
  • Patient & Provider Acceptance: Surveys show growing support, though trust hinges on transparency, informed consent, and safeguards.
  • Company Investment: Corporate spending on AI—through R&D, hiring, partnerships, and M&A—is a leading indicator of momentum.

Investment Landscape

Two avenues for exposure:

  1. Healthcare operators using AI internally – e.g., RadNet integrating AI into imaging centers, or ICON saving millions of hours through AI-enabled clinical trial tools.
  2. Companies offering AI-enabled products/services – spanning life sciences (Certara, Thermo Fisher), devices (Medtronic, Intuitive Surgical), pharmaceuticals (Roche, AstraZeneca), and tech enablers (NVIDIA, Microsoft, Oracle).

The report also notes venture-backed innovators like Xaira Therapeutics, Owkin, and PathAI, with potential IPO or acquisition opportunities.

AI in healthcare is still in its early innings, but the trajectory is clear. The near-term focus will be on efficiency gains, particularly in provider workflows and imaging. Longer term, the real value creation may lie in personalized medicine, preventive care, and novel therapeutics. For investors, monitoring regulatory maturity, data readiness, acceptance levels, and corporate investment will be key to identifying where adoption—and returns—will materialize first.

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