From AI to Tariffs: What 2025 Taught Healthcare & Pharma About the Year Ahead

2025 was a year defined by anticipation—a landscape shaped less by what happened and more by what people feared might happen. Would rising tariffs disrupt hospital supply chains and compromise patient safety? Would AI-driven automation reshape clinical and administrative roles, triggering widespread job displacement?

In hindsight, 2025 may be remembered more for the hype surrounding transformation than for irreversible disruption. Yet beneath the noise, several meaningful signals emerged—those signals that will shape the operating environment for Healthcare and Pharma as we enter 2026.

Key Messages for 2026

• AI’s potential will become more visible with real-world applications finally moving beyond pilots into scaled, operational value. But this shift will bring intensified regulatory scrutiny, requiring stronger governance, bias mitigation, and transparency frameworks.
• Tariff-driven supply chain fragility remains a strategic risk. Volatility in trade policy is forcing organizations to revisit sourcing models, inventory strategies, and digital visibility tools to ensure resilience.
• Skills evolution, not job elimination, defines the workforce shift. Organizations increasingly recognize that AI augments rather than replaces clinical and analytical roles, moving the conversation from downsizing to capability-building.
• Data interoperability and trust emerge as competitive differentiators, driven by accelerated digital health adoption and sharper expectations for secure, patient-centric data sharing.
• Cost pressures and productivity demands continue to rise, pushing providers, payers, and pharma companies toward automation, integrated analytics, and new collaboration models to drive efficiency.

1. Nascent Nature of AI’s Application in Healthcare and Pharma

Despite rapid innovation, AI in healthcare and pharma remains early in its maturity cycle. Most organizations are still validating feasibility, assessing safety risks, and determining how AI can operate effectively within highly regulated environments.

Across the industry, companies are experimenting broadly but scaling cautiously:

• Novartis has run AI pilots in R&D—including molecule-design partnerships with Microsoft—yet many remain focused on data curation and model validation.
• Pfizer has pursued AI in clinical-trial optimisation and drug-target prediction, but deployments remain programme-specific rather than enterprise-wide.
• The NHS continues early-stage AI testing in care delivery (e.g., stroke detection, dermatology triage), though scaling is limited by integration complexity and governance requirements.

AI’s strategic promise spans the full value chain:

• AI-enabled molecular design could significantly compress R&D timelines.
• Predictive models can support earlier diagnosis and personalised treatment pathways.
• Generative AI can streamline regulatory documentation, safety reporting, and scientific summarization.

The vision is clear—exemplified by Pfizer’s accelerated COVID-19 vaccine development through AI, and Novartis’s ambition to become a “data science–driven” pharma company—but the full impact is still ahead.

Emerging evidence of value is becoming visible:

• Drug Discovery & R&D: AI-generated chemical structures; machine-learning immunogenicity prediction; partnerships with AI-native biotechs such as Insilico Medicine and Exscientia.
• Clinical Trials: AI-enabled patient stratification, predictive recruitment models, and automated protocol drafting.
• Diagnostics & Care Delivery: NHS accelerators supporting tools like HeartFlow for cardiac imaging and Moorfields Eye Hospital’s retinal AI, both progressing toward scaled deployment.
• Medical & Regulatory Functions: Generative AI for medical information responses, literature summarization, and pharmacovigilance narrative drafting.

Still, adoption remains uneven due to data-quality challenges, evolving regulations, and fragmented readiness across organizations.

Human Importance Remains — Quality, Safety, and Regulatory Oversight

Despite technological progress, human oversight remains indispensable:

• The FDA’s Good Machine Learning Practice (GMLP) stresses explainability, monitoring, and safety.
• The EMA has issued guidance on AI in medicines and clinical trials, emphasizing accountability and robust validation.
• NHS England mandates clinical safety cases and human-in-the-loop governance for AI deployment.

AI augments expertise—it does not replace clinical, scientific, or regulatory judgement.

2. Unintended Consequences of US Government Policy

Efforts to curb healthcare spending in the US, particularly via drug pricing reform and reductions in federal reimbursement have generated unintended consequences across global markets and domestic provider networks.

Stickiness of US Pharmaceutical Pricing

The move toward Most Favoured Nation (MFN) pricing, which benchmarks US reimbursement against international prices was meant to reduce domestic drug costs. Yet because the US remains the most profitable global market, manufacturers have little incentive to lower US prices; instead, they adjust pricing behavior abroad.

Pharma companies have:

• Maintained US list prices to preserve global margins.
• Increased or protected prices internationally to avoid low benchmarks affecting US reimbursement.
• Delayed launches in lower-price countries to prevent unfavorable reference pricing.

The result is persistent US pricing stickiness with elevated nominal list prices despite modest net-price movements through rebates.

US policy changes have driven upward pricing pressure globally:

• NHS England increased branded drug spending by 25%, partly due to rising global reference prices.
• EU member states face pressure to raise reimbursement ceilings as manufacturers resist low-price agreements that could influence US price anchors.
• Most US drug categories, excluding weight-loss drugs, have seen relatively stable pricing, reinforcing global pricing expectations.

Net effect: branded-drug prices are trending upward across major markets structural win for diversified pharma companies.

Hospitals Come Under Pressure from Both Cost and Revenue Angles

Reductions in Medicare and Medicaid reimbursement are directly straining hospital finances, compounding inflationary pressures on labor, supplies, and capital.

This has led to:

• Accelerated hospital closures, particularly in rural and underserved areas.
• Intensified cost-cutting, including workforce reductions and service consolidation.
• Rising M&A activity, as distressed hospitals seek stability through scale.

Potential reductions in Affordable Care Act subsidies threaten to increase:

• Insurance premiums, pushing more individuals to underinsure or go uninsured.
• Uncompensated care, as coverage gaps widen.
• Access disparities, with underserved populations facing delays in treatment and reduced access to medicines.

Together, these pressures threaten the financial sustainability of hospitals and contribute to widening health inequalities.

3. Healthcare and Pharma M&A is Hot but Masks Underlying Weakness

2025 saw a surge in Healthcare and Pharma M&A, creating a perception of sector strength and strategic momentum. Deal volumes and valuations rebounded sharply as Big Pharma sought to replenish pipelines ahead of looming patent cliffs in oncology, immunology, and cardiometabolic disease.

However, the underlying drivers reveal structural fragility rather than sector-wide confidence.

• Early-stage biotechs remain capital constrained, with high interest rates reducing access to venture and public funding.
• Big Pharma’s organic R&D productivity remains uneven, pushing companies toward defensive acquisitions rather than long-term innovation bets.
• Valuation resets have made distressed or undervalued assets attractive targets, creating more opportunistic than strategic dealmaking.

M&A momentum reflects stress in the innovation ecosystem—not strength.

China’s biotech sector is undergoing a notable shift however: from follower to emerging innovation leader. This evolution is reshaping global competition and deal dynamics.

Chinese biotechs are increasingly developing advanced therapeutics:

• Next-generation cell and gene therapies
• AI-enabled drug discovery platforms
• First-in-class oncology mechanisms targeting global markets

This marks a meaningful climb up the value chain with China’s position in M&A is evolving to both targets and strategic acquirers. 

5.2025 ultimately revealed an industry in motion, not yet transformed, but unmistakably shifting.

AI proved its promise while exposing deep gaps in capability, governance, and trust. Tariff volatility underscored the fragility of global supply chains. Pricing reform produced ripple effects that reshaped markets in ways policymakers did not intend. Meanwhile, a surge in M&A activity highlighted not just opportunity but the underlying fragility of the innovation ecosystem.

As healthcare and pharma enter 2026, the organizations that will lead are those that can:

• Turn early AI experimentation into scaled, governed, compliant value;
• Build resilient supply chains that absorb political and economic shocks;
• Invest in skills, data architecture, and operating models that enable speed and transparency; and
• Navigate geopolitical complexity while competing in a rapidly shifting innovation landscape.

The winners will not be the ones that predict disruption, but the ones that build the capacity to adapt to it—consistently, safely, and at scale.