Shape shifters

2026 life sciences trends – thriving in a converging, AI-driven industry

Life sciences begin 2026 in a familiar squeeze. R&D costs remain high, product life cycles are compressing and scrutiny is rising across markets.

Yet this year also brings renewed confidence, as organisations begin turning recent disruption into sustainable advantage.

AI is no longer confined to pilots. Supply chains are being redesigned around geopolitical reality. And the boundary between pharma, healthcare and technology is starting to look more like a shared border than a hard line.

Together, these shifts mean many organisations are rethinking not just what they invest in, but how they operate.

Enterprise AI is becoming a basic operating requirement across discovery, clinical development, manufacturing and commercial decision-making. Agentic AI and domain models are extending automation into workflows that once relied on manual coordination.

That scale changes the risk profile. Without strong controls, errors propagate quickly across interconnected systems. Leaders need to treat governance, model provenance, auditability and human oversight as the guard rails that enable speed, not barriers that slow it down.

Organisations that get this right are already seeing faster adoption and greater confidence in AI-driven decisions.

As AI becomes embedded, compliance moves from a final checkpoint to a design principle. The EU AI Act is raising expectations around transparency and accountability in high-stakes use cases.

In the US, the Inflation Reduction Act continues to reframe pricing, access and evidence strategy, with direct implications for portfolio planning. In Europe, the proposed Critical Medicines Act reflects a growing policy focus on supply security and local capability.

The practical response is not to build separate models for every market, but to assume divergence while standardising what can be standardised. Documentation, traceability and decision trails should be reusable assets, not bespoke work every time. This approach is helping organisations move with confidence rather than hesitation.

These regulatory and pricing shifts land just as patent cliffs and payer demands intensify. Defending value now depends on evidence as much as innovation. Market access needs earlier input into development plans, and medical, commercial and safety teams need a shared view of outcomes.

Here, analytics becomes a strategic discipline. Leaders can stress-test scenarios, prioritise investment and focus on programmes where differentiated evidence will matter most. Cost containment is not about spending less across the board.

It is about removing duplication so investment stays directed at the pipeline. In practice, this is freeing teams to focus on the assets with the greatest long-term potential.

None of this works without the right skills. Automation has not closed the talent gap in clinical operations, regulatory affairs, quality or advanced analytics.

The organisations that move fastest are building AI literacy across functions so teams know when to trust an output, when to challenge it and how to escalate issues. The goal is not fewer people, but stronger teams equipped to do higher-value work. This investment in people is emerging as one of the most powerful differentiators in 2026.

The skills challenge is most visible in clinical development, which is evolving into a continuous evidence engine.

Real-world evidence, AI-assisted design and decentralised trial methodologies are compressing timelines and improving patient-centricity, provided interoperability and governance keep pace.

This year will reward leaders who treat AI, regulation, cost, resilience and talent as one connected agenda.

Robin Curtis is a Strategic Advisor at SAS