Innovation meets economic caution as life sciences leaders prepare for 2026, balancing investment and regulation in a shifting global market.
Step inside a life sciences boardroom heading into 2026, and you will hear inconsistencies. Leaders feel good about their own companies, but far less sure about everything else. Confidence, yes. Comfort, no.
According to Deloitte’s latest Life Sciences Outlook Survey, more than three in four biopharma and medtech executives say they are confident in their organizations’ financial prospects for the year ahead. Yet only 41% share that confidence when asked about the global economy. That gap is telling – not irrational optimism, but a kind of institutional compartmentalization. Companies trust their pipelines. They don’t trust the weather.
It is a split-screen moment for the industry: strong pipelines and innovation on one side, geopolitical tension, inflation and regulatory change on the other.
The industry has seen volatile years before, but this one carries a different texture: less about a single shock, more about overlapping friction – supply chains, tariffs, data governance, pricing controls, election cycles – all grinding at once.
The gap is shaping strategy. The year ahead is less about chasing growth at all costs and more about learning how to move fast while staying steady, making bold bets on technology while building the flexibility to absorb shocks.
Speed is still the point – but now it has to be controllable speed, like a centrifuge you can actually stop. That means modular operating models, diversified manufacturing footprints and “optional” commercial strategies designed to survive policy whiplash.
Optimism is not evenly distributed. Executives in Europe and Asia appear more upbeat than their US counterparts. Not because Europe and Asia are frictionless – but because some of the uncertainty in the US feels political, not cyclical. That’s harder to model and harder to hedge.
Around 90% of biopharma leaders in surveyed European and Asian markets describe their outlook for 2026 as positive or cautiously positive, and more than 80% expect revenue growth. In the United States, the mood is more mixed: just over half of biopharma leaders feel optimistic, while more than a quarter remain uncertain or negative [1]. The divergence reads like a map of perceived policy stability. Predictability is its own competitive advantage.
The differences in sentiments hint at how regulation, pricing rules and political stability – or the lack of it – are influencing how leaders plan for the year ahead. Boards are no longer asking: “Are we compliant?” They’re asking: “Will compliance change faster than our product cycles?” That is a very different kind of risk.
For many executives, regulation is no longer a compliance issue tucked away in legal departments; it is now a central strategic concern. Regulation has moved from the appendix to the spinal cord. It now shapes where you build, what you build and how quickly you can scale.
Outside the US, more than half of respondents point to national regulatory changes as a major factor shaping 2026 strategies, from new rules surrounding artificial intelligence (AI) in Europe to pricing reforms in China. Europe’s AI governance debate is forcing companies to think like aerospace engineers – audit trails, model transparency, system-level safety – even when the tool is “just” a clinical workflow assistant. That matters for aging research more than most sectors, because longevity trials often live or die on surrogate endpoints, digital phenotyping and real-world evidence – exactly the areas regulators are still learning to police.
In the US, leaders are watching shifts within the Food and Drug Administration (FDA) and the Department of Health and Human Services, as well as broader economic policies such as tariffs. Tariffs may sound like a macroeconomic footnote, but for medtech hardware, diagnostics and biologics supply chains, they can become an invisible tax on innovation – one that arrives without warning.
The result is a more cautious approach to pricing, portfolio choices and market entry. Companies are being forced to ask not just what they can build, but where and how it makes sense to sell it. And increasingly: whether a therapy, device, or platform can survive the reimbursement labyrinth – not only the science. Prevention is where the economics get weird. Longevity-adjacent interventions – metabolic resilience, immune rejuvenation, early disease interception – can deliver compounding value, but they still collide with reimbursement systems built to pay for acute episodes, not avoided futures.
If there is one theme that cuts across regions and sectors, it is AI. Nearly half of surveyed executives say accelerated digital transformation will significantly shape their organizations in 2026, a notable jump from last year. Generative AI, in particular, is now firmly on leadership agendas. For years, AI was treated like a moonshot. In 2026, it’s being treated like electricity – expected everywhere, invisible when it works, unforgivable when it doesn’t. For longevity and geroscience-focused teams, the AI promise is especially seductive – not because it writes emails faster, but because it can map the messy biology of aging into tractable biomarkers, stratify heterogeneous cohorts and shorten the distance between multi-omics signal and trial-grade endpoint.
Yet the enthusiasm comes with honesty. Only 22% of life sciences leaders say they have successfully scaled AI across their organizations, and just 9% report meaningful financial returns so far. For most, AI is still a work in progress. That’s the quiet headline: the industry is drowning in pilots and starving for production-grade systems. Scaling means governance, data harmonization, change management and clinical validation – the dull scaffolding that no one puts in the keynote slides.
“We’re all entering a period of purposeful transformation, where discipline and innovation must coexist as the industry matures beyond hype toward measurable productivity from AI and data,” said Gabriele Ricci, chief data and technology officer at Takeda Pharmaceuticals.
The hype cycle is ending – the integration cycle begins
What is changing is intent. Around 30% of respondents now cite interest in more advanced, autonomous AI systems – tools that can make decisions and perform tasks with less human input. Cybersecurity concerns are rising alongside these ambitions, reminding leaders that smarter systems also introduce new risks.
Autonomy raises the stakes: model drift, data poisoning, prompt injection and shadow AI use suddenly become board-level problems rather than IT annoyances. And when AI starts touching regulated decisions – trial enrollment, pharmacovigilance signals, diagnostic support – the liability surface expands fast.
Behind the technology push is a simple reality: life sciences is expensive, and it is getting more so. Costs aren’t rising in a neat line. They’re spiking in clusters – specialized talent, cloud compute, clinical operations, real-world evidence infrastructure.
For biopharma companies, improving research and development productivity remains the top lever for managing costs. With the average price tag of bringing a new drug to market now exceeding $2 billion [2], leaders are under pressure to develop therapies faster and more efficiently.
The $2 billion number isn’t just a statistic – it’s a forcing function. It pushes companies toward platform thinking, adaptive trial design, biomarker-led stratification and AI-supported hypothesis generation that can shave years off development timelines – less romance, more throughput.
In medtech, operational efficiency takes center stage, with nearly half of executives naming AI implementation as their main cost-containment strategy for 2026. For medtech, the AI story is often less about discovery and more about manufacturing yield, predictive maintenance, inventory accuracy and post-market surveillance – the unglamorous systems that decide the margin.
Pricing and market access also loom large. Roughly a third of leaders say contracting, reimbursement, and access will be significant areas of focus, often tied to regulatory change and supply chain risk. This is where health systems become the bottleneck. If payers and providers can’t metabolize innovation – financially, operationally, politically – even the best tech stalls. Access is the battlefield.
Despite the headwinds, growth is still very much on the agenda… just with a sharper focus. Selective growth, not just spray-and-pray.
Many organizations plan to lean into their own pipelines, launching new therapies, devices and digital platforms. Others are returning to mergers and acquisitions after a quieter period. Deal activity has already picked up, particularly in biopharma, as companies look to bolster pipelines and secure future growth. M&A is no longer just a pipeline patch – it’s a hedge against uncertainty, a way to buy optionality when internal timelines feel too slow.
Expect more “capability acquisitions” – data assets, platform tech, clinical trial infrastructure – not just molecule shopping.
AI is increasingly seen not just as a productivity tool, but as a growth engine. Not because it replaces humans, but because it reshapes the unit economics of R&D and commercialization – fewer dead ends, tighter segmentation, faster iteration. When it works.
“AI is already out of the box, and the speed at which innovation is moving will only accelerate,” said William Phillips, chief commercial officer of Terumo Neuro. The challenge, he adds, is whether regulation and healthcare systems can keep pace. This is the paradox of 2026: innovation can sprint, but institutions jog – and sometimes they don’t move at all.
As 2026 approaches, the life sciences industry stands at a crossroads. Confidence in science and innovation remains strong, but the external environment is anything but stable. Science is compounding. Policy isn’t.
The executives best positioned for the year ahead appear to share a common mindset: invest in AI with purpose, redesign how work gets done and stay anchored to the value delivered to patients. Purpose matters here because AI without a use case becomes corporate theater – expensive, impressive and ultimately disposable.
The winners won’t be the companies with the flashiest demos. They’ll be the ones with the cleanest data, the tightest governance and the courage to retire legacy processes that no longer serve patients.
“Agility and resilience matter, but our true purpose lies in uniting discovery with patient care,” says Simone Thomsen, president and general manager of Eli Lilly Japan. That is the real constraint: discovery without delivery is just a lab accomplishment. Delivery without trust is dead on arrival.
In an uncertain world, the combination of clarity and flexibility may prove to be the industry’s most valuable asset. Clarity about what you’re building, who it’s for and what evidence you’ll need. Flexibility about how you manufacture, how you price and how you navigate a fragmented regulatory landscape.
Adapt or freeze.
Photograph: RossHelen/Envato
[1] https://www.deloitte.com/us/en/insights/industry/health-care/life-sciences-and-health-care-industry-outlooks/2026-life-sciences-executive-outlook.html
[2] https://www.deloitte.com/ch/en/Industries/life-sciences-health-care/research/measuring-return-from-pharmaceutical-innovation.html
