Tech Trends 2026: Takeaways for the biotech sector

At our Tech Trends event, we heard from leading technology journalists Madhumita Murgia, Financial Times, Mark Selman, The Times, Natasha Bernal, Wired and Rory Cellan-Jones about what they expect to be big in tech this year.

For the biotech sector, while everyday AI applications face growing pressure to justify their value, Here are our key takeaways:

From AI implementation to evaluation

The most consistent feeling from every panellist, was growing apprehension around an AI bubble. One speaker characterised 2025 as the year of “implementation”, with 2026 shaping up to be the year of “evaluation”. Organisations will increasingly question “are we actually seeing value from our AI investments?”

High valuations will need to be justified by demonstrable progress. Yet in biotech, where clinical development can take years, that progress is rarely linear or immediately visible. As a result, clear and credible communication on scientific progress, pipeline development and partnerships will grow in importance to sustain confidence and demonstrate long-term value well before products reach the market.

Beyond Generative AI, towards R&D

The panel was unanimous that the most meaningful innovations lie beyond Large Language Models (LLMs). Many of today’s models are good at analysing the past, but less capable of engaging with the complexity of the real world.

The panel suggested that the next phase of AI development will depend on spatial intelligent systems that can learn through interaction, drawing on a broader range of inputs rather than relying solely on static datasets.

The breakthroughs on which science depends, like developing new drugs, finding cures for currently incurable diseases and discovering novel materials, are – argued our panel – out of reach for most of today’s LLMs. Where AI can be marred by scepticism and fatigue of surface-level AI gains, biotech’s truly transformative use cases may offer some of the clearest proof of AI’s long-term value.

The clash of AI models: open vs closed source

The panel also touched on the geopolitical dimensions of AI, with the global race increasingly shaped by two competing ideologies: open versus closed-source models. While the US is dominated by proprietary systems, China has leaned into open and freely available models. As of 2025 the majority of the world’s top ten open-source AI models are Chinese.

If the West remains overly reliant on closed systems, there is a risk that the most fertile environment for R&D innovation will emerge elsewhere. Open-source AI offers clear advantages for biotech research: it democratises access to advanced tools, enables collaboration across research silos and can ultimately accelerate discovery in drug development and genomics.

The UK sovereign AI

At the same time, as the UK and US “special relationship” looks more and more unpredictable, the UK’s reliance on US-based AI infrastructure is becoming harder to ignore. In the 12 months to October 2024, 87% of the total acquisition value of Cambridge life science and tech companies came from US buyers. One panellist suggested that while ownership can feel inconsequential when alliances are strong, in the event of a more serious UK- US “divorce”, the importance of ownership will shift.

That said, panellists were clear that the UK is not lacking in scientific talent or capability. The challenge is retention, not innovation. There are strong proof points that groundbreaking AI-driven innovation can be built and scaled in the UK. Pioneering companies such as (Brands2Life client) Basecamp Research demonstrate how UK-based teams are applying AI in genuinely novel ways, recently achieving a world-first in AI-programmable gene insertion.

To truly hold on to more of these businesses long term, UK government policy will need to focus not just on fostering innovation, but on enabling startups to scale at home.

Communicating progress effectively

What the Tech Trends discussion made clear is that 2026 will bring both rapid AI advancement and sharper scrutiny of whether that progress delivers real-world value.

In biotech, where tangible outcomes can be years away, the ability to communicate progress clearly and credibly is essential to maintaining investor confidence and public trust. Strategic communications can help translate complex, long-term science into compelling narratives that demonstrate momentum, keeping stakeholders informed and engaged as innovation unfolds.