Biopharma’s AI rally: Readiness not hype in 2025

The drumbeat of AI advancements over the last year has left us all breathless, wondering which benchmark will be broken next and which new problems we can solve in biology. But the promise of AI in biopharma is equally tempered by the long journey ahead and the technology’s many uncertainties.

For this year’s State of Tech in Biopharma report, we were deeply curious about what’s happening behind the scenes — how companies are actually adopting AI and the related technologies that feed an AI-driven strategy. Across large and small biopharma alike, the picture emerges of an industry that’s grappling with AI readiness, figuring out how to adapt its culture, tech, and systems to enable the use of AI at scale. In 2025, the story will not be about AI hype, it will be about AI readiness.

Large biopharma: Betting big on AI

The full benefits that AI can bring to drug discovery and the R&D lifecycle are still emerging, but large biopharma isn’t taking a wait-and-see approach. AI adoption among large biopharma is nearly three times that of smaller companies (67% vs 23%), and AI/ML ranks as their second-highest investment priority for the next three years, just behind R&D data platforms. This commitment reflects senior leadership’s belief in AI’s transformative potential: half of large biopharma respondents report top-down initiatives driving AI/ML adoption, compared to just 28% at small biopharma.

In 2025, we can expect to see large organisations — equipped with significant resources and benefitting from their scale — further integrating AI to reduce time to milestones and accelerate discovery pipelines. At the same time, large biopharma’s scale is a double-edged sword. Large biopharma organisations are working amidst a labyrinth of custom-built and disconnected software, data silos, and systems whilst they centralise and structure data for AI/ML. But they’re highly motivated to tackle these data and systems’ challenges, driven by the belief that AI will have material impact on speed: three-quarters of large biopharma respondents anticipate significant impact on time to milestone within 12–24 months if AI is fully deployed across their organisations.

Small biopharma: Focused ambitions, emerging opportunities

While some small biopharma companies, particularly "techbios", are built around AI-driven strategies, the majority are taking a measured approach to adopting enabling technologies. Retooling for AI often comes with significant costs and risks diverting attention from core scientific goals, leading many small companies to limit AI usage to pilots and proof-of-concept projects. Structural hurdles compound this measured approach, with 53% citing limited ability to hire skilled talent and 42% pointing to challenges with access to high-quality, well-structured data and metadata.

Small biopharma still recognise the value and important role of technology in improving R&D outcomes. Nearly 70% of respondents expect enabling technologies like R&D data platforms, scientific software, and connected lab instruments to significantly enhance quality and reduce human errors if fully adopted in the next 12–24 months. However, the cost of implementing solutions often limits broader adoption for smaller organisations.

Looking ahead to 2025, small biopharma will continue its deliberate and ROI-driven approach to technology adoption. At the same time, the rise of open-source tools and accessible AI frameworks promises to level the playing field, offering smaller companies new opportunities to compete and innovate.

Bridging the AI readiness gap

Readiness for AI — spanning talent, data infrastructure, and unified workflows — remains a significant hurdle for the industry. Only 14% of large biopharma company respondents report an advanced level of AI readiness — that their organisation is prepared for AI across all of the critical dimensions: talent, data (i.e., capture, processing, and generation) and, finally, unified and iterative workflows and the necessary compute that allows it all to happen. Even fewer, just 3%, of small company respondents reach this threshold. In 2025, companies will likely address these gaps head-on:

• Talent acquisition: Large biopharma will continue recruiting AI expertise from external industries like tech, with hiring trends showing top recruits from Nvidia, Nike, and Google to name a few. Smaller companies will emphasise their missions to attract skilled professionals drawn to the fast-paced, high-impact environment of biotech start-ups.
• Wet and dry lab integration: Large biopharma respondents identify the biggest gap in AI readiness as uniting wet and dry lab workflows (41% preparedness). In 2025, expect more companies to adopt integrated structures, using shared systems of record and scaling wet lab operations to match dry lab outputs. Advances in these areas can unlock a more iterative and hybrid/computational approach to R&D.

The future of R&D: AI at scale

2025 will be a heads-down year for scaling AI across biopharma. For organisations at the forefront, readiness will mean transforming R&D processes, leveraging connected systems, and ensuring that wet and dry labs operate in unison. Companies prioritising foundational investments in R&D data platforms, structured and centralised data and metadata capture, and cloud-connected tools will lead the charge in AI readiness, and therefore AI deployment.

However, AI’s impact extends beyond individual companies. Achieving ubiquitous adoption of AI technologies could revolutionise the industry, driving faster and more successful drug development. For this promise to become a reality, the biopharma community must collaborate to address structural challenges, democratise access to advanced tools, and build a workforce capable of supporting these advancements.

The AI rally in biopharma isn’t about racing toward fleeting trends — it’s about setting the foundation for lasting transformation. By the end of 2025, we expect to see tangible progress in AI readiness, with leading companies demonstrating how strategic investment and organisational change can unlock AI’s full potential. For biopharma, this isn’t just about technological advancement, it’s about delivering better medicines to patients, faster and more affordably, and reshaping the future of healthcare.