Across the life sciences industry, lab operations are quietly undergoing a seismic shift. The growing pressure to do more with less - accelerate discovery, ensure data integrity, improve throughput - is forcing labs to rethink how they work. What was once a largely manual environment, heavily reliant on spreadsheets, emails, and human oversight, is now being reshaped by automation, Artificial Intelligence (AI) and digital transformation.
But while the technology exists, adoption remains mixed. Some labs are pushing ahead, exploring AI to manage the complexity of data or rolling out automation to streamline lab capabilities. While others are still using disconnected workflows with legacy systems, unsure of how to build a robust lab for the future.
How Labs Are Navigating Digital Transformation
Our new white paper ‘The Future of Digital Lab Operations’, captures a snapshot of where the industry stands and where it is going next. It explores how labs are responding to shifting demands, what technologies they are prioritizing and the barriers that are still slowing up progress.
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One of the most striking insights from the white paper is the sense of urgency. 45% of respondents plan to implement advanced technologies within the next two years, despite ongoing funding pressures and capacity constraints. However, many labs are not ready yet. Digital maturity levels vary widely, only 15% of participants said that their labs are fully digitized, and a significant proportion are still relying on manual workflows for routine tasks. This disconnect between ambition and reality is a central theme of the white paper.
While many we surveyed see a future where AI helps scientists analyse complex results in real time, or where automation frees up time for more strategic research, most are still facing fundamental operational challenges. Managing large volumes of data, integrating systems across teams, and simply keeping track of inventory, reagents and supplies continue to cause friction.
The results from our survey highlight that while next-generation tools like robotics and AI dominate headlines, many labs are most eager to address the everyday bottlenecks that slow them down. Basic lab functions like inventory control top of the list. Without those foundations in place, more advanced innovations struggle to deliver value. This serves as a reminder that digital transformation is not about chasing trends. It is about solving real problems in ways that are scalable, sustainable and aligned with how science is done, by scientists.
Another insight that stands out is the perception of AI and its role within the lab. There is clearly excitement about what it can unlock - faster analysis, smarter automation and deeper insights, but also uncertainty about where to apply it first. Nearly a quarter of respondents (24%) identified managing the growing volume of data from lab experiments as the most significant role AI will play in laboratory operations over the next five years, highlighting its necessity in keeping pace with increasingly data-rich lab environments.
Despite this momentum, not every lab is ready to embrace these tools immediately. The white paper reveals a wide range of adoption timelines, from labs already piloting AI, machine learning and robotics to those still years away from making any major investment.
Building Toward Lab Efficiency
For many this white paper offers a valuable benchmark. It captures not only what peers across the industry are planning, but also what they are struggling with and how they are overcoming those obstacles. As well as painting a picture of a high-tech future,. it lays out the steps that are being taken today to get there.
Whether your lab is already experimenting with digital tools or still trying to eliminate paper-based processes, ‘The Future of Digital Lab Operations’ provides insight into the broader movement shaping the next generation of lab work.
Ready to see where your lab stands and what comes next? Download the full white paper today and discover how forward-thinking labs are preparing for the future.
