Data stands at the center of transformation in today’s digital labs—both as a major obstacle and a driving force for innovation, according to a survey of more than 150 scientists from Titian Software and Labguru.
Data overload and management were identified as the most significant challenges impacting lab operations. This same data deluge offers a powerful opportunity: respondents cited AI’s potential to manage and extract insights from the vast volumes of data generated by experiments, instruments, and other sources as its most valuable future role. This duality highlights data as not just a pain point, but the foundation for unlocking the next wave of AI-driven advances in the lab.
Titian Software, which delivers the Mosaic sample management solution, and Labguru a leading laboratory information management system (LIMS), electronic lab notebook (ELN), inventory, and data management platform, have released the results of their latest survey looking to the future of digital lab operations in the life sciences industry.
While machine learning and AI are expected to be major drivers of transformation in lab operations, the reality is that many labs aren’t quite ready to fully harness its potential. Foundational issues remain, with inventory management and the automation of manual processes taking precedence. In fact, 65 percent of survey respondents identified inventory management—specifically of reagents and supplies—as the top technology they’re interested in adopting. A strong majority—77 percent of respondents—believe automation will be the primary driver of change by 2026, underscoring the urgent need to address manual processes before the broader adoption of AI and machine learning.
The results signal the pressing need to address operational inefficiencies before labs can scale into more advanced technologies. The results were consistent across every type of lab, from big pharma to start-up. Despite growing interest in next-generation tools like AI and robotics, only 15 percent of labs claim to be fully digitized, and half still rely heavily on manual processes.
While 45 percent of respondents plan to implement next-generation lab technologies like AI within the next two years, a significant portion—25 percent—have no near-term plans or anticipate needing more than five years. This gap highlights a critical period of transition, where foundational improvements must be prioritized before the full promise of AI can be realized.
AI’s greatest promise lies in making sense of the overwhelming volume and complexity of lab data. Nearly a quarter of respondents (24 percent) identified managing data from lab experiments and instruments as the most significant role AI will play in lab operations over the next five years. With 54 percent citing data overload and management as a key challenge driving change, the need is clear. It’s not just the quantity of data that’s straining labs—it’s the complexity across diverse modalities, creating added pressure around storage, automation, acquisition, compliance, and regulatory requirements.
The life sciences industry is poised for a major evolution, as AI moves from a promising concept to a practical necessity in digital lab operations.
While organizations widely recognize AI’s potential to improve efficiency, accelerate discovery, and make sense of complex data, digital maturity remains uneven—and barriers like data silos and skepticism around AI outputs persist.
“Labs today are generating more data than ever before, but without the right systems in place, that data becomes a burden instead of a benefit,” said Keith Hale, Group Chief Executive Officer at Titian Software and Labguru. “Better data practices and smarter sample and inventory management are essential not only for improving day-to-day operations but also for setting the stage for more advanced capabilities. AI cannot deliver real, meaningful benefit without connected and well-managed data. That is where we come in. By helping labs streamline and structure their operations and data management today, we can enable the power of AI to transform the labs of tomorrow.”
About the survey
In January 2025, Titian Software and Labguru surveyed the life sciences industry to understand the trends and innovations that matter most in digital lab operations. 155 people completed the survey. These findings represent the current state of automation and data management and the evolution of AI in life science and its potential impact in lab operations. Survey respondent breakdown by organization type:
· Twenty six percent from large pharma/biotech (>5,000 employees)
· Twelve percent from mid-size pharma/biotech (500-5,00 employees)
· Twenty nine percent from small (start-up) pharma/biotech (<500 employees)
· Four percent from CRO (Contract Research Organization)
· Twenty one percent from academic institution
· Eight percent from other organizations
Other organization types specified included: Research Lab for Manufacturing, Research and Consulting Lab, Chemical Company, small startup, carbon capture tech development and government.
-Note: This news release was originally published on the Titian Software website. As it has been republished, it may deviate from our style guide.
