The second annual Cenevo survey highlights the current state of AI adoption in life sciences laboratories, revealing that while AI is gaining traction, its application remains largely experimental.
According to the survey, only 5% of life sciences labs are utilizing AI agents in production, despite over 60% exploring or piloting AI technologies. The primary focus for researchers is on data analysis, workflow automation, and inventory management, rather than fully agentic-driven scientific decision-making. Notably, 57% of respondents are using AI for data analysis, and 25% have implemented generative AI in their operations.
Challenges persist, particularly in data management and integration. Although the number of labs reporting issues with data quality has decreased, 55% still struggle with system integration and managing unstructured data. Concerns regarding privacy and security are prevalent, with 58% of respondents expressing apprehension about current AI capabilities.
As labs prioritize investments in automation and AI-enabled software, connectivity among systems has become crucial. The survey indicates that addressing these integration challenges is essential for maximizing AI's potential benefits in laboratory settings. Cenevo CEO Keith Hale summarized the situation, noting that while AI exploration is a priority, the actual deployment of agentic workflows is still limited due to ongoing concerns about data fragmentation and compliance.