Sapio Sciences’ study finds ELN limitations leave only 5% of scientists able to analyze data independently, 60% repeating experiments and shadow AI use increasing

Sapio Sciences, the science-aware™ AI lab informatics platform, today announced the results of new research examining scientists’ sentiment around electronic lab notebooks (ELNs) and AI tools in modern laboratory environments. The study reveals widespread frustration with existing lab software, leading to repeated experiments, inefficient data use, and a growing reliance on unauthorized shadow AI. 150 scientists were surveyed across U.S. and European labs in biopharma R&D, contract research organizations, clinical diagnostics, and pharmaceutical manufacturing.

Despite the significant investments made in digital lab technology, ELNs often fail to support effective scientific work. Only 62% of scientists say their ELN allows them to work efficiently, and just 5% report being able to analyze experimental results without specialist support.

Additionally, duplication is a persistent issue. Nearly two-thirds of scientists, 65%, say they have had to repeat experiments because prior results were difficult to find or reuse, driving avoidable costs and delays across lab teams.

Science has outgrown second-generation ELNs

The survey highlights several ways today’s ELNs are falling short:

• Workflow rigidity: Only 7% of scientists say their ELN can be adapted to new assays or experimental workflows without specialist support, limiting scientists’ ability to respond quickly as research evolves. Separately, just 5% of scientists say they can analyze experimental data without additional support.
• Usability issues: 56% of scientists say their ELN is too complex and slows them down.
• Manual data movement: 51% spend too much time importing and exporting data, rising to 81% among U.S.-based scientists and 72% in pharmaceutical manufacturing.
• Configuration difficulties: 71% of scientists say ELNs are hard to configure or adapt, with above-average frustration in pharmaceutical manufacturing at 84%.

Mike Hampton, chief commercial officer at Sapio Sciences, said:

“The survey clearly shows a growing mismatch between modern scientific practice and the capabilities of traditional ELNs. Most ELNs were designed as tools that focused on documenting experiments, not actively supporting scientists or guiding next steps. Today, scientists are working with increasingly complex data and are expected to move from results to decisions faster than ever, yet many ELNs still function like glorified filing cabinets.”

“When scientists can’t analyze data or easily build on previous experiments without additional support, frustration turns into real cost. Unnecessary experiment duplication wastes reagents, instrument time, and specialist labor. At the same time, it limits curiosity and slows the pace of discovery across biopharma R&D.”

ELN limitations are fueling shadow AI use

The research also shows how these frustrations are reshaping behavior in the lab. Almost half of scientists surveyed, 45%, say they use public generative AI tools through personal accounts to support their work, despite the security, IP, and compliance risks associated with shadow AI.

Sean Blake, chief information officer at Sapio Sciences, said:

“Scientists aren’t turning to public AI because they want to bypass governance. They’re doing it because existing lab tools can’t help them analyze results or determine next steps efficiently. When AI capability isn’t available in governed environments, people will find it elsewhere, even when they do understand the risks.”

Scientists want AI that accelerates science, not just documents it

When asked what they want from the next generation of ELNs, scientists consistently emphasized interaction, guidance, and interpretation rather than documenting experiments alone. Ninety-five percent want conversational, text-based interfaces, while 78% want voice interaction. Almost all respondents, 96%, say future ELNs must help interpret data, not simply capture it.

Scientists also want built-in, field-specific AI capabilities, with demand varying by discipline:

• Retrosynthesis, toxicity, and solubility prediction: 83% of diagnostics labs and 74% of biopharma R&D
• Molecular binding simulations: 71% of biopharma R&D
• Genetic sequence optimization: 65% of CROs and 63% of diagnostics labs

Rob Brown, head of the scientific office at Sapio Sciences, said:

“Our research clearly shows that second-generation ELNs have reached the limits of what scientists expect from them. As we shape the next generation of lab software at Sapio, the focus is on AI-enabled scientific analysis and design methods that keep scientists in control while actively supporting workflows, analysis and next-step decisions.”

The findings suggest scientists are not looking to relinquish control but to work with AI tools that actively support reasoning and interpretation within governed lab environments.

Download the full report here: https://www.sapiosciences.com/resource/rise-of-ai-lab-notebook/

About the research

The findings are based on a survey of 150 scientists working in laboratory environments across the United States and Europe. Respondents represented a range of sectors, including biopharma R&D, contract research organizations, clinical diagnostics, and pharmaceutical manufacturing. The research explored how scientists use electronic lab notebooks and AI tools in their day-to-day work, focusing on usability, data analysis capability, experiment reuse, and emerging behaviors such as the use of public generative AI. The survey was conducted in November 2025.

About Sapio Sciences

Sapio Sciences delivers the Sapio Platform, an agentic AI lab informatics platform for biopharma R&D, clinical diagnostics and manufacturing. Built on a shared native AI foundation, the Sapio Platform unifies Sapio LIMS, Sapio ELaiN (AI lab notebook) and Sapio Scientific Data Cloud in one configurable environment so labs can automate complex workflows and keep samples, experiments and data connected.

Learn more at www.sapiosciences.com and follow Sapio Sciences on LinkedIn.

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“The survey clearly shows a growing mismatch between modern scientific practice and the capabilities of traditional ELNs. Most ELNs were designed as tools that focused on documenting experiments, not actively supporting scientists or guiding next steps."