LONDON, UK. June 22, 2026 – New research commissioned by Sapio Sciences indicates that unofficial AI use has become commonplace in laboratories. The study found that more than three-quarters of scientists are using public AI platforms that have not been authorised by their organisations. Nearly half access these tools through personal accounts, creating potential risks around data exposure, research integrity, and compliance.
Only 5 percent of respondents said they are able to analyse experimental findings independently using approved laboratory systems.
Shadow AI describes the use of artificial intelligence tools without oversight or approval from internal IT and security teams. This practice can create concerns around intellectual property protection, regulatory compliance, and sensitive data management.
Sean Blake, Chief Information Officer at Sapio Sciences, said: “Shadow AI tends to emerge where official digital tools fail to support how modern science is practised.
“When platforms cannot support interpretation, comparison, or decision-making at the required pace, scientists work around them.”
Sapio experts believe shadow AI is now deeply embedded in biopharma research and development environments. Scientists increasingly rely on public AI applications to interpret findings, improve protocols, and organise scientific thinking. While electronic lab notebooks (ELNs) and laboratory information management systems remain widely used, gaps in functionality continue to drive alternative behaviours.
Sean Blake added: “Many ELNs are optimised for documentation and retention rather than scientific reasoning. Interpretation and comparison frequently require informatics queues, manual exports, or external analysis.
“Scientific progress rarely stalls at data capture. It more often stalls during interpretation, when results must be translated into decisions. When official tools cannot support that transition efficiently, scientists adapt.”
The survey found that 56 percent of scientists believe their ELN slows productivity, while 65 percent have repeated experiments because previous results were difficult to locate, understand, or apply.
Public generative AI tools provide rapid and intuitive support. They can summarise findings, help structure ideas, and reduce the effort required to process information. In settings where official workflows rely heavily on manual processes, these tools present an attractive alternative.
Sean Blake noted: “This usage reflects rational tradeoffs rather than defiance. From an infrastructure perspective, shadow AI reflects unmet demand within official systems.
“Typically, companies tend to respond by restricting the use of shadow AI. Blanket policies reduce exposure, but they rarely change behaviour.”
Industry observers stress that AI itself is not the core problem. Risks increase when AI operates outside systems designed to govern scientific data and decision-making.
According to Sean Blake, organisations should integrate governed, role-specific AI capabilities directly into scientific workflows. Solutions such as the AI Lab Notebook, often described as an AI-enabled ELN, are emerging to address this need. These systems are designed to support scientific reasoning rather than simply adding chatbot functionality.
Scientists are not looking to replace their expertise. Instead, they want tools that help accelerate research while maintaining quality and control.
Sean Blake concluded: “The challenge is designing infrastructure that supports both control and innovation. Focusing solely on restriction reduces confidence. Embedding intelligence within approved systems regains visibility.
“The choice is no longer whether AI belongs in the lab. It is whether intelligence remains outside official systems or is embedded where scientific decisions are actually made.”
For more information about Sapio Sciences, please visit https://www.sapiosciences.com/.
