LONDON, UK. June 22, 2026 – A new survey commissioned by Sapio Sciences has uncovered extensive use of public AI tools across scientific laboratories. The findings show that 77 percent of scientists are using AI applications outside approved workplace systems, while almost 45 percent are doing so through personal accounts. This trend raises concerns about data security, compliance obligations, and the reliability of scientific outputs.
Just 5 percent of scientists surveyed reported being able to carry out experimental analysis independently within approved software environments.
Shadow AI refers to artificial intelligence tools used without formal approval from IT and security departments. Such usage can expose organisations to risks involving confidential information, intellectual property, and regulatory requirements.
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.”
According to Sapio Sciences, the growing use of shadow AI reflects broader challenges within biopharmaceutical R&D. Researchers often turn to public AI platforms to help interpret data, refine methods, and organise experimental planning. Despite widespread adoption of ELNs and laboratory information management systems, many scientists still encounter obstacles when analysing results.
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.”
Survey results also showed that more than half of respondents feel their ELN hinders productivity. In addition, 65 percent said they have repeated experiments because previous findings were difficult to locate, interpret, or reuse.
Generative AI tools have gained popularity because they offer immediate assistance, helping researchers summarise data, organise ideas, and simplify complex information.
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.”
Experts argue that the challenge is not AI adoption itself but ensuring AI operates within approved and governed environments.
Sean Blake believes that integrating AI directly into laboratory workflows is the next step. Technologies such as the AI Lab Notebook are designed to support scientific interpretation and reasoning within secure systems rather than relying on external tools.
Scientists are seeking support that enables faster progress while maintaining confidence in their work.
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/.
