The short answer? No.

AI can analyse data and speed up lab work, but it can’t ask bold questions or think creatively. True discovery still relies on human curiosity, intuition, and judgement. Far from replacing scientists, AI makes them more vital – as critical thinkers and problem-solvers in an increasingly automated lab.

Labs are smarter, but at what cost?

Laboratories worldwide are undergoing a tech revolution – automated sample handlers, machine learning models that digest terabytes of data in seconds, and AI systems that draft experiment plans. These tools are powerful and efficient, but their rise raises a compelling question: how much is too much? At what point does AI stop being a helpful assistant and start making scientists obsolete?

AI is already doing the “science”

This isn’t science fiction. AI tools now predict chemical reactions, screen potential drugs in silico, optimise lab processes, and even write sections of research papers. Technology firms like DeepMind and Insilico Medicine demonstrate that machines are already performing traditionally human-driven tasks – often faster and at greater scale.

Scientific creativity still belongs to humans

Yet science isn’t just number-crunching or protocol ticking. Real breakthroughs often come from curiosity, intuition, and the willingness to question anomalies. AI may spot patterns, but it can’t ask “what if?” or “why does this matter?” Those questions still require a scientist’s spark, not a machine’s algorithm.

Are we training scientists or operators?

If AI is doing most of the heavy lifting, how should we be educating the next generation of scientists? Should pipetting skills give way to coding proficiency? As AI handles complex analysis, human scientists must become skilled interpreters. Without retraining, we risk producing scientists who follow AI outputs without understanding their basis.

The danger: outsourcing critical thinking

Blind trust in AI is risky. If results are accepted without scrutiny, we will lose scientific judgement. AI can suggest a statistically significant correlation – but does it understand the context or the broader implications? Without human oversight, we might lose not just jobs, but the very principles that ensure robust science.

The future: collaboration, not replacement

AI shouldn’t be seen as a replacement for scientists, but rather a partner that can free them from repetitive tasks. That liberation could let scientists focus on designing experiments, interpreting results thoughtfully, and tackling big-picture problems. But to keep humans in the driver’s seat, labs, institutions, and universities must adapt fast.

So, what we you think?

Should we fear that AI will take over our labs? Or worry more that we’re not harnessing its potential – or preparing people for the new reality? AI isn’t going away. The real question is: in the lab of tomorrow, will human scientists still be leading the charge?