
Could AI âÂÂchange the stakesâ in the development of bioweapons?
Experts say the technology could help terrorists and nation states with production but that significant hurdles remain
In his annual speech on threats to the nation, Sir Ken McCallum, the head of the UKâÂÂs intelligence service, MI5, warned that AI has the potential to âÂÂchange the stakesâ on existing and even new bioweapons. Here we look at how AI might help in the development of bioweapons and the hurdles that remain.
How could AI help people make bioweapons?
It depends on who wants to make them. One risk is the rogue, unskilled bad actor or terrorist group that works from a garage laboratory. AI chatbots could help them skill up, by compiling relevant information, planning experiments and troubleshooting problems. ItâÂÂs likely the work would focus on using existing pathogens and toxins.
The other risk comes from well-resourced organisations and nation states that have plenty of skilled scientists, high containment laboratories and all of the equipment and reagents needed to work on bioweapons safely. AI tools could help researchers identify genetic tweaks to make existing pathogens more lethal, for example. This is the more immediate concern, according to Dr Filippa Lentzos, a reader in science and international security at KingâÂÂs College London. âÂÂHere, AI does not remove the need for expertise, it amplifies expertise that is already there,â she says.
A more distant risk comes from highly skilled groups using AI to design completely new pathogens and toxins that are resistant to drugs or have no antidotes.
Have people tried using AI to make bioweapons?
Last year, police in India uncovered a suspected bioterrorism plot in which a doctor and several others drew on AI chatbot queries and AI-driven search, allegedly to help them make ricin, a deadly toxin, using kitchen tools. It is unclear whether the AIâÂÂs responses helped, but other accounts suggest the tools can provide relevant and dangerous information.
The AI company Anthropic raised further concerns in September when it reported five cases of scientists in unnamed countries trying to use its Claude chatbot for what may have been dangerous work on viruses or toxins. One red flag, the company said, was that after being blocked, the scientists found workarounds.
In one case, Anthropic said researchers used the chatbot to plan experiments that would introduce mutations in a highly pathogenic bird flu virus to make it adapt and spread more easily in mammals. The work, and the other cases, could signify attempts to make pathogens more dangerous, but such studies are also done in legitimate labs to help researchers spot future pandemics and develop vaccines and drugs to treat disease.
What else has raised concerns?
A flurry of studies has shown how AI tools can provide potentially dangerous information on bioweapons. In a recent exercise at MIT, non-science students were tasked to see if they could get an AI chatbot to help them unleash a pandemic. Within an hour, the chatbots listed four potential pandemic pathogens, explained how to make them from synthetic DNA, and supplied names of DNA synthesis companies that were unlikely to screen their orders. It is easier said than done, however.
In another case, the Stanford University researcher Dr David Relman described how an AI explained how to modify a pathogen to make it resistant to treatment. Another scientist revealed that an AI chatbot had explained how to use a weather balloon to release biological weapons from the sky.
The dual-use nature of biological research can make it hard to distinguish valuable work that could protect health from attempts to develop bioweapons. In 2025, scientists at Los Alamos National Laboratory trained an AI to predict how exceptionally potent neurotoxins from marine snails latch on to human cells, work that could help in the development of antidotes. But the US government became concerned when Chinese researchers drew on the work to develop their own tool to design new toxins. The Chinese researchers said the work was aimed solely at developing drugs.
In April, scientists raised further concerns when they made the first viruses designed by AI. The viruses are a particular type that only invade bacteria, and the work could lead to new medicines, but experts warned that it raised âÂÂurgent biosafety and biosecurity questionsâÂÂ.
What hurdles make it difficult?
Most work on bioweapons is beyond the reach of unskilled groups: as well as being highly technical, it is extremely dangerous. While AI chatbots might be prompted to give information on bioweapons, a list of instructions is not enough. âÂÂInformation is only one part of the problem,â says Lentzos. âÂÂTacit expertise, access to biological materials and equipment, experimental validation, scale-up and delivery all remain substantial barriers.âÂÂ
Sonia Ben Ouagrham-Gormley, deputy director of the biodefense programme at George Mason University in Virginia says tacit knowledge â the unwritten knowhow that an AI is unlikely to help with â has been key in the success of historical state-run bioweapons programmes.
Prof Martin PaÃÂesa at the University of Zurich said access to material was critical. âÂÂAny graduate physicist could sketch up plans for a potentially more effective nuclear bomb, but where is he going to get a lump of uranium from? Same for bioweapons. If you have access to material and facilities capable of producing them, then AI is not going to make too much difference if you want to do harm.âÂÂ
What extra measures are needed?
Some AI companies are taking steps to prevent people from using their tools to develop bioweapons, but the majority are not announcing what, if anything, they are doing, says Prof Tom Inglesby, director of the Johns Hopkins Center for Health Security. âÂÂWe have no formal government policies in place in any country yet to protect against this kind of misuse,â he says.
He wants formal independent evaluations of new AI models before they are released, with any dangers eliminated before the models are made public. And high-risk biological data, such as information on how pathogens might spread more easily, should be restricted. Meanwhile, companies that make genetic material for researchers must screen orders to ensure they are not for the creation of novel, highly dangerous viruses. Some screening already happens, but it is largely voluntary, and can be sidestepped if researchers use AI to design new, harmful genetic sequences that companies are not checking for.
