Image Credentials: Image Title: Artificial Intelligence and the Future of Biological Weapons Verification: Promise and Limitations Source: (sora.openai) Date: October 2025. Attribution: This image was created using AI-generated imagery (sora.openai) and does not depict a real-world scene.
Elliot Hayes | Senior Editor with Agencies
When U.S. President Donald Trump addressed the United Nations General Assembly and announced plans to “lead an international effort to enforce the Biological Weapons Convention (BWC) by pioneering an AI verification system that everyone can trust,” it marked a pivotal moment in global security policy. The Biological Weapons Convention, which entered into force in 1975, bans the development, production, and stockpiling of biological and toxin weapons. However, unlike nuclear or chemical treaties, the BWC lacks a robust verification mechanism to ensure compliance. Could artificial intelligence change that?
The Promise of AI in Treaty Verification
Artificial intelligence could revolutionize how the world monitors compliance with biological weapons bans. One of the most immediate applications involves AI-driven text-mining tools, which can analyze the “confidence-building measures” submitted annually by signatory states. These submissions contain details about national laboratories, biodefense programs, and related research, but they often go unread due to the sheer volume of data. AI could quickly identify anomalies, inconsistencies, or emerging risks.
Beyond official reports, AI can aggregate and analyze vast open-source data, ranging from academic research papers and patents to financial transactions and trade records involving biological materials. This approach mirrors how the International Atomic Energy Agency (IAEA) is exploring AI to improve nuclear safeguards, helping analysts detect irregularities in complex datasets. In the BWC context, AI could provide a clearer picture of what activities are occurring in national facilities and whether they align with peaceful purposes.
Natural language processing (NLP) tools could make this data analysis even more effective. NLP can understand, summarize, and translate large volumes of technical information, enabling real-time monitoring of facilities and research publications. Furthermore, AI anomaly detection algorithms, already used by the IAEA, could help spot suspicious patterns, such as unexplained equipment purchases or unusual biological sample transfers, that may merit further scrutiny.
In the event of a biological outbreak, AI systems could rapidly analyze data from social media, news reports, and public health databases to determine whether the event is natural or potentially linked to a weapons program. Additionally, if the BWC were to establish a formal inspection regime, AI could be used to train inspectors through virtual simulations, improving readiness for on-site verification missions.
The Technical and Political Challenges
Despite its promise, integrating AI into bioweapons verification faces significant hurdles. Data inequality is one of the biggest. Many countries do not have comprehensive or transparent data on their biological research infrastructure. AI systems trained on incomplete datasets could misidentify innocent research as suspicious or fail to detect genuine violations.
Another challenge lies in data reliability. With the growing prevalence of misinformation and deliberate deception, distinguishing factual information from fabricated reports is increasingly difficult. Verification systems that rely on AI will need rigorous data vetting and cross-checking mechanisms to prevent false positives or politically motivated accusations.
The most profound challenge, however, is defining what AI should look for. Historical data on biological weapons programs, such as those from the Soviet Union or Iraq are incomplete and often unreliable. Modern synthetic biology, gene editing, and dual-use research blur the lines between peaceful and offensive capabilities. Training an AI system to detect 21st-century bioweapons activity requires not only technical precision but also a deep understanding of emerging life science trends.
Even if AI could successfully flag suspicious activities, the political challenge of trust remains. Nations are unlikely to accept an algorithm’s judgment as definitive in matters as sensitive as weapons of mass destruction. To be credible, any AI-generated leads would require follow-up through challenge inspections, an issue that has long divided BWC member states.
A Long Road Toward Consensus
Efforts to create a BWC verification protocol have failed before—most notably in 2001, when the U.S. rejected a draft protocol it viewed as insufficient to detect covert programs. Renewed efforts to integrate AI must navigate similar geopolitical tensions. Achieving global consensus on data sharing, verification standards, and oversight mechanisms will be an immense diplomatic undertaking.
Moreover, the BWC’s Implementation Support Unit, which currently consists of only four staff members, is vastly underfunded for such an ambitious project. Any meaningful AI initiative would require major investment, sustained political will, and collaboration among states, private tech firms, and international organizations.
AI: A Tool, Not a Solution
Artificial intelligence will not solve the BWC’s verification gap overnight. It is not a “silver bullet,” but rather a supporting tool, one that can improve transparency, data analysis, and early warning without replacing human judgment or diplomacy.
Still, after half a century of debate about how to verify one of the world’s most critical arms control treaties, AI offers something new: a spark of innovation in a field long constrained by political gridlock. By combining technological progress with renewed international engagement, the world could take a significant step toward preventing the weaponization of biology in the 21st century.