University of Queensland and MIT 2026: which sectors are most exposed to AI risk.
The authors write that the standards, enforcement and liability other safety-critical industries rely on are still forming or missing for AI.
8 June 2026
AI-risk experts on the panel
countries represented across academia, industry and government
AI risk subdomains rated for severity and exposure
University of Queensland and MIT, 2026
In 2026 a team led by researchers at the University of Queensland and MIT FutureTech published a three-round expert study on which risks from AI matter most. The method is a Delphi study: a panel rates each risk, sees how peers rated it and revises over rounds.
An international panel of 272 AI-risk experts judged information, finance and national security the sectors most exposed to AI risk.
The panel’s ratings spread vulnerability to AI risk across users, affected people and nearly every sector, and placed responsibility for addressing it mainly on general-purpose AI developers and on governments, regulators and standards bodies. The authors write:
“Comparable mechanisms for AI are nascent or absent. Without them, vulnerable parties have little recourse and responsible parties face little pressure to act.”
The authors write that other safety-critical industries rely on mandatory standards, enforcement, liability and a public expectation of low risk, and that for AI these are still forming or missing. They note that AI risk management inside organizations has been described as layered defenses combining operational, monitoring and audit functions, and say the same logic can extend to the whole AI ecosystem, since societal resilience requires coordinated action from many actors.
The authors warn that responsibility shared across many actors can become “responsibility held by none.”
What Mandate does
Mandate checks messages to AI against your rules before they leave, and every decision goes on a signed record you can export for any period.
Sources
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Saeri et al. (2026): data and materials on the Open Science Framework
Data and materials for the study, posted on the Open Science Framework.
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Saeri et al. (2026): Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts
The paper itself, submitted 3 June 2026: the source for every finding and quote above.
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MIT AI Risk Repository (Slattery et al.)
The risk taxonomy the study rated: seven domains and 24 subdomains.
More reading notes
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CB Financial Services 2026: an SEC filing over customer data put into an AI app the bank had not approved
19 October 2026CB Financial Services told the SEC that customer names, Social Security numbers and dates of birth were handled with an AI application the bank had not authorized.
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EY 2026: 47% say their AI governance process was skipped for urgent deployments
18 October 202698% of the 202 US senior AI executives EY surveyed say their company has formal AI governance policies in place, and 47% say the process was skipped for urgent deployments.
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OWASP 2026: misuse of an AI agent’s identity and access is a top threat
9 June 2026The OWASP security project lists misuse of an agent’s identity and access among the ten highest-impact threats to AI agents, and recommends each agent get its own identity.
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NTT DATA 2026: what the companies furthest ahead with AI prioritize in governance
9 June 2026Of the companies furthest ahead with AI in NTT DATA’s survey of 2,567 executives, 59.4% named data privacy or sovereignty across countries a top governance concern, against 49.6% of those furthest behind.
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Schrems II and the CLOUD Act: which law reaches your data
18 May 2026Under the US CLOUD Act, a US court can order a provider under US law to hand over data it controls, wherever that data is stored.
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IBM 2026: 18% of Canadian organizations say they have systems to govern AI across everyday operations
8 May 2026In an IBM Institute for Business Value study, 18% of Canadian organizations said they have systems to coordinate and govern AI across everyday operations.
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United States v. Heppner: documents a defendant made with an AI tool, not at a lawyer’s direction, were not privileged
30 April 2026A US federal court found that documents a defendant made with an AI tool, not at a lawyer’s direction, were not privileged.
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