These are the most urgent AI risks, according to 272 experts
13:50 · July 20, 2026 · RSS APP - AI Primary Research

Which AI risks could cause the most harm in the next five years? New MIT research shows that businesses should be aware of threats like competitive pressure and dangerous AI capabilities.
Summary
MIT FutureTech and the University of Queensland used a Delphi process to gather structured judgments from 272 AI experts on 24 risk domains over a five-year horizon. The experts assessed both the likelihood and potential severity of harm under a business-as-usual scenario and under a pragmatic-mitigation scenario in which cost-effective safeguards are applied. Catastrophic outcomes were defined as events producing more than one million deaths, more than $100 billion in losses, or comparable civilizational damage.
Five domains stood out as carrying the highest combined likelihood and severity: dangerous capabilities that could enable persuasion, surveillance, or biological-weapon assistance; competitive pressures that encourage rapid deployment at the expense of safety; AI-enabled weapons and cyberattacks that exploit software vulnerabilities at scale; concentrated power arising from unequal access to advanced systems; and the generation and spread of false information. Even when experts assumed pragmatic mitigation measures, these five risks retained at least a 10 percent probability of catastrophic impact.
The information, national security, and finance sectors were judged most exposed. In information environments the primary concerns involve manipulation of content and erosion of trust; in national security the focus lies on offensive cyber operations and surveillance; in finance the risks center on fraud, market manipulation, and systemic instability. Across all three sectors, AI lowers the barrier for less-skilled actors while amplifying the speed and reach of already capable ones.
The study notes a persistent misalignment: AI developers and regulators are seen as bearing primary responsibility for risk reduction, yet the organizations and individuals most vulnerable to harm are often not positioned to influence those decisions. The authors therefore recommend that leaders embed AI-risk assessment into existing governance processes for cybersecurity, privacy, and business continuity rather than treating it as a separate compliance exercise.
Why it matters
This article provides empirical primary research on AI risk prioritization, which is highly actionable for Dutch researchers and enterprises aligning with the EU AI Act's risk-based approach. The focus on finance and information sectors directly applies to major Dutch industries seeking robust AI governance.







