{"id":15482,"date":"2026-09-28T09:29:03","date_gmt":"2026-09-28T03:59:03","guid":{"rendered":"https:\/\/threatcop.com\/blog\/?p=15482"},"modified":"2026-09-29T10:05:55","modified_gmt":"2026-09-29T04:35:55","slug":"ai-enabled-social-engineering","status":"publish","type":"post","link":"https:\/\/threatcop.com\/blog\/ai-enabled-social-engineering\/","title":{"rendered":"AI-Enabled Social Engineering: What the Loss Data Shows"},"content":{"rendered":"\n

AI has not created a new category of cyber loss yet. It has made the oldest one, social engineering, dramatically more effective, and insurance claims data shows the shift precisely: losses tied to phishing, social engineering, and transfer fraud climbed from 17.7% of incurred losses in H1 2024 to 85.3% in H1 2026, while zero incurred losses in the same period trace to an actual AI-specific attack vector like prompt injection or agentic misuse. The technology changed. The point of failure did not.<\/p>

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