Generative AI has changed what a malicious email looks like. Messages that once gave themselves away through clumsy wording, generic pretexts, and reused templates now arrive fluent, personalized, and unique to each recipient, and the behavioral signals email filters have relied on for years are fading as a result.

Proofpoint shared several examples of the shift at its Protect 2026 conference. In one, a single threat actor contacted more than 30 real estate agents at the same company, each from a different account, about a different property, and in different words, before closing every thread with the same request: join a video meeting.

Federal data points the same way. The FBI's Internet Crime Complaint Center counted more than 22,000 complaints involving AI in 2025, with nearly $900 million in associated losses, and logged 24,768 business email compromise (BEC) complaints with about $3.05 billion in reported losses, according to its 2025 Internet Crime Report.

Email filters were built for attackers who had to cut corners. Researching a target, writing convincingly in a second language, impersonating a supplier, and producing enough variants to defeat signatures all took time, so attackers reused templates and infrastructure, and that reuse left patterns. Behavioral detection learned to spot them: new infrastructure, awkward language, odd timing, and requests that did not fit the conversation.

The result, Proofpoint argues, is that behavior has become a weakening signal. When AI lets attackers make every message look normal, the analysis has to change too, from asking whether a message looks unusual to asking what it is trying to do.

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