Artificial intelligence presents new privacy challenges, but treating AI as if it lives outside the parameters of ordinary privacy law is fallacious. The emerging lesson from privacy regulators and enforcers is increasingly clear: there is no AI exceptionalism. The same principles that have long governed responsible data use still apply. What changes is how and where those principles need to be built. In these nascent days, AI offers an opportunity to move beyond “traditional” compliance by embedding privacy, transparency, and user control into the architecture itself.“Traditional” privacy compliance has often focused on collection, use, disclosure, and retention policies lined up with what a company says in its statements and privacy policies. The emerging reality with AI complicates this picture. AI infers, summarizes, remembers, ranks, and increasingly acts across blurred boundaries.That shifts AI into a category closer to delegated action, where the user is not controlling nor even observing each action. And this delegated action relationship creates a different risk profile and attack surface for privacy harms. The core concern is not only that a model may process personal data. It is that the system may decide what data it needs, access more than the task requires, move information across contexts, and act before the user fully understands what happened. What data gets inferred, shared, or disclosed might go beyond what a user is willing to share.Despite the broader AI…

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