Agentic AI can change campaign operations

From the blog post:

Here’s what political people know but rarely say out loud: campaigns are giant, deadline-driven startups of knowledge work.

Not “knowledge work” in the TED Talk sense. Knowledge work in the gritty sense:

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A frightening amount of campaign labor is the same pattern repeated: take a messy pile of inputs, turn it into something legible, then turn that into action.

That is exactly the pattern these agentic tools are getting good at. And campaigns have endless messy piles of inputs.

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For Democratic political staff, this is an acute risk. Our coalition depends on down-ballot races, state parties, and grassroots organizations that have never had the technical resources of presidential campaigns. If agentic AI remains “for engineers only,” the productivity gap between well-resourced and under-resourced campaigns will widen dramatically, and it’ll widen fastest in exactly the races where we can least afford it.

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There’s an obvious failure mode here: everyone quietly experimenting, pasting sensitive data into whatever tool is easiest, building brittle automations with no discernible schema, accidentally recreating the worst parts of shadow IT but with higher stakes.

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The goal is not to slow people down. The goal is to prevent the inevitable “we moved fast and broke trust” moment that causes a backlash and sets adoption back a cycle. Campaigns can’t hold institutional memory about what went wrong because they dissolve. The enduring organizations have to own governance, because they’re the ones who’ll still be around to learn from the mistakes.