Could an AI company turn devoted users into a political army, the way Uber and Airbnb once did?

This explores whether AI companies could turn their users into a political force that defends the product against regulators, as Uber and Airbnb did when they used in-app prompts to send riders and hosts to city councils. The collection has no paper on this question. What it does have is material on the conditions that playbook needs: strong user attachment, a product that sits between users and other parties, and a fight over regulation. Each of those looks different for AI.

Attachment is there, and it may run deeper than it did for ride-hailing. Ted Gioia argues that some chatbot users treat the systems with something close to religious devotion, and he predicts this could harden into organized groups Are AI chatbots becoming objects of cult-like devotion?. His evidence is anecdotal. Still, it points to something Uber never had: users who are emotionally invested in the product itself, not only in cheap rides. That cuts both ways. Devoted users are easier to mobilize. They are also the people for whom an assistant nudging them toward political action looks most like manipulation. DeepMind's ethics framework names manipulation, trust and anthropomorphism as the central risks of assistants, and says the risks grow once assistants act rather than just answer What makes ethics of AI assistants fundamentally different from chatbots?. An AI that asked you to call your representative would be using the same intimate channel those risks come from.

The incentive question is also murkier. Uber could credibly say that riders and drivers shared its interest in staying legal. Azhar argues that an agent paid through merchant referral fees cannot be loyal to both the merchant and the user Can an AI agent serve both merchant and user interests fairly?. Once an AI's business model splits its loyalties, a request to 'defend your assistant' becomes much harder to read as being on the user's side. There is a further twist: the audience may be shifting. If services start competing for the attention of agents rather than people Will agents compete for attention just like users do?, the most valuable advocates could be the agents themselves, which choose, rank and recommend on users' behalf. The fight could then be over agent defaults rather than petitions.

The regulatory side is the reverse of the Uber case. Uber and Airbnb rallied users against rules. Much of the AI argument in this collection pushes for rules: the Future of Life Institute argues that companies cannot manage AI risk themselves and need binding government limits Can companies alone manage the risks of AI systems?. Users rallied to protect an AI product would be pushing back against a safety case, not a taxi lobby. The user base may also be narrower than it seems. One note finds the personal-assistant model appeals mainly to time-pressed professionals rather than typical users Does the personal assistant model actually serve most users?. Uber's riders were a broad, visible voting bloc, and the professionals who use AI assistants most heavily are a smaller group.

The collection suggests the mechanics are possible, but the result would be a different kind of political force than Uber's: more emotional, more caught up in questions of loyalty and manipulation, and possibly carried out through agents rather than people. If you want to go further, start with the merchant-loyalty note and the assistant-ethics framework. Together they explain why asking an AI's users to advocate for it is a sharper ethical move than asking a rider to sign a petition.