Agentic AI: User Empowerment or Enclosure?

2026-08-06

AI Summary

This study investigates whether Agentic AI empowers users or entrenches existing power structures by embedding political choices within technical architectures that diminish collective resistance. Through comparative analysis of ad blockers, recommender systems, robo-advisors, and spam governance—integrating political theory with technology governance practices—it examines how API design, protocol governance, industry standards, and default configurations encode implicit political decisions. Introducing the concept of “depoliticization,” the paper reveals mechanisms through which power is obscured in technical governance, highlighting a paradox wherein individual user experience optimization may coincide with the erosion of public participatory capacity. Findings indicate that intermediary institutions enabling adversarial contestation foster sustainable user-oriented agency, whereas closed infrastructures exacerbate marginalization, raising concerns that current Agentic AI standard-setting processes entail similar risks.

Abstract

Agentic AI promises a more flexible form of digital agency: systems that can act on users' behalf, from filtering content to negotiating prices to selecting services. Whether it will empower users is an open question, and we argue that the answer depends on more than the technology. We conduct a comparative case analysis of four more mature domains where similar forms of agency arose: browser-based ad blockers, platform recommender systems, financial robo-advisors, and email spam governance. Across the cases, decisions about whose interests agents would serve were resolved through technical arrangements: API choices, protocol governance, industry standards, and default configurations. Beyond their technical form, these were political decisions. We identify this as depoliticization, a concept from political theory, here at work in technological systems. Its most consequential effect is that individual outcomes and collective contestation capacity can move in opposite directions: spam inbox quality improved substantially while the organized capacity to contest spam governance collapsed. Where intermediary institutions sustained adversarial challenge, user-aligned agency proved more durable; where proprietary infrastructure and closed standard-setting absorbed contestation, displacement compounded. We apply this to agentic AI, where governance arrangements consolidating around the Model Context Protocol and the Agentic AI Foundation are settling these configurations before the choices that define what agents can do move outside the reach of users and the public.

Problem

• Agentic AI
• user empowerment
• depoliticization
• governance
• digital agency

Innovation

• Agentic AI
• depoliticization
• governance
• technical arrangements
• user agency