<p>As the integration of Artificial Intelligence (AI) into learning, work, and daily life intensifies, the practice of outsourcing cognitive tasks to AI systems has raised concerns regarding the erosion of human control and autonomy. This article employs an immanent critique to challenge the view that attributes autonomy risks solely to implementation failures of control in practice. Instead, it reframes the theoretical roots of these risks as a systemic failure of the self-control paradigm itself. Practically, AI systems distort user control over cognition and decision-making and contribute to deskilling—autonomy challenges that cannot be resolved merely by strengthening self-control. Theoretically, the self-control paradigm fails to account for adaptive preference formation due to its overemphasis on users’ deliberative capacities and neglects of the constitutive role of algorithmic environments. To preserve and support human autonomy, we argue for the necessity of transcending the narrow conception of self-control in favor of an alternative paradigm of autonomy within Human-AI Interaction.</p>