Sovereign Agents: Towards Infrastructural Sovereignty and Diffused Accountability in Decentralized AI

TL;DR

This paper explores how decentralized AI agents exhibit sovereignty through infrastructural properties, creating resilience but also diffusing accountability across multiple stakeholders, posing new governance challenges.

Contribution

It introduces infrastructural sovereignty as a framework to understand AI agency in decentralized systems and analyzes accountability issues arising from non-human sovereign agents.

Findings

Infrastructural sovereignty increases system resilience.

Accountability diffuses across multiple stakeholders.

Decentralized AI systems pose unique governance challenges.

Abstract

AI agents deployed on decentralized infrastructures are beginning to exhibit properties that extend beyond autonomy toward what we describe as agentic sovereignty-the capacity of an operational agent to persist, act, and control resources with non-overrideability inherited from the infrastructures in which they are embedded. We propose infrastructural sovereignty as an analytic lens for understanding how cryptographic self-custody, decentralized execution environments, and protocol-mediated continuity scaffold agentic sovereignty. While recent work on digital and network sovereignty has moved beyond state-centric and juridical accounts, these frameworks largely examine how sovereignty is exercised through technical systems by human collectives and remain less equipped to account for forms of sovereignty that emerge as operational properties of decentralized infrastructures themselves, particularly when instantiated in non-human sovereign agents. We argue that sovereignty in such systems exists on a spectrum determined by infrastructural hardness-the degree to which underlying technical systems resist intervention or collapse. While infrastructural sovereignty may increase resilience, it also produces a profound accountability gap: responsibility diffuses across designers, infrastructure providers, protocol governance, and economic participants, undermining traditional oversight mechanisms such as human-in-the-loop control or platform moderation. Drawing on examples like Trusted Execution Environments (TEEs), decentralized physical infrastructure networks (DePIN), and agent key continuity protocols, we analyze the governance challenges posed by non-terminable AI agents and outline infrastructure-aware accountability strategies for emerging decentralized AI systems.