Resilience Meets Autonomy: Governing Embodied AI in Critical Infrastructure

Computer Science > Artificial Intelligence [Submitted on 16 Mar 2026] Resilience Meets Autonomy: Governing Embodied AI in Critical Infrastructure Puneet Sharma, Christer Henrik Pursiainen Critical infrastructure increasingly incorporates embodied AI for monitoring, predictive maintenance, and decision support. However, AI systems designed to handle statistically representable uncertainty struggle with cascading failures and crisis dynamics that exceed their training assumptions. This paper argues that Embodied AIs resilience depends on bounded autonomy within a hybrid governance architecture. We outline four oversight modes and map them to critical infrastructure sectors based on task complexity, risk level, and consequence severity. Drawing on the EU AI Act, ISO safety standards, and crisis management research, we argue that effective governance requires a structured allocation of machine capability and human judgement. Comments: 6 pages Subjects: Artificial Intelligence (cs.AI); Robotics (cs.RO) Cite as: arXiv:2603.15885 [cs.AI]   (or arXiv:2603.15885v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2603.15885 Focus to learn more Submission history From: Puneet Sharma [view email] [v1] Mon, 16 Mar 2026 20:28:02 UTC (83 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-03 Change to browse by: cs cs.RO References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)