paperAugust 2026Unreviewed

The CASE Framework: A Multi-Disciplinary Control Architecture for Governing Enterprise Agentic AI

Srinivas Telukunta, Georgios Nektarios Lilis, Lucio Baron

Abstract

Enterprises are deploying autonomous AI agents faster than they can govern them, and prevailing approaches stretch a single discipline, typically DevSecOps built for deterministic automation, across every scale of agency. We argue that agentic AI governance is four problems, not one, each with a mature governing science. The CASE framework assigns Control theory to the individual agent (intent as setpoint, guardrails as feedback, evaluation as observation), complex Adaptive systems theory to age

Cite

@misc{telukunta2026case,
  title = {{The CASE Framework: A Multi-Disciplinary Control Architecture for Governing Enterprise Agentic AI}},
  author = {Srinivas Telukunta and Georgios Nektarios Lilis and Lucio Baron},
  year = {2026},
  month = aug,
  eprint = {2608.10153},
  archivePrefix = {arXiv},
  url = {https://www.semanticscholar.org/paper/14d4b85624bbc1096651c3256dd4658507810463}
}