Autonomous Micro-Enterprise Governance (AMEG): Architectural Accountability, Deontic-Epistemic Verification, and Statutory Auditability in Multi-Agent Systems

As autonomous multi-agent generative systems tran- sition from conversational prototypes to high-stakes revenue- bearing infrastructure, organizational accountability can no longer rely on extrinsic policy documents audited ex-post. This paper formalizes Autonomous Micro-Enterprise Governance (AMEG), an architectural runtime framework that embeds institutional governance and statutory mandates directly into the state- transition dynamics of autonomous firms. Extending the Au- tonomous Micro-Enterprise Architecture (AMEA) state-machine model, AMEG establishes an institutionally regulated 8-tuple Mgov = ⟨S,A,T,E,Cnorm,R,K,Λ⟩. We formalize institutional policies as a dynamic deontic constraint lattice Cnorm = ⟨O,P,F⟩ (Obligations, Permissions, Prohibitions) combined with multi- agent epistemic state tracking (K), evaluated via a deterministic validation predicate Ψ(s) prior to external settlement dispatch. To operationalize the EU AI Act (specifically Title III requirements for high-risk systems under Articles 9, 11, 12, 14, and 15), AMEG records discrete state mutations in a cryptographic, tamper- evident Merkle execution tree (Λ), guaranteeing mathematical auditability and causal traceability without persisting unbounded natural-language logs. We prove that under a sound normative lat- tice (δnorm ≥0) and bounded self-correction refinement (Kmax), the probability of an uncontained statutory violation reaching external settlement is analytically bounded. We demonstrate that AMEG decouples compliance enforcement from human monitoring payroll while preserving jurisdictional portability across emerging global frameworks.