EAAP - Enterprise AI Architecture Pattern - A Governance Architecture for Deterministic Enterprise AI Systems

EAAP: Enterprise AI Architecture Pattern – A Governance Architecture for Deterministic Enterprise AI Systems defines a comprehensive governance‑first architectural model for deploying artificial intelligence in high‑trust, high‑impact enterprise environments. The paper argues that enterprise AI failures stem not from model capability but from architectural gaps: missing evidence provenance, absent confidence calibration, weak human‑approval enforcement, uncontrolled multi‑domain reasoning, and direct AI access to operational systems.

To address these structural weaknesses, the paper introduces the Enterprise AI Architecture Pattern (EAAP) a layered, governance‑deterministic framework that positions the large language model as a replaceable reasoning component inside a controlled, auditable system. EAAP defines six architectural layers: Governance, Orchestration, Domain Intelligence, Knowledge & Evidence, Execution, and Audit & Traceability. Each layer enforces strict boundaries, ensuring that AI‑assisted reasoning remains transparent, traceable, and subordinate to human authority.

Key contributions include:

• a formal definition of governance determinism, distinguishing architectural control from computational determinism;

• a nine‑category threat model covering hallucination, governance bypass, prompt manipulation, evidence poisoning, domain contamination, automation bias, stale approvals, orchestration deadlock, and execution boundary bypass;

• a structured evidence classification model requiring provenance disclosure for all AI recommendations;

• a tiered human approval boundary that enforces oversight for high‑impact actions;

• an Automation Gateway that isolates AI systems from direct infrastructure access;

• and a Conditional Override mechanism that escalates uncertainty rather than allowing autonomous continuation.

Designed for sovereign, air‑gapped, and regulated environments, EAAP provides an architectural blueprint for organisations seeking to deploy AI safely without relying on policy‑only governance or model‑centric alignment approaches. The paper concludes with limitations, non‑goals, and future research directions, emphasising that EAAP is a governance constraint framework, not a product or certification scheme.