Agentic Stability Framework: A Force-Based Enterprise Architecture Framework for Autonomous AI Systems

Enterprises are moving from assistive AI to agentic AI. Agentic systems can reason, plan, call tools, access memory, coordinate with other agents, and act on enterprise systems — which changes the central question from "is the output accurate" to "can the enterprise govern what this system is allowed to do." The Agentic Stability Framework (ASF) is an enterprise architecture assessment model for determining whether the governance environment around an autonomous AI agent is strong enough to contain the operational force that agent creates, in a specific business context. ASF measures two opposing forces for a single agentic system instance — the deployed configuration of model, prompts, runtime, memory, tools, MCP servers, identity, permissions, and operating context — and reports the margin between them: Agentic Force Index (AFI) — the operational pressure created by the agent's autonomy, reach, and criticality.Enterprise Gravity Index (EGI) — the strength of the governance and control environment around it, evidence-tiered so that claimed controls are distinguished from verified ones.Stability Margin Index (SMI = EGI − AFI) — the margin between them, which places the agent in one of five orbits (Stable, Controlled, Edge, Unstable, Critical) with a corresponding default deployment decision. This release includes the full specification and whitepaper, worked examples, a threat-modeling gate, an Agent Bill of Materials (ABOM) template, and a companion assessment workbook for practitioner use. ASF is a decision-support framework, not a proof of safety, and is released openly (CC BY 4.0) for practitioner adoption and field feedback ahead of future versions.