Establishing the Scientific Foundations of AI Governance
Patrick Upmann is the architect of the world’s first AI Governance Operating System (AIGN OS).
His work is not only shaping enterprises and regulatory frameworks, but is also published on SSRN, where it establishes AIGN OS and its components as part of the global scientific discourse.
Together, these works constitute the first coherent body of knowledge that defines systemic AI governance across architecture, paradigm shift, diagnostic methodology, and enterprise integration.
Publications on SSRN
1. AIGN OS – The Operating System for Responsible AI Governance
SSRN, 2025
Abstract:
This landmark paper introduces the 7-layer AIGN OS architecture, framing AI governance as a systemic operating system. It synthesizes regulatory frameworks, industry practices, and policy debates into a unified governance stack. The paper argues that AI governance must evolve from compliance checklists to a living infrastructure, comparable to financial reporting and cybersecurity standards. By combining global regulation, ISO standards, and governance-by-design principles, AIGN OS is positioned as a certifiable and scalable framework for enterprises and regulators worldwide.
👉 Read on SSRN
2. AIGN OS – AIGN OS -AI Agents: The AI Governance Stack as a New Regulatory Infrastructure
SSRN, 2025
Abstract:
This paper explores the paradigm shift from SaaS to AI Agents. As autonomous systems increasingly replace traditional applications, governance must be reimagined as a regulatory infrastructure stack. The paper shows how agentic AI challenges attribution, liability, and system control, and why governance cannot remain an afterthought. It introduces the concept of the AI Governance Stack as a regulatory meta-layer, ensuring systemic accountability for agent-driven economies. Positioned within broader debates in law, economics, and computer science, this publication reframes AI governance as a structural requirement for digital markets.
👉 Read on SSRN
3. AIGN Systemic AI Governance Stress Test
SSRN, 2025
Abstract:
Inspired by financial stress-testing methodologies, this paper introduces the first systemic stress test for AI governance. It provides regulators, auditors, and enterprises with a framework to evaluate resilience, compliance, and trust under different scenarios. Drawing on parallels with banking regulation, the stress test measures exposure to risks such as bias drift, shadow AI, and governance fragmentation. By operationalizing governance readiness, the paper offers a diagnostic tool to move from abstract principles to measurable safeguards. This contribution positions AI governance as auditable and enforceable within systemic infrastructures.
👉 Read on SSRN
4. AIGN – AI Governance Compliance Framework for SAP® S/4HANA
SSRN, 2025
Abstract:
This publication demonstrates how AI governance can be operationalized inside enterprise systems. Using SAP® S/4HANA as a reference model, it translates compliance principles into concrete governance controls and integration patterns. The paper outlines how ERP infrastructures can embed AI trustworthiness, regulatory alignment, and accountability-by-design. It also highlights the implications for global enterprises managing large-scale, mission-critical systems. By bridging governance theory with enterprise practice, this paper positions AIGN as the first governance framework directly applicable to ERP transformation and AI adoption at scale.
👉 Read on SSRN
Significance
Together, these four publications establish a coherent body of knowledge:
- Architecture → AIGN OS
- Infrastructure Shift → AI Agents
- Diagnostic Methodology → Stress Test
- Enterprise Application → SAP S/4HANA
This integrated body of work positions Patrick Upmann as both a visionary architect and a scientific standard-setter for the future of AI governance.
Citation Notic
- All works are published and date-stamped on SSRN, securing authorship and intellectual property.
- Non-commercial citation is permitted with attribution.
- Commercial use requires prior written permission.