AI Governance. Published as architecture.
This page presents the publication portfolio of Patrick Upmann not as a list of isolated outputs, but as a structured research architecture. Across public DOI records, Zenodo publications, and foundational SSRN-listed works, the body of work spans systemic AI Governance, legal defensibility, trust infrastructure, enterprise implementation, geopolitics, education, and epistemic resilience.
One portfolio. Distinct research domains.
The earlier version grouped the works mainly by platform. This version reorders the full body of work by research logic. That makes the portfolio stronger academically and clearer for boards, institutions, media, and partners: each publication now sits inside a visible field of inquiry rather than inside a repository bucket.
From repositories to research architecture
The 16 works now unfold across foundational architecture, agentic and operational governance, trust and readiness infrastructure, legal liability, applied enterprise governance, institutional education, and strategic-geopolitical as well as epistemic governance. This makes topics such as Geopolitics and AI Slop fully visible as their own substantive research areas.
The page now shows that the publications form a coherent governance ecosystem — not just a sequence of papers across SSRN and Zenodo.
Research taxonomy
The full body of work can be read through seven clearly differentiated domains. Together they describe how AI Governance evolves from foundational architecture into operational, legal, strategic, and epistemic infrastructure.
AIGN OS, Systemic AI Governance, and the constitutional logic of the field.
How governance becomes executable in agentic systems and organisational implementation.
Certification, licensing, benchmarking, and stress-testing as governance infrastructure.
Where governance meets legal exposure, accountability, and decision defensibility.
Concrete implementation inside procurement, enterprise architecture, and SAP environments.
Education and institutional capability as long-term governance infrastructure.
Geopolitical infrastructure, navigation logic, and knowledge integrity under AI conditions.
Research domains
All 16 works are assigned below. SSRN-origin works are preserved as research records where direct file access is currently restricted; public Zenodo and DOI-linked works remain directly accessible.
Foundational System Architecture
The core architectural and constitutional layer of the portfolio. These works define AIGN OS, establish Systemic AI Governance as a field, and articulate the operating principles behind the broader governance model.
AIGN OS – The Operating System for Responsible AI Governance
Foundational paper introducing AIGN OS as a systemic governance architecture for responsible AI.
AIGN OS 2.0 – The Operating System for Responsible AI Governance (Architecture, Compliance & Trust Infrastructure)
Advances the AIGN OS architecture into a broader system logic spanning compliance, trust, and governance execution.
The AIGN Declaration on Systemic AI Governance: Defining the Operating Principles for the Age of Intelligent Systems
Defines the operating principles and constitutional logic of the AIGN approach to Systemic AI Governance.
Agentic & Operational Governance
This domain translates governance into execution logic. It includes the agentic stack and the operational architecture required to embed responsible AI inside real organisations.
AIGN OS – AI Agents: The AI Governance Stack as a New Regulatory Infrastructure
Frames agentic AI governance as a regulatory stack and extends governance beyond traditional software compliance.
Operationalizing Responsible AI: A Systemic AI Governance Architecture for Organizational Implementation
Connects governance theory to organisational execution and shows how responsible AI must be built into operational structures.
Trust, Enforcement & Readiness Infrastructure
These works build the infrastructure layer that makes governance legible, measurable, enforceable, and institutionally comparable through trust logic, readiness measurement, and resilience testing.
AIGN OS – Trust Infrastructure – Certification, Licensing, and Market Enforcement for Responsible AI
Adds certification logic, licensing pathways, and market enforceability to the AIGN OS.
AIGN Systemic AI Governance Stress Test
Introduces the stress-test logic for evaluating AI Governance resilience under pressure, complexity, and institutional exposure.
The ASGR Index – Establishing the First Global Benchmark for Systemic AI Governance Readiness
Introduces the benchmark logic for measuring governance readiness as a new unit of institutional trust.
Legal, Liability & Defensibility
Here the portfolio moves into the zone where governance turns into legal exposure. These works address defensibility, accountability thresholds, and the translation of law into governance architecture.
The Control–Liability Paradox in AI Governance: Where AI Liability Actually Begins and Why Decisions Cannot Be Defended
A board-level governance paper on the point at which accountability shifts from organisational abstraction to legally exposed decision-making.
AIGN Legal – From Law to Architecture: Institutionalising Systemic Legal AI Governance
Reframes legal AI governance as a systemic architectural discipline rather than a purely interpretive legal exercise.
Applied Enterprise Governance
These works make the portfolio concrete inside enterprise environments. They show how governance is embedded in procurement decisions, platform architecture, and operational business systems.
AIGN – AI Governance Compliance Framework for SAP® S/4HANA
Shows how AI Governance can be embedded inside enterprise infrastructure through a concrete SAP-focused governance model.
AIGN – Procurement Governance Gate
Defines procurement as a governance decision point and embeds AI accountability earlier in organisational buying logic.
Institutional & Educational Governance
This work expands governance beyond compliance into institutional capability formation. It treats education as a structural prerequisite for sustained responsible AI practice.
The AIGN Academy – Institutionalizing Systemic AI Governance Education
Positions education as governance infrastructure and builds a bridge between institutional competence and responsible AI readiness.
Strategic, Geopolitical & Epistemic Governance
This domain captures the strategic outer edge of the portfolio. It includes AI Governance as geopolitical infrastructure, the organisational inability to create unified future logic, and the epistemic fragility introduced by synthetic knowledge amplification.
The Geopolitics of AI Governance – AI Governance as a Geopolitical Infrastructure
Positions AI Governance beyond compliance and into sovereignty, geopolitical capability, and strategic institutional design.
The AI Navigation Gap: A Cross-Domain Analysis of Why Modern Organizations Cannot Form a Unified Future Logic
Addresses the organisational inability to align AI direction, governance, and long-term logic across domains.
AI Slop in the Enterprise: Synthetic Knowledge Amplification and the Governance of Organisational Knowledge Infrastructures
Examines synthetic knowledge pollution inside organisations and frames it as a governance challenge for knowledge infrastructures and epistemic integrity.
Foundational research records
The following papers remain central to the architecture of the portfolio. They are shown here as documented records because direct access to the original SSRN files is currently limited, while authorship, year, title, and DOI trace remain preserved.
Foundational SSRN-origin works are intentionally displayed without active document links. This avoids dead or unreliable access paths while keeping the scientific record visible and correctly attributed.
AI Governance began to matter when accountability crossed the threshold from systems to people.Patrick Upmann