What’s Covered?
The Generative AI Governance Framework v1.0, published with sponsorship from Connor Group and contributions from leaders in audit, academia, and industry, presents a structured and highly practical tool for organizations aiming to implement GenAI in a responsible, risk-aware way. It defines five governance domains:
- Strategic Alignment and Control Environment – Ensures GenAI initiatives support corporate objectives and risk appetite, with clear governance roles, roadmaps, ethics policies, and stakeholder input.
- Data and Compliance Management – Addresses data quality, access controls, regulatory compliance, and auditability, especially in light of evolving laws and risks from self-learning models.
- Operational and Technology Management – Focuses on integrating GenAI into business processes, validating its outputs, and managing third-party technologies, IT security, and access control.
- Human, Ethical, and Social Considerations – Covers employee training, workforce impact, bias mitigation, reputational risks, and ESG concerns.
- Transparency, Accountability, and Continuous Improvement – Promotes explainability, decision traceability, risk evolution monitoring, and responses to hypothetical or emerging risks like AI misuse or superintelligence.
The framework is built around four implementation steps:
- Define GenAI objectives that align with strategic, regulatory, and budgetary priorities.
- Scope the framework based on GenAI’s relevance across departments, functions, and stakeholders.
- Perform a governance risk assessment using a five-stage model, producing deliverables at each stage—from planning to executive reporting.
- Execute and monitor the plan, adapting governance practices over time.
The document includes detailed risk-control matrices across each domain. These cover everything from contingency planning and scenario analysis to third-party vendor assessments, output validation protocols, and audit trails for GenAI decisions.
Organizations are encouraged to adapt this framework alongside COSO, COBIT, or the Three Lines Model. The authors also offer a maturity model and benchmarking services through genai.global.
💡 Why it matters?
GenAI is creeping into every layer of modern organizations—often without clear visibility or governance. This framework gives risk officers, auditors, and C-suite leaders a structured, customizable playbook for ensuring GenAI is used responsibly. It turns a fast-moving challenge into something tangible and manageable.
What’s Missing?
The framework is deeply operational and security-driven, but:
- It underweights AI-specific harms like hallucinations, misuse for manipulation, or dynamic emergent behaviors, which may need stronger real-time safeguards.
- There’s limited integration with AI-specific laws like the EU AI Act or NIST AI RMF. The framework mostly assumes governance happens internally, without strong links to external regulatory frameworks.
- It emphasizes risk mitigation and performance metrics, but doesn’t fully explore value alignment or long-term safety—especially for advanced or autonomous systems.
- While it touches on ESG and social risks, it doesn’t dive into equity or global asymmetries, which are critical in scaling GenAI responsibly.
- There’s little room for public transparency or red-teaming structures—oversight seems focused on internal processes and board reporting.
Best For:
Ideal for internal auditors, compliance teams, GenAI governance leads, or enterprise risk managers looking to formalize oversight without reinventing their entire control stack. Especially relevant for companies scaling GenAI adoption in regulated sectors or those under board scrutiny.
Source Details:
Title: Generative AI Governance Framework v1.0
Authors:
- Scott A. Emett, PhD – Associate Professor, Arizona State University; expert in financial decision-making shaped by tech.
- Marc Eulerich, PhD, CIA – Dean and Professor, University of Duisburg-Essen; heads the Mercator Audit & AI Research Center.
- Jason Pikoos – Managing Partner at Connor Group; specialist in GenAI-driven solutions for financial and ops transformation.
- David A. Wood, PhD – Professor, Brigham Young University; recognized among the most influential in accounting, with 160+ publications.
Sponsors and Contributors:
- Connor Group – Consulting firm for high-growth companies, backing the framework.
- Boomi – SaaS integration company supporting practical adoption and transparency tools.
