Who does what inside an organization.
18 resources
Guidance on establishing AI governance operating models within organizations. It covers governance committee structures, roles and responsibilities, decision-making processes, and integration with existing risk management frameworks.
Guidance on the Chief AI Officer role, including responsibilities, required competencies, organizational positioning, and relationship with other C-suite roles. Addresses both technical and governance aspects of AI leadership.
Template and guidance for creating AI governance RACI matrices. Defines who is Responsible, Accountable, Consulted, and Informed for key AI governance activities across the AI lifecycle.
Guidance on establishing AI ethics boards and oversight committees. Covers composition, mandate, decision-making authority, reporting lines, and integration with corporate governance structures.
An educational resource explaining AI governance principles including model development, validation, and transparency requirements. References Canada's Directive on Automated Decision-Making as an example of how governments implement AI governance frameworks with scoring systems for human oversight and monitoring.
A framework for establishing AI governance operating models and developing core capabilities to mitigate risks in AI implementation. The resource focuses on organizational structures and processes needed for effective AI governance in enterprises.
A guide for building AI governance operating models that includes RACI (Responsible, Accountable, Consulted, Informed) role definitions, workflows, approvals, and controls. The resource focuses on helping organizations scale AI responsibly while managing risk and maintaining compliance.
This resource defines the role of a Chief AI Officer (CAIO) as an executive responsible for overseeing AI technology development, strategy, and implementation within organizations. It provides guidance on the responsibilities and importance of this emerging leadership position in AI governance.
A guide examining the emerging role of Chief AI Officer (CAIO) and their responsibilities in leading organizational AI transformation. The resource focuses on how CAIOs can integrate AI into companies while building more agile, innovative, and responsible organizations.
Wikipedia article defining the Chief AI Officer (CAIO) role as a senior executive position responsible for overseeing artificial intelligence strategy, development, and implementation within organizations. The resource provides information about this emerging C-suite position that focuses on AI governance and strategic oversight.
This research paper explores how AI companies can improve their risk governance by establishing AI ethics boards. The authors identify five key design choices including board responsibilities, legal structure, and other organizational considerations for effective AI ethics oversight.
A practical guide for organizations on establishing AI ethics boards to oversee responsible AI development. The resource covers different board structures, including internal and external board models, and provides guidance on implementation and governance processes.
A research paper providing guidance on designing AI ethics boards, covering structural considerations including internal versus external board configurations. The work examines the role of ethics boards in AI governance and offers practical recommendations for implementation within organizations.
A RACI (Responsible, Accountable, Consulted, Informed) matrix template specifically designed for AI governance. The template helps organizations define clear ownership and responsibility across all stages of the AI lifecycle, from model development and validation to deployment and audit.
A RACI (Responsible, Accountable, Consulted, Informed) matrix template that maps organizational roles and responsibilities for AI governance activities. The matrix is structured around the NIST AI Risk Management Framework's four core functions: govern, map, measure, and manage, helping organizations clarify decision-making authority and stakeholder involvement in AI governance processes.
A template for creating an AI Governance Charter that establishes the structure, responsibilities, and decision-making authority of an AI Governance Committee within an organization. The charter provides a framework for organizations to define guiding principles and processes for handling AI-related use cases and governance decisions.
This resource provides insights into OneTrust's approach to establishing an AI governance committee structure. It describes how their executive-level committee operates quarterly reviews of strategy, policy, and performance, while smaller working groups handle more frequent assessments of individual use cases and policy updates.
The National AI Advisory Committee is a US federal advisory body established under the AI Initiative Act of 2020. The committee provides guidance and recommendations on artificial intelligence policy and governance to the federal government. It operates under a formal charter that outlines its responsibilities and work processes.