Effective AI governance is fundamentally a multidisciplinary and cross-cutting function. AI systems impact virtually every part of an organization, including legal, ethics, data science, IT, security, and business operations. Therefore, a foundational characteristic of a successful governance program is the engagement of a cross-functional team. This team brings together diverse expertise and perspectives to ensure that policies are comprehensive, risks are identified from all angles (e.g., technical, legal, reputational), and the governance framework is integrated throughout the organization's structure and culture. Without this collaborative approach, governance efforts would be siloed and incomplete.

B. Reliance on tested vendor management processes: This is a specific component of a broader AI governance program, not its foundational characteristic.

C. Thorough reviews of a company’s public filings with experts: This is an external-facing due diligence or compliance activity, not a core, internal principle of how AI governance operates.

D. Uniform policies and procedures across developer, deployer and user roles: Policies must be tailored to the distinct responsibilities and contexts of different roles; a uniform approach would be ineffective.

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1. National Institute of Standards and Technology (NIST). (2023). AI Risk Management Framework (AI RMF 1.0).

Reference: Page 12

Section 3.1

"GOVERN." The document states

"Governance is a cross-cutting function... Effective governance requires accountability structures to implement AI risk management processes. This includes assigning roles

responsibilities

and lines of communication for different teams..." This highlights the need for coordination across various teams

which is the essence of a cross-functional approach.

2. World Economic Forum. (2021). AI Governance: A Holistic Approach to Implement Responsible AI.

Reference: Page 10

"Set up the governance structure." The report explicitly recommends establishing a "cross-functional steering committee" as a key step. It suggests this committee should include "representatives from legal

compliance

data

technology

business

and other relevant functions" to ensure a holistic view.

3. Ransbotham

S.

Kharlamov

A.

& Mazumdar

S. (2023). The New Rules of AI Governance. MIT Sloan Management Review.

Reference: In the section "Establish a Cross-Functional Governance Team

" the article states

"Effective governance requires a cross-functional team that includes business

analytics

and IT leaders... This team should be responsible for setting AI policies

overseeing AI projects

and ensuring that AI is used ethically and responsibly." This directly identifies the cross-functional team as a requirement for effective governance.