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AI Roles & Responsibilities: Governance, Build Teams, and Oversight
This seventh episode of the ISACA Advanced in AI Audit (AAIA) exam prep series maps out who is accountable for what when an organization adopts artificial intelligence. It walks through the categories of roles that combine to deliver a safe, compliant AI program so auditors can quickly identify whose office to visit when something goes wrong.
What this episode covers
- Why not every company has every AI role — and how company size and build-vs-buy choices shape the org chart.
- Leadership and strategy — executive management, the Chief AI Officer, and the AI steering committee.
- Developmental and operational roles — IT development, IT operations, and product management.
- The user pillar — end users plus the HR and customer service functions that support them.
- Governance and oversight — the governance committee, risk management, information security and privacy, and internal audit.
- How auditors use this diagnostic map of accountability to trace failures back to their source.
Watch the full episode above for the worked examples and detailed explanations of each concept.
Frequently Asked Questions
What are the four pillars of AI roles and responsibilities?
The four categories are leadership and strategy, developmental and operational, users, and governance and oversight. Leadership sets the vision and takes ultimate accountability, the developmental group builds and maintains the systems, users interact with the tools with support from HR and customer service, and governance provides the ethical and secure boundaries that keep the operation safe and legal.
What does a Chief AI Officer do?
The Chief AI Officer acts as the primary commander for technological integration and reports directly to executive management, functioning as the dedicated project manager for the entire company’s technological leap. Depending on company size this may be a brand-new standalone job title, or the duties may be attached to an existing executive such as the Chief Information Officer who wears two hats.
Why does every company not have every AI role?
The specific jobs a company creates depend entirely on how large it is and how it chooses to adopt the technology. Building a custom system from scratch requires data scientists, engineers, and researchers, while simply buying an off-the-shelf tool from a third-party vendor means the technology department likely will not need to hire specialized data scientists to build anything.
What is the role of internal audit in AI governance?
Internal audit serves as the independent inspector, responsible for assessing technology-related risks as a formal part of the overarching audit plan. Auditors must also know the full map of roles so that when a system fails, they can quickly determine whether it is a technical glitch from the engineers or an oversight failure from the executive board.
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Reference: This article is based on concepts discussed in AI Roles & Responsibilities: Governance, Build Teams & Oversight.