Leadership & Governance

Governance aligned to professional institute standards

IIAIG’s leadership and governance approach reflects expectations placed on professional institutes: clear responsibilities, ethics-focused oversight and structured support for learners, academic partners and organizations working with AI systems.

Governance at a glance
  • A professional institute model with strategic oversight and stewardship.
  • Advisory input across law, risk, technology, compliance and education.
  • Ethics-oriented perspective to support AI governance and human oversight themes.
View governance & ethics charter
Structure

How IIAIG is governed

IIAIG’s governance structure separates operational work from oversight and ethical review, while creating channels for input from practitioners, academic institutions and organizations working with AI-enabled systems.

Core elements

At a high level, IIAIG’s conceptual governance model includes:

  • A governing body responsible for strategy, certification structures and alignment with IIAIG’s mission and vision.
  • Advisory input from professionals in AI, law, risk, technology, compliance and education.
  • Ethics-focused review oriented toward fairness, accountability and responsible AI practice.
  • Engagement with academic and organizational stakeholders involved in AI adoption and oversight.
Illustrative model
Governance layers

A conceptual summary of responsibilities:

  • Governing body – strategic direction, certification oversight and mission alignment.
  • Advisory input – cross-domain perspectives on governance themes.
  • Ethics-focused oversight – responsible AI considerations and fairness-aligned review.
  • Operational execution – learning design, candidate experience and partner coordination.
Roles

Roles in IIAIG’s governance model

These conceptual role descriptions outline functions that support a professional institute approach to AI governance. They describe responsibilities, not individual appointments.

Governing body
Strategy & oversight

Provides overall direction for IIAIG, including the certification pathway, alignment with mission and vision, and stewardship of AI governance themes.

Advisory input
Domain perspectives

Perspectives from law, risk, technology, compliance and education that help ensure governance themes remain grounded in real practice.

Ethics & governance
Ethics-focused oversight

Supports alignment with responsible AI practice, fairness, accountability and conceptual questions around AI-HITL themes.

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Principles

Principles guiding IIAIG’s governance

These principles help shape transparent, responsible and mission-aligned governance.

Mission alignment

Governance decisions reflect IIAIG’s mission and certification objectives.

Transparency

Clarity in role definitions, certification structures and governance themes.

Responsibility

A focus on responsible AI practice and accountability for governance themes.

Continuous learning

The governance model evolves as expectations and governance practice mature.

Ethics & AI-HITL

How ethics-focused governance connects with AI themes

IIAIG’s governance approach is compatible with a view of AI systems centered on human oversight, documentation and structured review, helping ensure alignment with responsibility-oriented perspectives.

Engagement

How governance connects with stakeholders

Governance shapes how IIAIG communicates with learners, academic partners and organizations, and how real-world feedback informs curricula and guidance.

Learners
Clarity on certifications

Governance ensures clarity in certification purpose, learning outcomes and assessment.

View certification structure
Academic partners
Program-level alignment

Governance supports alignment between institutional missions and shared program development.

For universities
Organizations
Governance themes in practice

Practical governance considerations inform how organizations approach oversight, accountability and responsible AI use.

Corporate programs