Who’s in Charge Here? A case to explore Governance Structures, Oversight, and Capacity Building in AI for Education

ACCOUNTABILITY & LEADERSHIP IN AI

How to cite this learning scenario

Arantes, J. (2025). Who’s in Charge Here? Case Studies in AI Governance for Education. www.AI4education.org. Licensed under a Creative Commons Attribution 4.0 International License.
abstract
This case study explores the consequences of implementing AI technologies in education without established governance structures, oversight responsibilities, or institutional capacity. Based on real-world patterns, the fictionalised scenario follows a regional education authority that rapidly deployed AI tools to streamline administration and personalise learning—but lacked a clear framework for governance, monitoring, and professional learning. The result: fragmented decision-making, unclear accountability, and escalating risks. This case underscores the importance of building internal capability, clarifying roles and responsibilities, and embedding ethical AI governance at every level of the education system.

Without governance, good intentions fall apart. AI in education must be guided by more than innovation—it requires strong structures, shared responsibilities, and a workforce equipped to lead ethically.

Who’s in Charge Here?

In 2023, the Central Education Authority of a regional school system rolled out a suite of AI tools across schools to manage administrative tasks, automate assessment, and personalise learning experiences. The rollout was fast-tracked under a digital transformation agenda—but the authority had no existing policy or governance structure in place to oversee AI. At the school level, principals were unclear on who was responsible for managing AI risks or responding to ethical concerns. IT teams were tasked with deployment, but lacked training in algorithmic literacy. Teachers received no guidance on how to evaluate or question AI-generated recommendations. A growing number of issues went unresolved: AI-moderated assessments marked Indigenous cultural content as off-topic; student wellbeing flags were generated with no explainability; and concerns about data sharing with third-party vendors escalated. A report from an internal audit revealed that no central governance body existed to assess the educational, ethical, or legal implications of AI use. There was no AI literacy training for staff, no risk escalation protocols, and no mechanisms for community or student feedback. In response, the system established an AI Governance Committee with diverse representation—including educators, students, technologists, cultural advisors, and legal experts. They developed a multi-tiered governance model outlining roles, responsibilities, decision rights, and escalation pathways. Internal capability building began with AI ethics training for leaders and a new role: AI Integration Lead, to coordinate safe, inclusive implementation across the region. This case reminds us that successful AI integration in education is not just about the tools—it’s about the systems, people, and values that shape how those tools are used.

Overview

discussion and application

This case highlights the critical need for structured governance, clear oversight, and capability development to ensure ethical and effective use of AI in education.
Discussion Questions
Learning Objectives Participants will: Explore what AI governance means in an educational context and why it matters. Identify key structures, policies, and roles needed for oversight and accountability. Develop strategies to build internal capability across leadership, teaching, IT, and student support. Understand how to foster a culture of responsible AI through participatory and transparent governance.
What should an AI governance structure include to be effective in an educational setting? Who should be responsible for monitoring, evaluating, and responding to AI risks in schools or universities? How can organisations build internal capacity for ethical AI deployment and oversight? What role should student and community voices play in governance structures? How can institutions ensure shared understanding and clarity of roles when deploying emerging technologies?

supplementary materials

To support learning and application, the following resources can be integrated into planning workshops or governance reviews:  OECD: Implementing Trustworthy AI—Governance Models in Practice Australian Human Rights Commission: AI Governance Principles EDSAFE AI Alliance: Frameworks for AI Governance in Education Suggested activity: Map the current AI governance responsibilities in your school or institution. Where are the gaps? What training or coordination is needed?

AI Governance for Education: case studies
CONTACT
janine.arantes@vu.edu.au
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