The proliferation of AI innovations in higher education presents significant benefits in terms of improved efficiency and enhanced learning opportunities, such as improved experiential learning, personalized support or tutoring for students, and making complex subjects more accessible, among other benefits.
But the rewards come with risks. AI raises concerns about data privacy, discrimination and bias against students and employees, and uncertain legal and regulatory environments for universities.
The evolution of the legal and regulatory environment of AI
The legal and regulatory environment surrounding AI in the United States is volatile and constantly evolving. At the federal level, congressional leaders have yet to agree on a viable AI bill that would have a realistic chance of passing both the House and Senate. As a result, the Biden administration’s executive order on the Safe, secure and trustworthy development and use of artificial intelligence The AI Executive Order remains the most coherent guidance on the federal government’s use of AI. The AI Executive Order directs federal agencies to develop technical standards and guidelines that impact the use of AI across various sectors of the economy.
Legislative activity has increased at the state level. For example, Colorado passed the first comprehensive law in the United States aimed at combating the use of “high-risk artificial intelligence systems.” The Colorado law, which will take effect on February 1, 2026, requires AI developers and entities deploying high-risk AI systems to exercise “due diligence” to prevent algorithmic discrimination. The law largely avoids regulating the use of AI systems that are not considered “high-risk.”
Unlike Colorado’s model, other states have passed laws targeting specific aspects or uses of AI. For example, several states, including California, Florida, Michigan, Minnesota, Texas, and Washington, have passed laws regulating the use of generative AI in political advertising. Other states, including Illinois and Maryland, have passed laws to ensure that individuals know when and how an AI system is being used.
The question of whether states will adopt a comprehensive or partial legislative model on AI remains open.
Importance of AI Governance
For higher education institutions to fully leverage the opportunities offered by AI while mitigating the inherent risks, proactive steps must be taken to develop and implement an AI governance framework. To put this in context, an AI governance framework is a structured set of policies, standards, and best practices designed to regulate and govern the use, development, and application of AI technologies. An effective AI governance framework can serve as a guide to ensure that AI systems are used ethically, responsibly, and in accordance with applicable legal standards.
There are many governance frameworks to consider for colleges and universities.
For example, the National Institute of Standards and Technology (NIST) published a AI Risk Management Framework to help manage risks to individuals, organizations, and society associated with artificial intelligence. The NIST framework focuses on strategies to integrate trustworthiness considerations into the design, development, use, and evaluation of AI products, services, and systems.
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Another notable AI governance framework is the “Principles of AI“OECD AI Principles” set out by the Organisation for Economic Co-operation and Development (OECD). The OECD AI Principles focus on the responsible management of trustworthy AI, including transparency, fairness and accountability of AI systems.
Regardless of which framework a college or university chooses to adopt, there are certain principles that can help manage and navigate the use of AI technologies, including:
- Responsibility
- Bias Control
- Privacy protection
- Safety and security
- Transparency
Looking forward
Going forward, the legal and regulatory environment around AI will likely remain volatile, with an ever-growing patchwork of state-level AI laws and executive orders. Colleges and universities must be proactive in monitoring the AI landscape and developing an AI governance framework that addresses how AI can be used in admissions, hiring, recruiting, and the classroom.
