As Donald Trump returns to the White House, the trajectory of AI regulation in the U.S. is set for a significant shift, diverging sharply from the policies under Biden. We anticipate a “light-touch” approach that could reshape AI innovation and development, with profound implications for higher education and nonprofit organizations, where AI’s role is rapidly evolving. Educational institutions will face a less restrictive regulatory landscape that may offer new opportunities for growth and experimentation, but this new world also demands a careful reassessment of ethical responsibilities and risk management. And paradoxically, the higher education and AI policy landscape may be more complicated as individual states pursue their own AI regulations to fill the void created by federal deregulation.

Moving Away from Safety-First AI Regulation

Under Biden, AI policy has focused on managing risks, enhancing transparency, and establishing frameworks to protect users. The administration’s 2023 executive order introduced safety mandates, such as requirements for sharing data on advanced AI systems and guidelines for secure cloud services. In addition, Biden’s AI strategy encouraged international alignment on ethical standards through collaborations with the EU and G7, positioning the U.S. within a global network committed to responsible AI.

Trump’s incoming administration signals a stark departure from this risk-averse approach. President Trump has already promised to rescind Biden’s executive order and give preference to self-regulation. You can expect Trump and a Republican Congress to focus on eliminating what is seen as unnecessary regulatory barriers.

However, this development will be complicated by the increasing AI regulations of the European Union. Just as with the GDPR, organizations in the United States will not be able to ignore European directives if they want to recruit students or maintain their online presence there.

Light-Touch AI Policies with Major Implications for Higher Education

AI-Driven Research and Institutional Autonomy

Higher education institutions stand to benefit from reduced federal oversight in their AI research endeavors. Trump’s deregulation could mean more freedom in AI exploration, potentially reducing compliance costs and streamlining the use of AI in innovative applications, from predictive analytics in student success to autonomous learning systems. However, this freedom comes with new ethical responsibilities. Without federal mandates, institutions will need to self-regulate to ensure their AI research aligns with privacy, security, and fairness standards—critical issues when AI systems directly impact students and staff.

A Deeply Fragmented Regulatory Landscape? 

AI regulation will likely become fragmented with a lighter federal framework, particularly as states pursue their own laws and standards. For universities operating in multiple states, this could create a challenging compliance environment with a patchwork of differing requirements. Institutions must stay abreast of state policies and develop adaptable compliance strategies. This state-level variability may also affect research partnerships, especially for universities working on multi-institution AI initiatives across state lines.

States are already developing AI regulations, which could actually make the higher education and AI policy landscape much more complicated than it would be under a unified federal policy.

As The Council of State Governments noted,

Since 2019, 17 states have enacted 29 bills focused on regulating the design, development and use of artificial intelligence. These bills primarily address two regulatory concerns: data privacy and accountability. Legislatures in California, Colorado and Virginia have led the way in establishing regulatory and compliance frameworks for AI systems.

In 2024, according to The National Conference of State Legislatures (NCSL), 45 states introduced AI-related bills, and 31 passed resolutions or enacted legislation. As AI rapidly advances, we can expect those numbers to increase significantly. The NCSL site is an excellent reference as it keeps track of the AI legislation in each state.

AI in Curriculum and Pedagogy

As AI becomes more integral to educational programs, the lack of strict federal guidance may enable institutions to incorporate AI into both academic and administrative settings freely. From personalized learning models to AI-assisted grading and advising, universities could experiment with these applications more flexibly. However, without standardized ethical guidelines, institutions may face public scrutiny if AI tools are perceived as biased or invasive. This places the onus on universities to develop transparent AI practices that maintain student trust and uphold educational values.

Public Trust and Ethical Responsibility

While Trump’s self-regulatory model may accelerate AI deployment, it also risks increasing public skepticism if institutions cannot demonstrate clear accountability in their AI usage. For higher education and AI policy, where trust is fundamental, universities must develop rigorous internal oversight processes. Ethical AI use—especially in areas like student data privacy and algorithmic decision-making—will be essential to avoid potential controversies that could harm institutional reputation and student relationships.

Strategic Takeaways for Higher Education and AI Policy in 2025

As the Trump administration redefines federal AI regulation, higher education institutions should proactively prepare for both the opportunities and challenges this shift may bring. Here are several strategies universities can adopt to navigate the changing regulatory landscape:

• Establish Robust Ethical AI Frameworks
  With reduced federal oversight, universities must lead in setting ethical AI guidelines that address data privacy, transparency, and fairness. Developing an ethical AI framework specific to higher education can help safeguard student trust and ensure that AI applications align with institutional values.
• Stay Vigilant on State-Level Regulations
  Without a cohesive national AI policy, state governments will likely speed up the introduction of their own standards. Universities should monitor these developments closely, especially if they operate across multiple states, to maintain compliance and anticipate any changes that could impact AI research funding or partnerships.
• Strengthen Data Security and Privacy Protections
  As AI tools increasingly integrate into academic life, universities must prioritize robust data security and privacy practices to protect students and staff. Data security becomes a vital self-imposed standard in a deregulated environment, especially when handling sensitive information through AI-driven applications.
• Promote Transparency in AI Use
  Public trust will be essential as institutions expand their use of AI. Universities should communicate openly about their AI systems, including how they are designed, deployed, and evaluated. By fostering transparency, institutions can build trust and demonstrate that AI serves educational, not exploitative, purposes.
• Develop Adaptable Compliance Strategies
  Universities should prepare for a patchwork of state-level regulations by building flexible compliance frameworks. An adaptable approach will allow institutions to respond quickly to shifting requirements while minimizing disruption to ongoing research and educational initiatives.

Please do not hesitate to reach out to us for further assistance in implementing these strategies.

Conclusion: A New Era of Responsibility for Higher Education

The anticipated Trump administration’s rollback of AI regulations heralds a new chapter for higher education and AI policy, where the increased responsibility for ethical governance may temper the benefits of deregulation. Of course, there is much more at stake in education-related policies, especially with President Trump’s promise to abolish the Department of Education, transform the accreditation process, and roll back the Title IX regulations, which provide protections for LGBTQI+ students.

However, with generative AI advancing so rapidly, focusing on K12 / higher education and the new AI policy challenges that arise will be critical. With fewer federal guardrails, institutions now bear greater responsibility in shaping how AI impacts the student experience and broader society. For universities, this shift offers a chance to lead in responsible AI use and demonstrate that academia can balance innovation with ethical stewardship. By developing their own rigorous standards and transparent practices, educational institutions can set the bar for trustworthy AI, preparing for a future where AI remains a transformative force in education and beyond.