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Report

AI in Higher Education: Learner-Centered Insights for Policymakers and Practitioners

July 2, 2026

This series of reports from Southern New Hampshire University’s (SNHU) Center for Higher Education Policy and Practice (CHEPP) is intended to educate policymakers, higher education leaders, and other stakeholders on how institutions are currently engaging with AI tools and capabilities, why their role in shaping AI use cases in learning environments is critical to the future of higher education, how they are mitigating or managing risk factors, and the ways in which AI is showing potential to fundamentally change teaching and learning. Central to these topics are the individual learners: how they are experiencing or benefitting from AI, or conversely, where institutions need to exercise care to avoid potential learner harm. Click here to here to learn more about the AI in Higher Education series .

Report

AI in Higher Education: A Primer for Higher Education Policymakers and Leaders

July 2, 2026

A greater understanding of AI’s components, defining features, and how it operates is critical to making informed decisions about its use. This primer provides an overview of key AI definitions and capabilities as well as a glossary of key terms to help practitioners, leaders, and policymakers understand the implications of AI. Click here to here to learn more about the AI in Higher Education series .

Report

AI in Higher Education: Teaching and Learning – Applying a Learner-Centered Lens to AI Integration

July 2, 2026

An important start to the discussion of AI in higher education is its application to teaching and learning. This report provides an overview of how AI is being thoughtfully integrated into teaching and learning in higher education and how universities and colleges must play a critical role in that process. Central to this process is the role of learner agency and awareness in the learning process and the extent to which AI can be used in ways that can augment rather than replace learning. In terms of academic relevance and engagement, faculty and instructors are grappling with how to effectively and authentically assess learning, the importance of preparing students for an AI-era workplace, and what guardrails or guidance is needed to ensure academic integrity. Finally, the learner experience in higher education has the potential to be transformed through AI agents, chatbots, and other tools that reduce repetitive and administrative workloads. Institutional leaders have important decisions to make in each of these areas. Each of these topics is covered in this report, which is comprised of three main sections: learner agency and awareness, academic relevance and engagement, and learner experience. To support policymakers and leaders as they navigate AI, there are call-out boxes throughout the report that highlight institutional challenge and decision points. Click here to here to learn more about the AI in Higher Education series .

Report

AI in Higher Education: Infrastructure and Operations – Key Enablers of AI Strategies

July 2, 2026

Higher education institutions are complex organizations. Teaching and learning are presumed to be their core purpose, and yet, their operational and administrative functions have wide-ranging responsibilities for strategic planning, meeting regulatory requirements, fundraising, managing data and information technology, marketing, enrollment management, communications, and more. AI tools are being used across operational functions and infrastructures are being configured to support them. It is here that leadership determines how AI fits within the overall mission and culture of the institution and sets guidelines for responsible use, particularly concerning data infrastructure, privacy, and security issues. Each of these topics is covered in this report, which consists of three main sections: mission and culture, vision and leadership, processes and infrastructure. To support policymakers and leaders as they navigate AI, there are call-out boxes throughout the report that highlight institutional challenge and decision points. Click here to here to learn more about the AI in Higher Education series .