Conference Agenda

Artificial Intelligence (AI) is transforming education, government, and industry, posing urgent questions of equity, institutional preparedness, and national workforce capacity. Historically Black Colleges and Universities (HBCUs) are essential to preparing students from historically underrepresented communities for an AI economy. However, there is scant empirical research on how these institutions are constructing ecosystems of AI literacy or taking on roles in public-sector governance of AI. How do HBCUs engage with AI literacy that seeks to empower rather than exclude and what opportunities exist for them to shape the future of governance of AI in the service of greater equity? This study presents a qualitative analysis of the first [AI Institute], established by an HBCU in the Southeastern United States, examining how institutional mechanisms, partnerships, and interdisciplinary structures collectively advance AI literacy and what this reveal about national AI policy gaps.

We address three policy-relevant research questions: (RQ1): How has the [AI Institute] shaped the university's institutional approach to AI literacy, and what policy barriers or enablers does this reveal? (RQ2): How do public-sector and industry partnerships function as mechanisms for ecosystem-level AI capacity building? (RQ3): What interdisciplinary shifts have emerged, and how do they inform policy frameworks for sustainable AI integration at minority-serving institutions (MSIs)?

Data sources include institutional documents, program records, workshop evaluations, partnership materials, and public communications. These materials provide insight into programmatic adoption, partnership dynamics, interdisciplinary collaboration, and institutional practices. The analysis draws on socio-technical literacy, equity-centered AI frameworks, and institutional capacity-building theory.

Findings reveal three institutional mechanisms that collectively advance AI literacy. First, structured programming, including workshops, summits, book clubs, and training sessions, engaged 1,487 participants across 2025, providing hands-on exposure to generative AI tools and prompting faculty to integrate AI-related assignments and ethical discussions into their courses. Second, faculty development emerged as a central capacity-building mechanism. More than 75 faculty and adjunct instructors participated in major AI events, and additional faculty engaged in micro-credential pathways through national institute partners. Third, student engagement was substantial: 171 students attended the institute's flagship summit, 286 participated in a major AI event, and 1,007 students earned micro-credentials throughout the year.

Partnerships functioned as critical policy instruments. The [AI Institute] served as an evaluator for a 2025 state-level AI pilot, providing students and faculty with real-world experience assessing AI systems. This role demonstrates the potential for MSIs to contribute to public-sector AI governance, particularly in contexts requiring community accountability and ethical oversight. Industry collaborations provided significant in-kind support, including cloud credits, software access, and AI training resources. Cross-institutional networks spanning 36 HBCUs, regional partners, and K-12 districts facilitated knowledge exchange and positioned the institute as a regional hub for AI readiness.

Policy analysis reveals several gaps. Federal and state AI strategies rarely address the unique needs of MSIs, despite their central role in diversifying the AI workforce. Digital equity plans often overlook AI literacy as a core component of equitable access. Public-sector AI pilots frequently lack independent evaluators with community-centered perspectives, a role HBCUs are positioned to fill. Institutional AI governance structures remain uneven, with limited funding for faculty development, curriculum integration, and infrastructure.

This study proposes policy recommendations at multiple levels. Institutions should establish AI governance committees, integrate AI literacy across curricula, and fund sustained faculty development. States should include AI literacy in digital equity plans, support MSI-centered AI workforce policies, and formalize partnerships with HBCUs for public-sector AI evaluation. Federal agencies should expand funding for AI literacy at MSIs, develop national AI literacy standards, and incentivize equitable AI workforce development through grant programs.

This case study offers an empirically grounded model of institutional AI literacy development and highlights the critical role of HBCUs in shaping equitable AI futures. As AI continues to transform society, policy frameworks must recognize and support MSIs' contributions to national AI readiness, governance, and workforce development.