Why AI matters at this scale

The John Glenn College of Public Affairs at Ohio State University is a large, influential school training the next generation of public servants, policymakers, and analysts. With a community of 1,001-5,000 students, faculty, and staff, it operates at a scale where manual processes and traditional research methods become limiting. AI presents a transformative lever to enhance its core missions: education, research, and public engagement. For an institution of this size, AI can automate administrative overhead, personalize the student experience at scale, and supercharge policy research with data-driven modeling, allowing the college to amplify its impact without proportionally increasing costs.

Concrete AI Opportunities with ROI

1. AI-Powered Policy Simulation Labs: Developing or licensing AI simulation platforms allows students to model complex policy interventions—from economic stimulus to climate regulations—in realistic virtual environments. The ROI is multifaceted: it elevates the college's reputation as a tech-forward leader, attracts research grants and partnerships, and provides students with cutting-edge, experiential learning that improves job placement rates. The initial investment in software and training is offset by the potential for new revenue streams and elevated student demand.

2. Intelligent Research and Grant Management: Faculty time is a precious resource. An AI assistant tailored to academic research can automate literature reviews, identify funding opportunities aligned with faculty expertise, and help draft boilerplate sections of grant proposals. This directly increases research output and grant capture rates. For a college this size, even a modest percentage increase in successful multi-year grants represents a significant financial return, funding further innovation and faculty positions.

3. Operational Efficiency through Administrative Automation: From processing student applications and course evaluations to managing alumni communications, numerous administrative workflows are ripe for automation using AI-driven document processing and communication bots. The ROI is measured in full-time-equivalent (FTE) hours saved, allowing staff to focus on high-touch student support and strategic initiatives. For a 1,000+ person organization, automating even 10-15% of repetitive tasks can translate to substantial annual cost savings or capacity reallocation.

Deployment Risks Specific to This Size Band

Implementing AI in a large academic unit within a major university introduces unique risks. Budget Fragmentation: While the overall organization is large, discretionary budgets for innovative technology are often siloed and competed for, making it difficult to secure upfront investment for enterprise-wide AI tools. Change Management at Scale: Rolling out new technologies across hundreds of faculty and thousands of students requires extensive training and support; resistance from established educators can slow adoption. Data Governance Complexity: The college handles sensitive student data, public records, and proprietary research. Integrating AI necessitates robust data governance frameworks to ensure compliance with FERPA, university policies, and research ethics, which can be a slow, committee-driven process. Integration Headaches: The college likely uses a sprawling tech stack (SIS, LMS, CRM, etc.). Getting AI tools to work seamlessly across these systems within a large university's IT infrastructure can be a major technical and bureaucratic hurdle.