Kayode Ishola

Research Interests

My research examines the security, governance, and data quality implications of deploying AI systems in institutional information environments. Drawing on case studies from production AI cataloging deployments at a major R1 research university, I develop and validate cybersecurity frameworks, data governance models, and human-in-the-loop quality assurance mechanisms for AI-assisted bibliographic metadata pipelines. My work sits at the intersection of Library and Information Science, Information Security, and AI Governance, grounded empirically in systems I have designed and operate.

Publications

Ishola, K., Moutran, H., Williams, W., Chang, B., Halaychik, C., Choate, A., & Hossain, G. (in peer review JISTap). Automating the path from physical media to discoverable bibliographic records: A production AI pipeline for legacy music collections. Submitted to: Journal of Information Science Theory and Practice (JISTaP).

Ishola, K., Moutran, H., & Hossain, G. (in preparation). Human-in-the-Loop data governance for AI-assisted bibliographic metadata: A framework for quality assurance, provenance accountability, and error detection. Target: Cataloging and Classification Quarterly/JASIS&T

Ishola, K., & Hossain, G. (in preparation). Security-by-design in AI-assisted library information systems: A framework for threat modeling and compliance. Target: Computers and Security or IEEE Access.

Ishola, K., & Hossain, G. (in preparation). Cybersecurity risks in AI-assisted library systems: A systematic review using PRISMA 2020. Target: Computers and Security.

Ishola, K., Moutran, H., Williams, W., Chang, B., Halaychik, C., & Choate, A. (Book Chapter in Submission). From backlog to discovery: A multi-batch practitioner case study of an AI-assisted cataloging pipeline for legacy music collections. In K. Glover & E. Decker (Eds.), Practical applications and case studies for AI-augmented library operations. IGI Global Scientific Publishing. [Proposal accepted May 2026]