AI-Driven Anomaly Detection in U.S. University Networks: A Qualitative Study of Development, Implementation, and Governance
The findings reveal that the adoption and operation of AI-driven anomaly detection systems are shaped by several interconnected factors, including vendor influence, governance frameworks, and ethical considerations, which highlight the critical role of effective governance in ensuring the successful deployment and resp...