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AI Feature Creep: Enhancing Institutional Control in Vendor Management

Session Date & Time
-
Session Room
MR 8
Standard Presentation Beginner

As AI vendors rapidly introduce new features without consulting institutions, the risks to security, compliance, and privacy grow significantly. Unapproved AI functionalities can introduce vulnerabilities, increasing the chances of data breaches and unauthorized access. These updates may also violate critical regulations like FERPA and HIPAA, complicating compliance and exposing institutions to legal risks. To mitigate these challenges, institutions must actively manage AI vendor relationships and behaviors, ensuring that vendor innovations align with institutional security, regulatory, and ethical standards. This session will provide strategies for effectively managing vendor behavior, focusing on contract management, proactive policy enforcement, and establishing clear communication channels to prevent AI feature creep. Participants will gain insights into risk assessment and best practices for holding vendors accountable, protecting both privacy and institutional integrity.

Speaker/Host

Primary/Host Speaker
Lisha Bornilla

Lisha Bornilla

Learning Tools Service Lead at UC Berkeley

Lisha Bornilla is the Learning Tools Service Lead at UC Berkeley’s Research, Teaching, and Learning division, where she manages campus-wide instructional technology platforms and their vendor relationships. She specializes in navigating the evolving edtech landscape—especially as AI features are rapidly integrated into existing tools and new products. Lisha advocates for institutional control, accessibility, and ethical implementation of digital tools in higher education. Her cross-functional work bridges pedagogy, policy, and technical infrastructure, ensuring that instructional technology adoption aligns with university values and compliance standards. With a background in learning design and master's degree in education and technology from the Harvard Graduate School of Education, she brings a systems-oriented approach to managing vendor innovation and risk in an age where AI innovation moves faster than policy and vendor roadmaps often outpace institutional readiness and oversight.

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