AI now plays a central role in online proctoring, yet many practitioners have only a surface-level understanding of how these systems actually work. This session demystifies the computer vision technologies at the core of AI-powered proctoring and explains why purpose-built, specialized models offer substantial benefits over the generalized, off-the-shelf models commonly used in the assessment industry. Attendees will learn: - How AI is applied across different types of online proctoring (live, drop-in, record & review, automated) - The distinctions between generalized computer vision models and models trained specifically for proctoring - How proctoring specific models are trained, turned, and validated - How specialized models can increase precision and reduce false positives by up to 80% - How they can reduce processing and operational costs by nearly 70% - Why a single, unified model often outperforms multi-model systems - How configurable settings allow the same model to support live proctoring, drop-in proctoring, real-time alerts, and fully automated solutions - How specialized models lower computing and bandwidth requirements for test-takers /// Whether you are a test delivery vendor, a test sponsor, psychometrician, or test security professional, this session will give you a clearer understanding of how next-generation AI models can make online proctoring more reliable, more efficient, and more equitable for test takers.