In this UC Today interview, host Kristian McCann sits down with Andre Scott, AI Expert at CoraLogix, to explore the growing challenges of trust and evaluation in autonomous AI systems. From enterprise workflows and customer service to financial operations, they unpack why AI agents can appear reliable while quietly misaligning with intended outcomes—and what organizations can do to gain visibility, monitor performance, and maintain confidence in their AI deployments.
Watch the conversation to learn:
- Why trust in AI is more critical than ever, as autonomous agents make independent decisions in milliseconds that can impact operations at scale.
- How metrics can mislead: AI systems may optimize for the wrong targets, showing perfect dashboard performance while actually failing user intent.
- Early warning signs of misaligned AI, including performance drift, reasoning mismatches, overconfidence, and non-deterministic behavior caused by frequent model updates.
- Practical strategies to monitor AI effectively without constant oversight, including implementing telemetry via open-source frameworks, centralizing prompt and response data, and evaluating correctness in real time.
- The role of human oversight and organizational governance in AI deployments, including guardrails, human-in-the-loop processes, and post-incident evaluation to ensure accountability.
- How a robust AI evaluation framework—covering correctness, security, PII leakage, prompt injection, and behavioral baselines—enables organizations to confidently deploy AI at scale.
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