In this panel discussion, experts examine how human oversight plays a critical role in ensuring large language models behave safely, ethically, and reliably. They'll explore emerging frameworks for evaluation, red teaming, and governance that help mitigate risk and bias in real-world deployments. The conversation will highlight practical strategies for maintaining accountability and trust as LLMs become deeply integrated into enterprise and public-sector systems.

This talk explores the operational and technical challenges of deploying LLMs for production survey analysis in regulated environments. Drawing on a real case study from a Fortune 500 financial services firm, it examines what it takes to move from LLM notebooks to enterprise-scale systems: reducing feedback analysis from 3–4 weeks to 2–3 days, achieving 92% consistency, and delivering business impact.