Responsible AI In the Age of Autonomous Agents

Abstract

Responsible AI in the Age of Autonomous Agents. As conversational AI systems evolve to become more autonomous and integrated into business operations, the need for trustworthy AI practices — including safety, privacy, security, fairness, and transparency — is more urgent than ever. These systems must be unbiased, explainable, secure, respectful of user privacy, and include human oversight to ensure they effectively address user needs.

Yet today, privacy is often violated. Testing and evaluation frameworks for conversational AI remain insufficient or underdeveloped. Many companies still lack practical tools to validate their systems beyond surface-level performance metrics and safeguard filters. Meanwhile, academic research — although valuable — is often difficult to apply in real-world product environments.

This presentation explores:
• The risks of deploying AI agents without responsible AI foundations
• The gap between academic theory and practical implementation
• The need for more applicable, business-friendly frameworks for testing AI systems
• Why measuring ROI and user impact should be part of every responsible AI strategy

The idea is to give participants a clearer view of what effective testing for conversational AI systems should look like.