Pendo Launches AI Agent Analytics for Enterprise Performance Tracking
Pendo introduces Agent Analytics, a groundbreaking solution to measure AI agent performance and adoption, providing enterprise-grade monitoring for digital workers.
Pendo, the software experience management platform, has launched Pendo Agent Analytics, a first-of-its-kind solution designed to help companies track and optimize the performance of AI agents. The tool provides visibility into agent behavior, adoption rates, and compliance, enabling enterprises to measure digital workers as they would human employees.
Key Features of Pendo Agent Analytics
- Behavior Tracking: Monitors user interactions across AI agents and traditional software to identify workflow changes.
- Conversation Analysis: Examines prompts and interactions to uncover trends and improve agent responses.
- Compliance Monitoring: Flags non-compliant behavior to ensure adherence to organizational standards.
- ROI Measurement: Maps agent usage to task completion, helping businesses assess the value of AI investments.
- Safety and Governance: Ensures enterprise-grade monitoring for secure and trustworthy AI deployments.
According to Pendo CEO Todd Olson, the rapid shift to intelligent software necessitates tools like Agent Analytics to support companies at every stage of their digital transformation. The announcement was made during Pendo's Pendomonium X event in New York City, where the company also revealed numerous product updates aimed at enhancing user onboarding, reducing support costs, and driving productivity.
Industry Context
A recent Forrester report, Agentic AI Agents Are A Rare Sighting, highlights the need for transparency, data security, and advanced monitoring before widespread adoption of agentic systems can occur. Pendo Agent Analytics addresses these concerns by providing actionable insights into AI agent performance.
For more details, visit Pendo's website.
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About the Author

Alex Thompson
AI Technology Editor
Senior technology editor specializing in AI and machine learning content creation for 8 years. Former technical editor at AI Magazine, now provides technical documentation and content strategy services for multiple AI companies. Excels at transforming complex AI technical concepts into accessible content.