Pendo introduces analytics platform for AI agent performance tracking
Pendo's new Agent Analytics platform helps businesses measure and optimize AI agent performance, addressing the challenge of proving ROI in agentic AI investments.
By Shane Snider, Senior News Writer
Published: 17 Jun 2025
Pendo on Tuesday launched Agent Analytics, touted as the first platform designed to measure and optimize the performance of agentic AI software. The platform enables businesses to track AI agent performance similarly to human employees and monitor adoption like SaaS applications.
Key Features of Agent Analytics
- Provides metrics and reports for both in-house and third-party AI agents
- Tracks agent behavior alongside traditional software
- Aims to help enterprises demonstrate ROI from AI investments
Pendo CEO Todd Olson said the platform emerged from customer demand: "What we heard loud and clear from the companies we work with is that there is an enterprise-wide mandate to start experimenting and trying out new agentic technologies."
The Challenge of AI ROI
Recent data highlights the urgency for such solutions:
- 48% of tech executives surveyed by EY are adopting or have deployed agentic AI
- 43% report more than half their AI budgets go toward agentic AI
- Only 25% of AI initiatives delivered expected ROI in past 3 years (IBM report)
Pradeep Sanyal, AI leader at Capgemini, noted: "Enterprises are investing heavily in agentic AI... many leaders admit they still lack the tools to track impact or even define success."
Why Traditional Analytics Fall Short
Sanyal explained the unique challenges:
- AI agents are autonomous and goal-seeking
- They behave like digital employees
- Legacy tools can't adequately measure their value creation
Olson positioned Agent Analytics as a solution: "We envision companies using this product to iterate and update the agents until you reach a point where you are getting that ROI."
Industry Reaction
Gartner's Arun Chandrasekaran called it "a win for AI governance, ROI measurement and automation efficiency."
Sanyal concluded: "It's not just a useful tool. It is a critical step toward scaling AI responsibly and capturing the returns enterprises have been chasing."
Shane Snider covers IT infrastructure at Informa TechTarget.
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About the Author
Dr. Emily Wang
AI Product Strategy Expert
Former Google AI Product Manager with 10 years of experience in AI product development and strategy formulation. Led multiple successful AI products from 0 to 1 development process, now provides product strategy consulting for AI startups while writing AI product analysis articles for various tech media outlets.