5 metrics to measure AI-generated answers' decision-making impact
Nov 18, 2025
%20(1).webp)
Summary
This post introduces a framework for measuring the decision-making impact of AI-generated answers, focusing on five key metrics: accuracy, relevance, coherence, helpfulness, and user trust. It details how these metrics can be systematically measured and tracked to quantify improvements in decision speed, quality, and confidence, transforming AI from a promising technology into a measurable driver of better business outcomes. The platform's retrieval augmented generation (RAG) architecture grounds answers in verified company data, ensuring compliance and security.
More from the Agent Orchestration Platform trail
- AI Agents for Financial Compliance: How Enterprise AI Is Solving the Regulatory Reporting Challenge
- From enterprise search to enterprise context: what AI agents actually need
- Scale AI usage without runaway spend with Glean’s AI usage controls
- Glean Agents can now work independently, build faster, and stay governed at scale
- Glean expands horizontal, agent platform with open agent interoperability, dozens of personal and business agents, and comprehensive AI security