Why Technical Accuracy is the Wrong Metric for Agent Success
Technical accuracy is failing AI agents. Here's what actually matters.
Why it matters
As enterprises deploy AI agents at scale, the industry is discovering that traditional ML metrics (accuracy, precision, recall) don't predict real-world business value. Salesforce argues for a human-centered quality framework that measures what actually matters: user satisfaction and business outcomes.
The key facts
7 to knowSalesforce proposes shift from technical metrics to human-value framework for agent evaluation
Gap identified between system logs and lived user experience in agent deployments
Implies enterprises are deploying agents without adequate success metrics
Salesforce argues for human-value-based quality framework over technical accuracy metrics
Focus on gap between system logs and lived user experience
Relevant to enterprise AI deployment decision-making
Published May 2026 — reflects maturation of agent deployment phase
Go to the source
Salesforce Blogsalesforce.com
Publisher excerpt: Close the gap between system logs and lived experience with a quality framework built for human value.