Introducing ROI for agents in Foundry

2026-07-08 · Source: Microsoft Foundry Blog articles · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems · Depth: Intermediate, medium

Summary

Microsoft Foundry introduces "ROI for Agents," a new feature now in private preview, designed to help organizations measure the business value, cost, and efficiency of their production AI agents. This tool connects agent quality, usage, and operational costs to tangible business impact, enabling teams to determine if agents are delivering sufficient value and identify areas for improvement. At its core, ROI for Agents calculates ROI using the formula (business value gained - total cost) / total cost. It integrates with Application Insights trace data, allowing users to select built-in or custom business-value evaluators and estimate operating costs. The Monitor tab within Foundry's Agents experience provides key performance indicators like Net Value, Business Value, Total Cost, and Current ROI, alongside trend charts and version comparisons, moving beyond technical metrics to a unified business outcome view.

Key takeaway

For AI Product Managers or Directors of AI/ML evaluating agent deployments, you can now directly quantify the business value and cost-efficiency of your production agents. This shifts your focus from purely technical performance to measurable ROI, enabling data-driven decisions on agent optimization, scaling, and resource allocation. Consider joining the private preview of ROI for Agents in Foundry to integrate this business lens into your agent lifecycle and ensure your AI initiatives deliver tangible financial impact.

Key insights

Production AI agent success requires measuring business value and cost alongside technical performance.

Principles

• Agent value transcends technical metrics.
• Business value models are highly customizable.
• Integrate cost, quality, and business impact.

Method

Connect traces, select a business-value evaluator, estimate value, measure operating cost, review ROI metrics, and investigate low-ROI behaviors within a unified platform.

In practice

• Define custom business value evaluators.
• Adjust cost estimates for specific scenarios.
• Analyze traces to pinpoint ROI issues.

Topics

• AI Agents
• ROI Measurement
• Microsoft Foundry
• Business Value Modeling
• Agent Performance
• Cost Optimization

Best for: CTO, VP of Engineering/Data, Product Manager, Director of AI/ML, MLOps Engineer, AI Product Manager

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Editorial summary, takeaway, and curation by AIssential. Original article published by Microsoft Foundry Blog articles.