The Economics of Agent Optimization: How AI agent governance controls cost and proves ROI
This blog post is the fourth and final installment ofThe Economics of Agent Optimization, which shares the strategies, capabilities, and proof points that can help you optimize agent costs and run AI as a managed investment system on Microsoft Foundry.The first postset out the three decisions that systems rest on, the second posttook the request at runtime, andthe third posttook the workflow over time. This post takes the decision that never stops running: governing the spend.
AI agents are moving from isolated pilots into an enterprise estate. They work across teams, connect to data and tools, and make decisions with varying degrees of autonomy. For IT leaders, that creates a broader operating question: how do you govern a agentic system that can grow and act faster than traditional applications?
AI agent governancestarts with knowing which agents exist, who owns them, what...
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