As organisations move AI agents from experimentation into production, the focus is shifting from proving that AI works to understanding the value it delivers. Microsoft Azure explores how agent optimisation can help businesses balance cost, performance and outcomes as AI adoption scales.

Here’s how Microsoft Foundry on Azure can help organisations understand, optimise, and manage AI costs.

Understand What Drives AI Costs
AI costs depend on more than the model you choose. Prompts, conversation history, retrieved content, tool calls, and agent workflows can all increase consumption and make costs harder to predict.
Gain Visibility Across AI Workloads
A single AI bill doesn’t tell the full story. Foundry helps provide visibility into spending across models, agents, applications, and workflows so teams can identify what is driving costs and where improvements can be made.
Optimise AI Performance and Spend
Cost optimisation isn’t simply about choosing a cheaper model. Matching requests to the right models, reducing unnecessary context, limiting tool usage, and improving agent workflows can help achieve better efficiency.
Optimise at Every Level
Effective AI cost management requires action at different speeds. Foundry supports optimisation at the request level, workflow level, and governance level, helping organisations continuously improve how their AI workloads operate.
Ask These Four Questions
Do you know what you’re paying for? Are you paying the right amount for each request? Are your agents operating efficiently? And will your spending controls hold when usage spikes? For organisations investing in AI, these questions can help turn AI experimentation into a more measurable and sustainable investment.

Take your Dynamics 365 and Power Apps further with AI that works alongside your team. Discover Infinity AI Agents and contact us today to get started.