Optimizing AI Agent Planning with Operations Research and Data Science

# AI Agents Are Getting Too Expensive—Here's How to Fix It AI agents can rack up costs quickly, but companies can use proven mathematical optimization techniques to cut spending and allocate resources smarter. The approach treats real business problems—like deciding which tasks each agent should handle, how to spread work across your team, and staying within budget—as mathematical puzzles that software can solve efficiently. Rather than guessing, you get data-backed plans that save money while keeping your AI system running smoothly.