When AI Agents Lose Focus: What Google’s Research Means for Supply Chain Operations

Google has identified a problem with artificial intelligence agents that deserves the attention of supply chain and logistics executives. Increasingly capable AI systems can become distracted by outdated information, pursue work nobody requested, and consume substantially more resources without advancing their assigned objectives.

In research published November 6, 2026, Google senior staff software engineer Sam Saccone and senior staff data scientist Madhuri Garikapati examined coding-agent interactions across thousands of engineers and hundreds of millions of individual agent steps.

Their findings were striking. After controlling for factors including developer, task type, model tier, and codebase complexity, sessions involving unprompted detours into unrelated software bugs were associated with 70% more agent steps, 77% more tokens consumed, and 105% more waiting time.

Although the research examined software-development agents, I believe it exposes a broader issue that supply chain technology providers and end users need to consider as autonomous systems move into operational environments.

This story was originally published by Logistics Viewpoints. Read the full story at Logistics Viewpoints →