Amazon study finds a single AI agent is the best default for enterprise workflows

Amazon researchers found that multi-agent setups burned up to 4.7 times more tokens for modest and often statistically insignificant gains

The enterprise AI world has spent a lot of energy building teams of AI agents that hand work to one another. A new Amazon study suggests most companies should start with one.

Amazon researchers found that a single, well-built agent is usually the best default for enterprise workflows. The more complex setups consumed far more tokens and time, and in many cases delivered only small improvements in exchange.

What the researchers tested

The paper is titled “Agent Architecture Cost–Success Trade-offs: A Controlled Evaluation across Enterprise-Style SOPs” and was posted to arXiv as arXiv:2611.12953 in early November 2026. SOPs, or standard operating procedures, are the step-by-step playbooks companies use for routine work.

The team ran agents through 13 realistic enterprise workflows. They compared four approaches.

The first was a function-calling single agent. That is one model that can call external tools, such as looking up a record or submitting a form.

The second was a skill-augmented agent. This is the same solo agent, equipped with prepackaged skills that guide how it handles specific tasks.