ResearchModels

CEO-Bench: Princeton tests strategic intelligence of AI agents—most fail

Researchers at Princeton University have developed CEO-Bench, a test where AI agents must run a fictional software company over 500 simulated days—only three models end with profit, and a simple rule-based algorithm beats nearly all of them.

In detail

  • CEO-Bench simulates a realistic startup scenario: NovaMind starts with zero customers and one million dollars; the AI must keep the company profitable or go bankrupt.
  • The agent controls the company via a Python API with 34 tools and 19 database tables—writes its own code, executes SQL queries, and builds custom workflows.
  • The benchmark measures not individual tasks but long-term strategic steering under uncertainty: setting priorities, allocating resources, interpreting noisy signals, adapting to change.

Why it matters

Current AI agents excel at isolated tasks but fail at complex, multi-step decisions under uncertainty—exactly what executives do daily. This test shows that strategic intelligence remains unsolved.

For you Do not assume today's AI agents can steer your business independently—they are ready for operational single tasks, not strategic overall responsibility.

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