Can LLMs Be CEOs? Benchmarking Strategic Resource Reallocation with Multi-Role Agent Simulation
Researchers have developed CEO-Bench, a new benchmark designed to evaluate the strategic decision-making capabilities of large language models (LLMs) in complex organizational environments. Unlike previous benchmarks that focus on isolated tasks, CEO-Bench simulates a multi-round scenario where LLM agents must integrate conflicting advice from various C-suite roles (CFO, CTO, COO, CMO) to reallocate resources. Experiments with frontier models show that while LLMs can structurally validate plans, they struggle with strategic calibration, exhibiting failure modes such as over-reliance on single advisors or historical amnesia. AI
IMPACT CEO-Bench highlights LLMs' current limitations in complex strategic decision-making, informing the development of future AI-assisted executive systems.