How Many AI Agents Are Too Many? NTT Research and Harvard University Research Reveals Key Insights for Using Agentic AI in the Workplace
NTT Research in collaboration with Harvard Center for Brain Science researchers find that enterprise AI performance depends not only on the number of AI agents, but on how humans structure, guide and coordinate multi-agent AI systems.
As organizations rapidly deploy AI agents across customer service, software development, cybersecurity, scientific research and business operations, one question is becoming increasingly important: How should organizations structure AI agent teams to achieve the best results?
New research from Dr. Hidenori Tanaka and Elizabeth Pavlova from NTT Research's Physics of Artificial Intelligence (PAI) Lab, in collaboration with Harvard University's Center for Brain Science, challenges the assumption that simply adding more AI agents automatically improves enterprise AI performance. Instead, the research shows that multi-agent AI systems perform best within an optimal operating range. Beyond that range, additional AI agents can surface competing interpretations of the same evidence, causing groups to split into camps rather than converge, depending on the task.
