Berkeley RDI launches AI agent benchmark across 55 industries with 1,500+ tasks

AI agents—systems that operate autonomously to complete professional workflows—have emerged as a focus area for both researchers and enterprises seeking to automate complex, knowledge-based work. However, evaluating whether these agents actually perform reliably on real-world tasks has lacked a standard, industry-wide framework. Agents' Last Exam addresses this gap by building a comprehensive evaluation platform that measures agent performance against tasks drawn from actual professional practice across dozens of industries.

The involvement of 300+ industry experts suggests the benchmark is being anchored to work that practitioners recognize as meaningful and economically significant, rather than academic test cases disconnected from how agents will actually be deployed. By requiring verifiable outcomes and maintaining objective, comparable scoring across different professional domains, the benchmark aims to create a shared standard that both builders of AI agents and users evaluating them can rely on. The trajectory toward 5,000 tasks—moving from 1,500 currently collected—indicates this is a long-term effort to build breadth and depth across professional fields.