  We study the use of large language model-based agents for interacting with
software via web browsers. Unlike prior work, we focus on measuring the agents'
ability to perform tasks that span the typical daily work of knowledge workers
utilizing enterprise software systems. To this end, we propose WorkArena, a
remote-hosted benchmark of 33 tasks based on the widely-used ServiceNow
platform. We also introduce BrowserGym, an environment for the design and
evaluation of such agents, offering a rich set of actions as well as multimodal
observations. Our empirical evaluation reveals that while current agents show
promise on WorkArena, there remains a considerable gap towards achieving full
task automation. Notably, our analysis uncovers a significant performance
disparity between open and closed-source LLMs, highlighting a critical area for
future exploration and development in the field.
