Automation’s Early Footprint: The ATE Dataset

This post introduces the Agentic Task Ecosystem (ATE) dataset, a novel corpus of approximately 696,000 published tools across 123,000 MCP servers. It presents a quantitative analysis of the agentic AI tool landscape, revealing that only 2.6% of published tools can fully automate recognized work tasks. The analysis categorizes the ecosystem into three main patterns: existing work represented at a finer grain, infrastructure for running agents, and a small amount of genuinely new work primarily focused on agent management. It also identifies that nearly half of U.S. occupations have no agentic tools represented and that technical feasibility, rather than worker preference, predicts which occupations receive tools. The post further details how the distribution of agentic tools across occupational tasks varies by industry, with specialized tasks in healthcare and computing receiving tools, while routine tasks in legal, production, and sales remain largely untouched by automation.