AgentDS Technical Report: Benchmarking the Future of Human-AI Collaboration in Domain-Specific Data Science

TL;DR

This paper introduces AgentDS, a benchmark and competition to evaluate AI and human-AI collaboration in domain-specific data science, revealing current AI limitations and the continued importance of human expertise.

Contribution

It presents a new benchmark and competition for assessing AI and human-AI collaboration in domain-specific data science tasks, with insights into AI performance and future directions.

Findings

AI agents struggle with domain-specific reasoning

Human-AI collaboration outperforms AI-only approaches

Current AI performance is near or below median of human teams

Abstract

Data science plays a critical role in transforming complex data into actionable insights across numerous domains. Recent developments in large language models (LLMs) and artificial intelligence (AI) agents have significantly automated data science workflow. However, it remains unclear to what extent AI agents can match the performance of human experts on domain-specific data science tasks, and in which aspects human expertise continues to provide advantages. We introduce AgentDS, a benchmark and competition designed to evaluate both AI agents and human-AI collaboration performance in domain-specific data science. AgentDS consists of 17 challenges across six industries: commerce, food production, healthcare, insurance, manufacturing, and retail banking. We conducted an open competition involving 29 teams and 80 participants, enabling systematic comparison between human-AI collaborative approaches and AI-only baselines. Our results show that current AI agents struggle with domain-specific reasoning. AI-only baselines perform near or below the median of competition participants, while the strongest solutions arise from human-AI collaboration. These findings challenge the narrative of complete automation by AI and underscore the enduring importance of human expertise in data science, while illuminating directions for the next generation of AI. Visit the AgentDS website here: https://agentds.org/ and open source datasets here: https://huggingface.co/datasets/lainmn/AgentDS .