Human-AI Collaboration for Scaling Agile Regression Testing: An Agentic-AI Teammate from Manual to Automated Testing
Abstract
Automated regression testing is essential for maintaining rapid, high-quality delivery in Agile and Scrum organizations. Many teams, including Hacon (a Siemens company), face a persistent gap: validated test specifications accumulate faster than they are automated, limiting regression coverage and increasing manual work. This paper reports an exploratory industrial case study of the Hacon Test Automation Copilot, an agentic AI system that generates system-level regression test scripts from validated specifications using retrieval-augmented generation and a multi-agent workflow. Integrated with Hacon's CI pipelines, the Copilot operates asynchronously as a "silent AI teammate", producing candidate scripts for human review. Mixed-method evaluation shows the AI accelerates script authoring and increases throughput, with 30-50% code reuse. However, human review remains necessary for maintainability and correct domain interpretation. Clear specifications, explicit governance, and ongoing human-AI collaboration are critical. We conclude with lessons for scaling regression automation and enabling effective human-AI teaming in Agile settings.
Keywords
Cite
@article{arxiv.2603.08190,
title = {Human-AI Collaboration for Scaling Agile Regression Testing: An Agentic-AI Teammate from Manual to Automated Testing},
author = {Moustapha El Outmani and Manthan Venkataramana Shenoy and Ahmad Hatahet and Andreas Rausch and Tim Niklas Kniep and Thomas Raddatz and Benjamin King},
journal= {arXiv preprint arXiv:2603.08190},
year = {2026}
}
Comments
Accepted at the XP 2026 Workshop on Human-AI Collaboration in Agile Teams. To appear in proceedings