AI-Assisted Automation for Maintaining User Documentation - Lassila, Joni (My University, 2026)
This study investigates how artificial intelligence can support the process of updating user documentation in an enterprise software environment, where documentation maintenance has traditionally been a manual and time-consuming task. The research was conducted as a case study in an enterprise environment, where an AI-assisted solution was designed and implemented using Microsoft Power Platform technologies. The solution uses large language models to analyze software change descriptions, such as release notes, and compares them against existing documentation to identify outdated content. The process follows a human-in-the-loop approach, in which the documentation maintainer reviews and approves all changes before they are applied. The evaluation was performed using real documentation update cases. The results show that the AI-assisted approach reduces the time required for documentation updates by approximately 48%, particularly in identifying relevant documents and sections. The solution performed best when modifying existing documentation, while generating new content remained more challenging. The findings highlight the importance of human control to ensure accuracy and consistency with documentation standards. The study concludes that AI-assisted solutions effectively support documentation maintenance by reducing manual effort and improving efficiency, while still requiring human validation. The results suggest that such systems function most effectively as decision-support tools rather than fully autonomous solutions.
Keywords: artificial intelligence; large language models; intelligent document processing; documentation maintenance; Microsoft; Microsoft Copilot Studio Agent