Research on AI-Powered Employee Feedback Tools
This paper explores methods for employee feedback (EF) collection and introduces a new framework to improve the process. Current feedback collection process often suffers from slow workflow, bias, and poor Artificial Intelligence (AI) integration. Large Language Models (LLM) combined with human oversight may provide a more agile, objective, and user-friendly way for collecting and analyzing feedback. Existing EF tools were evaluated based on criteria such as AI capabilities, usability, and costs. Building on these findings, an open-source and self-hosted EF tool was developed. The tool integrates AI at every stage of the process and offers real-time AI assistance in writing, summarizing, and interpreting feedback. Pilot testing in two tech companies demonstrated user satisfaction.
Authors
- Ivan Filianin
- Konstantin Babushkin
- Nikolai Timofeev
Institutions
- ITMO University (RU)
Publication Details
- Published
- 2025-03-24
- DOI
- https://doi.org/10.1109/smartindustrycon65166.2025.10986092
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00