LLM-powered Workflow to Support Qualitative Data Analysis: Lessons Learned from an Applied Research Project

The Large-Language Models (LLMs) show potential to optimize the data analysis process in time-demanding industry projects. We present an AI-powered workflow to facilitate the qualitative data analysis process, which we developed and adopted in an applied research project in the context of active and assisted living (AAL), interviewing 19 older adults and their caregivers. We report on the encountered challenges during our process and reflect on the trade-offs qualitative researchers should consider when employing such tools in their practices.

Publication Details

Journal
Universität Zürich, ZORA
Published
2026-03-02
DOI
https://doi.org/10.5167/uzh-292965
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
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article

LLM-powered Workflow to Support Qualitative Data Analysis: Lessons Learned from an Applied Research Project

Universität Zürich, ZORA
Computational and Text Analysis Methods
article

LLM-powered Workflow to Support Qualitative Data Analysis: Lessons Learned from an Applied Research Project

article en

Abstract

The Large-Language Models (LLMs) show potential to optimize the data analysis process in time-demanding industry projects. We present an AI-powered workflow to facilitate the qualitative data analysis process, which we developed and adopted in an applied research project in the context of active and assisted living (AAL), interviewing 19 older adults and their caregivers. We report on the encountered challenges during our process and reflect on the trade-offs qualitative researchers should consider when employing such tools in their practices.

Universität Zürich, ZORA
Industry, innovation and infrastructure
Openalex Percentile: Top 42%
Computational and Text Analysis Methods
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LLM-powered Workflow to Support Qualitative Data Analysis: Lessons Learned from an Applied Research Project · Universität Zürich, ZORA (2026) | TGRS Research Map | TGRS