The question of what AI means for qualitative research and researchers is already a topic of heated debate.  Perhaps less so on LinkedIn where positive appraisals seem to dominate, particularly in relation to time saved.

We will be discussing this further at our free session on 10th September - don't forget to sign up!

Such positive appraisals also exist in academia, especiallyfor those in the race to attach their names to new AI based methods although those I have seen so far seem to be lists of steps rather than fully fledged methodological considerations (see for example McTaggart and McCarthy, 2026).

Within academia however tensions between those who do notsee any place for AI in qualitative research and those who are wary but want to explore are building.  Notably this exchange has been captured in the journal Qualitative Inquiry.  Jowsey et al (2025) offered an outright rejection in an open letter with over 400 signatories highlighting the importance of the human in research practices and raising concern over both theimpact of the black-boxed algorithmic processes on research outcomes and the wider impact of damaging business practices.

In response, various academics have  have urged a softer approach (Friese et al,2026; De Paoli, 2026; Greenhalgh, 2026). Some of these authors note the increasing technologization of qualitative research prior to recent AI developments and argue that the benefits (especially time saved) outweigh the risks.  Others urge a debate which engages with the ethical challenges.  Across these debates it seems that those most closely aligned with post-positivist research are moving towards embracing AI, often with scant consideration of the issues.   Certainly Howsey et al (2026) raise significant ethical concerns which are often sidelined by those promoting AI use.

While we could argue about the ecological impacts of AI and question AI firms business practices more widely, for me it is the local ethical concerns that seem to be most often forgotten in these debates.  Marshall and Naff (2024) offer a useful reminder here that our research participants may not have provided their consent for their data to be uploaded to ChatGPT or other similar model.  Some researchers claim to be using run-local systems, but there is little detailed unpacking of terms and conditions of different platforms or understanding of how uploaded data sets might be used beyond the researchers’ own queries.

A further concern is the current trend of building-in AI options to commonly-used CADQAS tools, which may lead to novice users being unaware of their own AI usage.  We have already seen this with usage of various transcription apps, where there is often a lack of awareness of the terms and conditions associated with free versions or the concerns raised by journalists over data security.

What does this all mean in practice?  For now it means that as Saeth Consulting we are not using Gen-AI tools within our own qualitative research. For us, particularly given our research topics the ethical concerns outweigh any perceived benefit.  We do however see the importance of engaging in the debate, being educated about the(many) tools and approaches that are being put forward and keeping abreast of future developments.

References

Friese, S., Nguyen-Trung, K., Powell, S., & Morgan, D. L. (2026). Beyond binary positions: Making space for critical and reflexive GenAI integration in qualitative research. QualitativeInquiry, 10778004261429393.  (Please note the conflict of interest statements at the end of this article)

Greenhalgh, T. (2026). Reflexive qualitativeresearch and generative AI: A call to go beyond the binary. QualitativeInquiry, 10778004261429383.

Jowsey, T., Braun, V., Clarke, V., Lupton, D.,& Fine, M. (2025). We reject the use of generative artificial intelligencefor reflexive qualitative research. Qualitative Inquiry,10778004251401851.

Marshall, D. T., & Naff, D. B. (2024). Theethics of using artificial intelligence in qualitative research. Journalof Empirical Research on Human Research Ethics, 19(3), 92-102.

McTaggart, V., & McCarthy, J. (2026).Adopting an AI-Assisted Thematic Approach: Exploring Everyday Use of GenerativeAI Through Qualitative Data Analysis. In AI-Driven Research Innovationsin Computing and Information Science (pp. 37-80). IGI GlobalScientific Publishing.

See Also:

https://www.surrey.ac.uk/computer-assisted-qualitative-data-analysis/qual-ai/ai-tools-qda

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