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Human–Ai Collaboration in Qualitative Sustainability and Supply Chain Research: Cognitive Engagement, Interpretative Depth, and Ethical Implications

Year: 2026

Type: article

Abstract: Qualitative research methods are being rapidly transformed by artificial intelligence (AI) tools, especially in the areas of data analysis and cognitive engagement. Through a qualitative study that includes interviews with academics and practitioners who actively use AI in their work, this paper explores the dual effects of AI on researcher interpretation and decision-making. Participants highlighted the risks of superficial insights, implicit bias in AI outputs, and an excessive dependence on automated results, even as they reported significant efficiency gains, such as quicker thematic analysis and idea generation. The results imply that, when applied as an adjunct to human judgment rather than as a substitute, AI can improve research. The article ends with a framework of best practices for integrating AI, recommending quick engineering, critical analysis, and ethics education to guarantee a balanced, rigorous, and reflective use of AI in qualitative research.

Source: Supply Chain and Sustainability Research (SCSR)

Authors: Rotumoi, Kibet, Kosey, Athanas, Kimanzi, Margaret

Language: English

Topic: Qualitative Research Methods and Applications

Subfield: Education

Field: Social Sciences

Domain: Social Sciences

Open Access status: diamond

OpenAlex ID: W7220287196

FWCI:

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