As the use of artificial intelligence (AI) tools is becoming increasingly common in all aspects of research, there is a growing debate as to how and how much such tools will influence theorizing as well. In this viewpoint article, I discuss three plausible scenarios that could arise from a combination of efficiency pressures, practice shifts and collective choices: (i) theorizing will remain human‐centric while empirical research will be AI‐centric; (ii) theorizing will become more data‐driven and evidence‐based thanks to AI, crowding out paradigm‐based theorizing; and (iii) theorizing will be professionalized as an AI‐enhanced workflow. I compare characteristics and major implications of each scenario and reflect on skills we scholars need to develop to effectively theorize with and without AI going forward.
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Stephan Davys Manning (2026) studied this question.
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