Generative artificial intelligence (GenAI) is emerging as both an efficiency tool and a collaborator in marketing research. Large language models (LLMs) such as ChatGPT and Claude offer powerful affordances of speed and fluency, shaping how knowledge is produced, interpreted, and represented. However, inexpert, unethical or malicious use risks degradation of the knowledge base through generic, misleading or damaging outputs, and diminished insight quality. To support better research practice, this paper presents practical guidelines for enlisting AI as a research collaborator rather than a mere tool. The paper outlines a three-mode model of AI integration, spanning human only, task enhancement (the centaur), and full co-creation (the cyborg). An illustrative case study shows how AI adds value to research practice and identifies two enabling conditions (acknowledging the transition challenge and allowing relational engagement) and four principles for effective collaboration (co-creation, purposeful prompting, iterative reinforcement, and rich contextualization). The framework provides researchers with actionable guidance on how to incorporate AI responsibly into research practice; recognizing that output quality depends not only on technology capability, but also on how humans choose to interact with it. By critically reframing AI as an integrated cognitive partner rather than a neutral assistant, the paper contributes to methodological innovation in marketing research and to wider debates on the future of insight work in an AI-augmented environment.
Little et al. (2025) studied this question.