The integration of artificial intelligence (AI), and particularly generative AI, into research methods is rapidly transforming both academic and industry marketing research, including both methods practices and education regarding these practices. AI application within methods offers new opportunities for enhancing efficiency, automating processes, and generating insights while also presenting threats to data privacy and ethical dilemmas. This study examines the trends, perceived benefits, and challenges associated with AI adoption by marketing and other social sciences researchers, drawing on perspectives from both academic scholars and industry practitioners. Through in-depth interviews with 20 professional researchers, the study reports findings that highlight the duality of AI's potential: while it may offer significant improvements in productivity and scalability, it also raises questions about the accuracy, validity, and ethical use of its outputs. By applying a technological reflexivity framework, this study critically evaluates the consequences of AI integration into research practices, the evolving role of human oversight, and other considerations essential for responsible utilization. The discussion provides actionable insights for academic institutions aiming to prepare marketing students for an AI-enabled workplace, as well as for industry practitioners seeking to navigate the complex landscape of AI-assisted research methods.