The use of artificial intelligence in new product development: A systematic literature review, conceptual framework, and future research agenda

Artificial Intelligence (AI) has increasingly captured the attention of scholars and practitioners, particularly following the advent of Generative AI (GenAI) technologies. This advancement has also reignited interest in AI's role in driving innovation, with New Product Development (NPD) as a key area of focus. Although prior research acknowledges AI's transformative potential, its specific application within NPD remains conceptually fragmented. This study develops an integrative, process-oriented perspective on AI in NPD. Drawing on a systematic literature review of 98 peer-reviewed articles, we inductively derive a conceptual framework grounded in organizational information-processing theory. The framework explains how AI enhances information-processing capacities and how these capacities unfold differently across the front end, development and testing, and back end of NPD. We identify five interrelated dimensions: (1) Information-processing capacities through AI in NPD, (2) application of AI in the NPD process, (3) benefits of AI in NPD, (4) enablers of AI in NPD, and (5) challenges of AI in NPD. Our findings show that AI effects are stage-dependent as well as cumulative, linking early ideation quality to downstream development efficiency and post-launch learning. We further highlight boundary conditions related to data availability, governance, and organizational readiness. We conclude our study by identifying several research gaps and proposing a future research agenda at the intersection of AI and NPD.