As companies invest in Artificial Intelligence (AI), assembling a team that can succeed in several types of AI projects is a complex undertaking. Furthermore, the talent shortage and the new skills and expertise necessary in AI projects require a thoughtful approach to building an AI team that meets company needs and the structure they need to succeed. We propose a conceptual framework for structuring AI teams based on Qualitative Comparative Analysis (QCA) and digital agility theory. We suggest a configurational analytics framework that examines how AI teams are embedded in a configuration of individual and AI project elements. Our conceptual model suggests five important factors to consider when building AI teams: expertise, experience, project complexity, project life cycle, and project objective. We discuss implications for theory and practice as well as future research avenues.