The Stanford Institute for Human-Centered Artificial Intelligence (HAI) and Amazon Web Services (AWS) have launched the Stanford and AWS Marketing Science Lab, a collaborative research initiative aimed at advancing AI and machine learning (ML) methodologies for marketing measurement. This lab unites Stanford HAI, Stanford Data Science, the Stanford University Graduate School of Business, and AWS to address marketing analytics challenges through AI/ML techniques. Leadership includes Guido Imbens (Stanford HAI-SDS Co-Director), Susan Athey and Wesley Hartmann (Stanford Graduate School of Business), and Jiafeng (Kevin) Chen (Stanford Economics). In a LinkedIn announcement, Stanford HAI highlighted the kickoff event where industry and academic AI experts gathered to initiate this collaboration, focusing on improving marketing measurement and AI/ML research. The lab aims to develop practical, scalable decision-making tools such as enhanced marketing measurement approaches, new methods for B2B customer journey analysis, and AI-driven causal inference. Expected outputs include published studies, open-source code, and prototypes. Julia White, AWS VP & CMO, was acknowledged for catalyzing the partnership. The lab’s work emphasizes causal inference and scalable tools to improve marketing measurement and solve real-world business problems, particularly analyzing B2B customer journeys. The commitment to open-source code and prototype development signals a shift from purely theoretical research to practical implementation.

This initiative exemplifies a growing trend of AI research collaborations between major cloud providers and academic institutions, relevant to higher education and EdTech sectors. Pedro Sant’Anna, Associate Professor at Emory University and Amazon Scholar, praised the collaboration on LinkedIn, noting it reflects AWS’s positive, ambitious, and business-focused engagement with academia. He anticipates strong synergies and innovation resulting from the partnership. Stanford HAI’s mission is to advance human-centered AI research, education, policy, and practice by integrating expertise from business, economics, law, medicine, and computer science. Stanford Data Science promotes embedding data science across disciplines, while the Graduate School of Business educates future leaders. The Marketing Science Lab embodies the intersection of these efforts, combining academic research with AWS’s cloud infrastructure and AI capabilities. This partnership is part of a broader pattern where academia and cloud providers collaborate to speed AI research translation and large-scale testing. For education, this lab highlights the increasing linkage of AI research to applied domains such as marketing measurement, analytics, and decision support. Its deliverables—especially open-source tools and prototypes—are expected to impact business education, analytics curricula, and digital strategy programs by integrating AI-driven methods. Additionally, the ETIH Innovation Awards 2026 were mentioned, suggesting ongoing recognition of advancements related to innovation and AI research collaborations.