The primary goal of this project is to assess how generative AI is influencing core functions in the retail and CPG industries, including personalized marketing, product design, inventory optimization, demand forecasting, and customer service automation. With generative AI becoming increasingly accessible, businesses are exploring its potential to generate marketing content, create virtual product prototypes, simulate consumer behavior, and deliver hyper-personalized customer experiences. Students will analyze both the opportunities (e.g., cost reduction, speed, personalization) and risks (e.g., ethical issues, data privacy, over-reliance on automation) associated with adopting generative AI tools in business workflows. The outcome will be a strategic framework for responsible and effective integration of generative AI across retail and CPG value chains.
Students will begin the project with secondary research on the capabilities of generative AI tools (e.g., ChatGPT, DALL·E, Midjourney, RunwayML) and their business use cases. They will examine how major retail and CPG brands are applying these technologies in areas like product innovation, consumer engagement, virtual try-ons, packaging design, and AI-driven customer support.
Following this, students will identify challenges such as regulatory concerns, content authenticity, data security, and ethical use of AI in advertising and consumer communications. Primary data collection through interviews or surveys with marketing managers, product designers, or digital transformation officers may also be included.
The project will culminate in developing a business strategy document that includes industry analysis, a risk-benefit matrix, and implementation guidelines for generative AI adoption in retail/CPG operations. Final deliverables will include a research report, strategic recommendations, and a group presentation to communicate findings and insights.
