The GenAI in Retail Certification is a hands-on, applied program that teaches students how generative AI is actually used in modern retail and merchandising roles. Students learn to work with large language models, no-code AI tools, and creative AI to support real tasks such as assortment planning, promotions, content creation, and shopper engagement—while understanding the limits and responsibilities of using AI in business.

Retail is rapidly adopting generative AI, and employers now expect graduates to be comfortable using these tools as part of everyday work. This certification focuses on practical skills, not just theory—how to design effective prompts, evaluate AI outputs, and translate results into business decisions that drive impact.

By completing the certification, students graduate with a portfolio of hands-on projects and a clear signal to employers that they are ready to apply AI responsibly in retail environments. It is designed to complement the Retail Studies Minor by connecting core retail concepts with the technologies shaping the future of the industry.

An overview of what five sessions of this program will cover . . . .

• Session 1 (Monday, Jan 26, 2026 | 6:30–7:45 PM) – Foundations of Generative AI & Productivity
  Learn what generative AI is, how large language models and image models work. You’ll also see how AI productivity tools are already being used in everyday workflows to save time and improve output quality by Jodi Goldsberg, Director, Global Business Applied AI (GBAI) Google.
• Session 2 (Wednesday, Feb 18, 2026 | 6:30–7:45 PM) – Prompt Engineering and AI Safety 
  In this session, you’ll learn core prompt techniques (zero-shot, few-shot, role-based) and how to add guardrails that improve accuracy, consistency, and safety. We’ll cover common risks like hallucinations, bias, and sensitive data exposure, and apply practical safety checks. You’ll build a ready-to-use prompt library designed for safe deployment..
• Session 3 (Tuesday, Mar 10, 2026 | 6:30–7:45 PM) – AI in Consumer Shopping & Retail Merchandising
  Explore how shoppers actually use AI today, from conversational search and recommendations to personalized shopping experiences. Through real retailer case studies, you’ll learn how AI influences consumer behavior and where its use in merchandising makes sense—and where it does not.
• Session 4 (Thursday, Apr 22, 2026 | 6:30–7:45 PM) – Hands-On Workflows with GenAI
  Experience the full capability of AI tools in action. You’ll see an end-to-end retail workflow that combines no-code tools, text generation, and image generation to support tasks like assortment decisions, product content, and promotional visuals.
• Session 5 (Monday, May 18, 2026 | 6:30–7:45 PM) – Capstone: AI in Action
  Apply everything you’ve learned in a team-based capstone project. You’ll design and present a GenAI solution to a real retail problem, demonstrating how AI can be used responsibly to drive merchandising decisions and business impact.

Our Instructor

Jodi Goldberg is a senior product and retail leader at Google, where she currently serves as Global Director of Product Strategy. With over 13 years at Google, Jodi has held leadership roles spanning product strategy, product marketing, industry partnerships, and revenue growth—working at the intersection of AI, ecommerce, and enterprise productivity.

Throughout her career, she has led cross-functional teams responsible for building and scaling AI-enabled tools used across Google’s sales and product organizations, advising global retailers on consumer trends, and shaping go-to-market strategies for large, complex businesses.

Beyond Google, Jodi is deeply engaged in the startup and academic ecosystems. She has served as an advisor to Google for Startups, CapitalG, and multiple early-stage companies, and is a Senior Fellow & Advisory Board Member at the Retail Management Institute at Santa Clara University, where she supports the institute’s strategic direction and industry partnerships.

Jodi brings a rare combination of industry depth, product leadership, and practical AI perspective, making her a valued voice on how modern organizations adopt AI to improve productivity, decision-making, and everyday work.

Our Instructor

Akshay Jagadeesh is a Member of Technical Staff (Resident) at OpenAI, where he focuses on AI safety, reliability, and alignment, with an emphasis on building AI systems that can be trusted in high-impact domains such as health and medicine.

He brings a strong academic foundation, having earned his PhD from Stanford University, where he studied how the human brain represents information and compared biological intelligence with deep neural networks. He later completed a postdoctoral fellowship at Harvard Medical School, extending this work into perception, attention, and computational modeling.

Akshay’s interdisciplinary background in neuroscience and machine learning informs his approach to AI safety as a systems-level challenge—ensuring advanced AI models are robust, interpretable, and aligned with human values.

Our Instructor

Dan Demeyere is the Chief Product and Technology Officer at ThredUp, where he leads product, engineering, data, and platform teams for one of the world’s largest resale and recommerce marketplaces. With 15+ years at ThredUp, Dan has played a central role in scaling the company from early-stage startup to a public company.

As CPTO, Dan is responsible for aligning product strategy, technology execution, and marketplace economics, ensuring that ThredUp’s platform delivers sustainable growth across supply, demand, pricing, and operational efficiency. His leadership spans Product Management, Engineering, Infrastructure, Data Science, and Growth bridging deep technical execution with business outcomes.

Previously, Dan served as Chief Product Officer, where he led Product and Engineering through ThredUp’s IPO, and as VP of Engineering, where he scaled customer-facing platforms and core infrastructure. Across these roles, he partnered closely with finance and executive leadership to optimize unit economics, forecasting, and marketplace levers while maintaining high engineering velocity.

Dan began his career as a hands-on engineer and progressed through every layer of technical leadership Full Stack Engineer, Lead Engineer, Director of Engineering bringing a builder’s mindset to executive decision-making. His background gives him a rare perspective on how technology, data, and product strategy intersect in modern retail and ecommerce platforms.

He is widely respected for translating long-term vision into execution, building high-performing teams, and scaling complex systems that power data-driven retail marketplaces.

Our Faculty

Hiring managers from a variety of industries share their thoughts on the Certification difference.