Artificial Intelligence in Retail

Not applicable

The course is taught in  a synchronous online regime, with sessions that combine theoretical exposition, demonstration of tools, analysis of case studies and practical group exercises. The continuous evaluation model  comprises:

• Participation in online sessions and discussions: 20%
• Applied individual work (project or report on an AI application in retail): 80%

Approval criteria: final grade ≥ 10 points.

The assessment values the ability to apply the concepts to real scenarios and to articulate technical foundations with strategic management and marketing decisions in retail.

This course aims to provide students with skills to understand and apply the main tools and techniques of Artificial Intelligence (AI) to the context of modern retail. Students should be able to use data to optimize assortment management processes, dynamic pricing, demand forecasting, customer experience personalization and marketing automation. It is also intended to develop the critical capacity to assess the impact of AI on the digital transformation of the retail sector and on the creation of sustainable value for consumers and businesses.

• Introduction to Artificial Intelligence and digital transformation in retail.
• Data and algorithms: machine learning applied to demand forecasting and inventory management.
• AI applied to dynamic pricing and margin optimization.
• Personalization of the shopping experience and product recommendation.
• AI-powered marketing, CRM, and customer service automation.
• Consumer behavior analytics and intelligent segmentation.
• Ethics, transparency and privacy in the use of AI in retail.
• Case studies of AI application in physical and digital retail companies.

• - Individual and/or Group Work - 80.0%
• - Attendance and Participation - 20.0%

NAO