GenAI in Business: Discover the Possibilities
Explore how generative AI transforms business operations, automates tasks, and drives innovation through real-world case studies and practical applications.
Explore how generative AI transforms business operations, automates tasks, and drives innovation through real-world case studies and practical applications.
This introductory course explores the transformative potential of generative AI in business contexts. Led by Andrew Wu from the University of Michigan, the course begins by examining how generative AI is reshaping industries by automating routine tasks and driving innovation in customer interactions and strategic insights. Through detailed real-world case studies, including the implementation of a generative AI-based learning assistant at the University of Michigan, participants learn how complex businesses can successfully implement generative AI solutions to enhance productivity. The course introduces the "See" phase of the See, Plan, Act framework, designed to help participants explore each step of the implementation process and understand how to connect generative AI with organizational data to create customized solutions. By the end of this course, participants will be able to identify and evaluate opportunities where generative AI can create value for their organizations, providing foundational knowledge to move forward with confidence in developing AI strategies. This is the first course in the "Generative AI in Business" specialization, designed for business professionals interested in leveraging AI to support and enhance their organizations.
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What you'll learn
Understand core capabilities of generative AI tools in business settings
Envision new business possibilities offered by generative AI
Identify opportunities for AI implementation in your organization
Recognize how generative AI can transform everyday business tasks
Understand how to connect AI with organizational data for customized solutions
Evaluate appropriate use cases for generative AI applications
Skills you'll gain
This course includes:
1.5 Hours PreRecorded video
1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 modules in this course
This course provides a comprehensive introduction to the possibilities of generative AI in business environments. It begins by exploring how this transformative technology can reshape everyday business operations across various functions, demonstrating through practical examples how workflows can be optimized. The course features an in-depth case study from the University of Michigan showing how a generative AI-based learning assistant was successfully designed and implemented to provide 24/7 support to thousands of students. Through this real-world application, participants learn valuable lessons about selecting appropriate business areas for AI transformation, integrating relevant data, and deploying strategies to maximize value. The final module unpacks key technical concepts and terminology related to generative AI, explaining how these systems function and generate content. The course emphasizes practical applications over technical complexity, making it accessible to business professionals without technical backgrounds while providing them with the knowledge needed to identify valuable AI implementation opportunities.
Introduction
Module 1 · 1 Hours to complete
GenAI in Action: Maizey Case Study
Module 2 · 36 Minutes to complete
GenAI Concepts
Module 3 · 1 Hours to complete
Fee Structure
Instructor
Pioneering Research in FinTech and Blockchain
Andrew Wu is a prominent researcher in fintech, specializing in blockchain, cryptocurrencies, and robo-advisors. He leverages machine learning and automated text analysis to examine large-scale, unstructured data, with his findings published in the Journal of Financial Economics and featured in op-eds for The Hill. Dr. Wu teaches courses on FinTech Innovations and Global Business Field Projects in FinTech, and he has conducted an Executive Education program on Smart Banking in the Age of FinTech for the Industrial and Commercial Bank of China. He earned his PhD in finance from the Wharton School at the University of Pennsylvania and holds a BA in mathematics and economics from Yale University.
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