GenAI in Business: Strategies for Successful Execution

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GenAI in Business: Strategies for Successful Execution

This course is part of Generative AI in Business Specialization

Instructor: Andrew Wu

3,056 already enrolled

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4 modules

Gain insight into a topic and learn the fundamentals.

42 reviews

Beginner level

No prior experience required

4 hours to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

42 reviews

Beginner level

No prior experience required

4 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Understand the current landscape of generative AI-driven business model transformation across a variety of industries and organization types
Identify and communicate effectively with various stakeholders affected by the transformation
Develop and apply a quantitative framework to rigorously assess the impact of generative AI on your organization

Skills you'll gain

Tools you'll learn

Generative AI

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

1 assignment

Taught in English

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This course is part of the Generative AI in Business Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 4 modules in this course

In the third course of the "Generative AI in Business" series, we focus on the "Act" phase of the "See, Plan, Act" framework. This course will guide you through a structured, five-step process to build, launch, and scale the generative AI solution you’ve planned.

During the process, we'll analyze the critical factors that drive the long-term success of your generative AI project. You’ll learn how to assemble and manage the right team, optimize the user experience, and develop an effective communication strategy for both internal and external stakeholders. Additionally, we’ll cover how to track performance after launch and proactively identify and mitigate risks to ensure your generative AI solution continues to deliver value. By the end of this course, you’ll have the tools and knowledge to confidently bring your generative AI solution to life and sustain its impact over time. This is the third course in “Generative AI in Business,” a short course series for business professionals interested in using generative AI to support, enhance, and amplify the work of their organizations.

The PAD framework provided us with a clearly defined problem to tackle using GenAI, and helped us create a blueprint for an initial blueprint for the solution. To bring that to life, let's first learn an efficient and structured process to design, test, launch, and scale your GenAI solution.

What's included

5 videos3 readings

One of the most critical decisions in your GenAI journey is choosing the right team to implement it. In this module, we will explore the concept of "innovation pods" and why this structure is ideal for implementing GenAI. You'll learn a series of strategies to hire the right talent, assemble innovation pods of the right size and composition, and manage the pods efficiently.

What's included

4 videos1 reading

A solution, no matter how powerful, is meaningless if your customers—whether internal or external—don't want to use it. In this module, we'll cover how to design the right customer experience for your GenAI project, and communicate effectively with different types of customers to minimize adoption barriers.

What's included

3 videos

Even after a successful launch, many innovative solutions fail due to a lack of ongoing oversight on the projects' progress and risks. In this module, you'll learn how to track your solution’s impact and manage risks effectively. We'll first discuss strategies to track and quantify the impact of your solution has on your business over different time horizons. Then, we'll discuss strategies to assess, track, and mitigate the risk factors unique to GenAI projects. Maintaining this oversight is key to ensuring an enduring success.

What's included

4 videos4 readings1 assignment

4 videosTotal 25 minutes

Importance of Post-Launch Oversight7 minutes
Maintaining Strong Performance Oversight7 minutes
Maintaining Strong Risk Oversight7 minutes
Course Wrap-Up3 minutes

4 readingsTotal 35 minutes

Guided Case Study Introduction5 minutes
End-of-Course Survey10 minutes
Glossary & Additional Resources10 minutes
Continue your AI education with the AI Collection from Michigan Online10 minutes

1 assignmentTotal 30 minutes

GenAI at ZStyle: The Action Phase30 minutes

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Instructor

Instructor ratings

(8 ratings)

Andrew Wu

University of Michigan

8 Courses140,449 learners

Offered by

University of Michigan

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Reviewed on May 3, 2026

Great material, with a solid case study that directly covers the "How To:" material.

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