Generative AI Integration: Effects on Labor and Workforce
This course is part of Navigating Disruption: Generative AI in the Workplace.
This course examines the broader implications of generative AI integration on labor markets, workplace dynamics, and organizational relationships. Moving beyond task-level analysis, it explores how AI technologies are disrupting traditional knowledge work and redefining roles within organizations. The curriculum focuses on identifying significant disruptions across multiple organizational levels while highlighting the importance of strategic innovation and value creation when implementing AI solutions. You'll learn to assess workplace readiness for AI integration, anticipate challenges for both workers and management, and understand how AI reshapes relationships between firms and clients. The course places special emphasis on developing appropriate workplace policies to guide AI integration, examining transparency issues, and establishing standards that maintain organizational culture while maximizing AI benefits. As the third course in the "Navigating Disruption" specialization, it builds on previous foundations to address the complex interplay between AI technologies and workforce dynamics, preparing you to lead thoughtful AI implementation efforts.
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What you'll learn
Evaluate your organization's readiness for AI integration
Identify how generative AI alters traditional knowledge work functions and value
Assess the impact of AI on managerial responsibilities and workforce dynamics
Anticipate changes in company-customer relationships due to AI implementation
Analyze how AI shifts responsibility and autonomy within organizational structures
Develop comprehensive workplace policies to guide effective AI integration
Skills you'll gain
This course includes:
1.3 Hours PreRecorded video
1 assignment
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There are 3 modules in this course
This course explores the transformative effects of generative AI on labor markets and organizational structures. Structured in three comprehensive modules, the curriculum begins by examining workplace readiness for AI integration and forecasting broad impacts on jobs. The second module analyzes the evolving nature of knowledge work, evaluating how AI destabilizes traditionally "safe" white-collar positions. This section questions whether knowledge workers are replaceable and explores shifting responsibilities between workers and firms in an AI-integrated environment. The final module focuses on redefining key relationships affected by AI adoption—including worker-workplace dynamics and firm-consumer interactions. Students learn to analyze existing AI policies across various industries and develop their own workplace standards for ethical AI integration. Throughout the course, emphasis is placed on transparency, managing risks and benefits, and drawing lessons from historical technological disruptions. The practical curriculum culminates in students creating AI implementation policies tailored to their organizational needs.
Getting Started
Module 1 · 1 Hours to complete
Past & Future of Knowledge Work
Module 2 · 1 Hours to complete
Redefining Relationships
Module 3 · 2 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Navigating Disruption: Generative AI in the Workplace
Instructor
4 Courses
Leading Scholar in Political Communication and Public Opinion Research
Josh Pasek serves as Associate Professor of Communication & Media and Political Science at the University of Michigan, where he has established himself as an expert in political communication, public opinion, and survey methodology. His research focuses on how new media and psychological processes shape political attitudes and behaviors, as well as improving techniques for measuring public opinion. As a Faculty Associate in the Center for Political Studies and Core Faculty for the Michigan Institute for Data Science, he explores topics such as the impact of political information on public opinion, the changing political information environment due to social media, and methodological issues in survey research. His work has been published in top journals including Public Opinion Quarterly, Political Communication, and Communication Research. Pasek has developed two widely-used R packages for survey analysis: anesrake for producing survey weights and weights for analyzing weighted survey data. His academic journey includes a Ph.D. from Stanford University and previous positions at the University of Pennsylvania and University of Vienna before joining the University of Michigan in 2011.
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