Planning for Generative AI’s Impact on Jobs

Three-fourths of HR leaders agree they will be lagging in organizational success if they do not adopt and implement generative AI (GenAI) in the next 12 to 24 months. However, GenAI’s long-term impact on jobs is yet to be determined, and as a result, organizations must prepare for multiple scenarios as they engage in workforce planning and adopt GenAI to their unique context.

In this episode of the Talent Angle, Helen Poitevin, a distinguished vice president analyst at Gartner, shares a framework to help organizations evaluate the context-specific workforce impact of GenAI by identifying the market and technology drivers that matter for talent decisions. This Gartner model will help HR leaders establish workforce strategies as they align technology and business investments with talent implications.

Helen Poitevin is a distinguished VP analyst with a focus on human capital management (HCM) technologies and advising clients on their HCM technology strategies. In HCM, areas of particular focus include talent analytics, voice of the employee analytics, workforce planning and AI in HCM. Ms. Poitevin also conducts research regarding the future of work with a focus on technology’s effect on how people will work, the gig economy, talent marketplaces and ecosystems, and future talent practices.

Peter Aykens is the chief of research for Gartner’s HR practice. Mr. Aykens is responsible for building and leading research teams within the practice to address clients’ key initiatives. Before his current role, he spent over 25 years at Gartner leading research teams focused on banking and financial services strategy, producing numerous studies that addressed business strategy, channels, marketing, customer experience and product challenges. He holds a bachelor’s degree in political science from St. Olaf College, a master’s degree in international politics from Aberystwyth University (formerly known as the University College of Wales, Aberystwyth) and a master’s degree and a doctorate in political science from Brown University.