Sam Burt, a Gartner senior director of research, dives into the evolving role of generative AI in supply chains. The conversation highlights how AI impacts productivity differently for desk-based versus frontline workers, exploring both time savings and potential job reductions. Burt discusses the 'productivity paradox' and how leaders can strategically invest in AI tools. Recommendations for chief supply chain officers aim at maximizing team creativity through collaborative approaches, ensuring that innovation and employee experience are prioritized.
Generative AI is expected to lead to significant headcount reductions in supply chain organizations, raising concerns about job stability and workforce structure.
The impact of GenAI on productivity varies between desk-based and frontline roles, with notable gains for desk positions but limited benefits for team dynamics.
Deep dives
Impact of Gen.AI on Headcount Reduction
Gen.AI is significantly influencing strategic decisions in supply chain organizations, particularly regarding headcount reductions. A survey revealed that 81% of supply chain leaders anticipate a reduction in their workforce due to the implementation of Gen.AI, with an expected decrease of around 8.3%. This anticipated shift raises concerns about the implications for job stability and the overall workforce structure within the supply chain sector. While new technologies often lead to efficiency and job transformation, the expectation of large-scale layoffs may result in premature job cuts, potentially harming the organizations in the long run.
Defining and Measuring Productivity
The research uncovers various interpretations of productivity among supply chain leaders, with a consistent definition focused on the ratio of inputs to outputs. Findings indicate that Gen.AI tools have positively impacted desk-based roles, resulting in an average time savings of 4.1 hours, increased work output by 71%, and improved quality by 63%. However, these productivity gains do not correlate at the team level or for frontline roles, where results are significantly lower. This inconsistency highlights a risk of misaligned expectations regarding Gen.AI's benefits across different functions within supply chains.
Successful Gen.AI Implementation Strategies
Effective Gen.AI implementations focus on enhancing productivity for both frontline and desk-based roles while simultaneously addressing employee anxiety. Organizations can improve outcomes by adopting a strategy that aligns with organizational productivity, fostering creativity and strategic thinking among teams. A noteworthy example is Micron, which instituted 'Innovatathons' to encourage team-driven pilot projects, promoting engagement and successful adaptations of Gen.AI. Such approaches not only drive positive results but also enhance the overall employee experience, helping to mitigate potential anxiety associated with technological changes.
Generative AI’s expected impacts on headcount when GenAI exploded into mainstream news in 2022 (1:32).
How GenAI’s impacts on productivity and time savings vary between desk-based and frontline employees (4:54).
Measuring whether GenAI “lived up to the hype” in light of research results (11:31).
What leaders are doing to resolve GenAI’s “productivity paradox” (12:38).
Recommendations for CSCOs driving GenAI projects (15:24).
In this episode of the Supply Chain Podcast, host Tess Frenzel and guest Sam Berndt, a Gartner senior director of research, discuss generative AI’s (GenAI’s) variable impacts on supply chain employee productivity in both desk-based and frontline roles.
Tess and Sam frame the discussion with findings from Gartner’s Supply Chain Executive Report: The GenAI Productivity Paradox to provide details on key differentiators like individual- and team-based time savings, work quality improvements and employee comfort levels.
About the Guest
Sam Berndt is a Gartner Senior Research Director leading long-form studies on chief supply chain officers and their key priorities. He has led studies on risk and supplier due diligence, talent and skill gap myths, last-mile delivery customer preferences, and the impact of generative AI on supply chain employee productivity. Before Gartner, Sam studied the economic impacts of large regulations.
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