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Restructuring Entry-Level Employment in the AI Era: Beyond Traditional Apprenticeship Models, by Jonathan H. Westover PhD

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Manage episode 508094597 series 3593224
Content provided by HCI Podcast Network. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HCI Podcast Network or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Abstract: The integration of artificial intelligence into professional work environments is rapidly transforming entry-level employment, challenging traditional pathways into knowledge work. This article examines the limitations of conventional apprenticeship approaches in an AI-accelerated economy and proposes evidence-based alternatives for Chief Human Resources Officers (CHROs) and talent leaders. Drawing from research in organizational psychology, labor economics, and human capital development, it presents a framework for sustainable talent development that acknowledges both market realities and long-term workforce needs. The analysis reveals that while protecting entry-level positions solely for societal benefit is economically unsustainable, strategic redesign of junior roles with emphasis on AI-complementary skills can create genuine business value. Organizations that develop systematic approaches to developing AI-native talent may secure significant competitive advantages as the experienced talent pipeline contracts over the next decade.

  continue reading

101 episodes

Artwork
iconShare
 
Manage episode 508094597 series 3593224
Content provided by HCI Podcast Network. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HCI Podcast Network or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Abstract: The integration of artificial intelligence into professional work environments is rapidly transforming entry-level employment, challenging traditional pathways into knowledge work. This article examines the limitations of conventional apprenticeship approaches in an AI-accelerated economy and proposes evidence-based alternatives for Chief Human Resources Officers (CHROs) and talent leaders. Drawing from research in organizational psychology, labor economics, and human capital development, it presents a framework for sustainable talent development that acknowledges both market realities and long-term workforce needs. The analysis reveals that while protecting entry-level positions solely for societal benefit is economically unsustainable, strategic redesign of junior roles with emphasis on AI-complementary skills can create genuine business value. Organizations that develop systematic approaches to developing AI-native talent may secure significant competitive advantages as the experienced talent pipeline contracts over the next decade.

  continue reading

101 episodes

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