Organizational Workforce Management in the Digital Age: The Role of Technocultural Interventions in Mitigating the Negative Impacts of AI-Driven Technological Change

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Abstract
This study explores the impact of AI-driven technological change on workforce management, focusing on job displacement, employee satisfaction, and productivity. A mixed-method approach was employed, including logistic regression, K-means clustering, and multivariate regression analysis, to evaluate the effectiveness of technocultural interventions (upskilling programs, ethical AI frameworks, and innovation culture). Data was sourced from the U.S. Bureau of Labor Statistics (BLS) and survey questionnaires. Logistic regression revealed that routine AI adoption showed a weak positive relationship with job displacement (B = 0.013, p = 0.111), but the overall model was not statistically significant. The K-means clustering identified three distinct organizational patterns in adopting technocultural interventions. Multivariate regression highlighted the substantial role of leadership commitment in increasing employee satisfaction (B = -0.067, p = 0.039) but found limited direct effects of upskilling programs and AI frameworks on productivity. Based on the findings, the study highlights the importance of customized, sector-specific interventions and recommends that organizations integrate leadership and ethical considerations to manage AI-driven changes effectively.

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