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Artificial Intelligence and Workforce Transformation: An Analysis of Employment Disruption and Adaptation Strategies

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  • Arthur Bernard Henry

    (Takoradi Technical University)

  • Dr. Richard Essah

    (Takoradi Technical University)

Abstract

This research examines the transformative effects of artificial intelligence technologies on contemporary employment structures through both systematic literature analysis and empirical data collection. Using a mixed-methods approach combining bibliometric analysis (n=847 papers), survey data from 2,350 workers across 15 industries, and longitudinal employment statistics from 12 countries (2019-2024), this study quantifies AI's impact on global labor markets. Statistical analysis reveals that routine-intensive occupations face a 67% higher displacement risk (p<0.001) compared to creative and interpersonal roles. Industry-specific regression models demonstrate manufacturing (β=-0.43, CI: -0.52 to -0.34) and administrative services (β=-0.38, CI: -0.47 to -0.29) show significant negative employment correlations with AI adoption rates. Conversely, healthcare (β=0.29, CI: 0.21 to 0.37) and education (β=0.22, CI: 0.15 to 0.29) sectors demonstrate positive employment growth correlations. The study provides quantified evidence for 2.3 million net job creation potential by 2030, with 78% confidence intervals, while identifying critical skill gaps affecting 34% of current workforce positions.

Suggested Citation

  • Arthur Bernard Henry & Dr. Richard Essah, 2025. "Artificial Intelligence and Workforce Transformation: An Analysis of Employment Disruption and Adaptation Strategies," International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 14(8), pages 493-501, August.
    • Handle: RePEc:bjf:ijltem:v:14:y:2025:i:8:a:1635
    DOI: 10.51583/IJLTEMAS.2025.1408000059
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