Objectives: This review article aims to examine the impact of artificial intelligence (AI) on workforce dynamics and its broader socio-economic implications across industries.
Theoretical Framework: The study is grounded in theories of technological change and labor market transformation, focusing on how AI adoption influences productivity, employment, and skills requirements.
Method: A systematic literature review was conducted using databases such as IEEE Xplore, Google Scholar, ACM Digital Library, ScienceDirect, and SpringerLink, covering the period 2015–2024. Keywords included “AI in workforce,” “Job replacement,” “Industry impacts of AI,” “Skills transformation,” “AI,” and “Employment.” Articles were selected following strict inclusion and exclusion criteria, and data were synthesized to identify industry-level impacts.
Results and Discussion: AI adoption has contributed to significant job displacement while simultaneously creating new employment opportunities and driving skills transformation. Its influence spans sectors such as manufacturing, healthcare, retail, finance, agriculture, and transportation, where it improves efficiency and productivity but also heightens concerns over job insecurity and income disparities.
Research Implications: The findings highlight the need for policymakers, educators, and industry leaders to implement strategies that support workforce reskilling, adaptability, and equitable access to technological benefits.
Originality/Value: This study provides a comprehensive, multi-sectoral review of AI’s influence on the future of work, offering insights into both its opportunities and challenges for sustainable workforce development.