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Workforce 5.0 Adoption in Intelligent Enterprises: A Case Study of AI-Driven Reskilling and Agile Workforce Development
Published Online: July-August 2026
Pages: 232-238
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↗ https://www.doi.org/10.59256/ijrtmr.20260604027Abstract
Background: The emergence of Workforce 5.0 has transformed traditional organizational structures by integrating human expertise with artificial intelligence (AI) capabilities. Intelligent enterprises are increasingly adopting Human–AI collaboration models to enhance workforce productivity, accelerate reskilling initiatives, and improve organizational agility in rapidly changing business environments. Case Description: This case study examines the implementation of a Human–AI collaboration framework within an intelligent enterprise undergoing digital transformation. The organization introduced AI-powered learning platforms, intelligent decision-support systems, and automated workflow tools to support employee reskilling and operational adaptability. Data were collected through organizational reports, employee feedback, and performance indicators to assess the effectiveness of the initiative. Key Findings: The findings indicate that Human–AI collaboration significantly improved employee learning outcomes, reduced skill gaps, enhanced decision-making efficiency, and increased workforce adaptability. AI-driven personalized learning pathways accelerated reskilling efforts, while intelligent automation enabled employees to focus on higher-value tasks. The organization also demonstrated improved responsiveness to market changes and greater operational flexibility. Conclusion: The case highlights the strategic role of Human–AI collaboration in developing a future-ready workforce. Workforce 5.0 models can foster continuous learning, strengthen organizational resilience, and support sustainable competitive advantage. The study provides practical insights for organizations seeking to leverage AI technologies for workforce transformation and organizational agility in the era of intelligent enterprises.
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