Harnessing AI Adoption in the Workforce A Pathway to Sustainable Competitive Advantage through Intelligent Decision-Making and Skill Transformation

Md, Shokran and Md Saiful, Islam and Jannatul, Ferdousi (2025) Harnessing AI Adoption in the Workforce A Pathway to Sustainable Competitive Advantage through Intelligent Decision-Making and Skill Transformation. American Journal of Economics and Business Management, 8 (3). pp. 954-976. ISSN 2576-5973

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Abstract

Artificial intelligence (AI) is transforming the workplace by enhancing decision-making, improving efficiency, and developing employee skills. To fully benefit from AI, organizations must ensure their seamless integration into daily operations. This study explores how businesses can gain a sustainable competitive advantage by adopting AI in workforce development, focusing on decision-making improvements and skill transformation. By analyzing industry trends and case studies, the research identifies key factors that drive or hinder AI adoption among employees. Companies that invest in structured AI training programs experience higher productivity, better decision-making, and increased innovation. Additionally, organizations that embrace AI-driven workforce development can adapt more effectively to rapid market changes. The study highlights the role of leadership in fostering an AI-driven learning culture by emphasizing incentives and support systems for employee engagement. A well-planned AI strategy strengthens workforce capabilities, ensuring long-term business success and resilience in the digital economy. Organizations that proactively adopt AI and train employees in essential skills gain a competitive edge while safeguarding against digital challenges. Companies that leverage AI to enhance human talent, rather than replace jobs, will drive continuous innovation, sustainable growth, and lasting success.

Item Type:	Article
Subjects:	Q Science > Q Science (General)
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	07 Mar 2025 04:56
Last Modified:	07 Mar 2025 04:56
URI:	http://eprints.umsida.ac.id/id/eprint/15798

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