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Building High-Performance Teams and Enhancing Staff Training Through AI-Driven Solutions in Financial Institutions and SMEs

Author

Listed:
  • Hope Ehiaghe Omokhoa

    (Department of Business Studies, The University of the Potomac, Virginia, USA)

  • Chinekwu Somtochukwu Odionu

    (Independent Researcher, Texas, USA)

  • Chima Azubuike

    (Guaranty Trust Bank (Nigeria) Limited)

  • Aumbur Kwaghter Sule

    (Independent Researcher, Abuja, Nigeria)

Abstract

This paper explores the transformative potential of AI-driven solutions in building high-performance teams and enhancing staff training within financial institutions and SMEs. High-performance teams are characterized by collaboration, trust, and shared goals, and AI technologies are increasingly pivotal in improving these dynamics through enhanced communication, decision-making, and productivity. Traditional staff training approaches are changing significantly with AI-powered personalized learning, performance analytics, and continuous development tools, fostering better knowledge retention and skill acquisition. However, the adoption of AI presents challenges, including high implementation costs, technical expertise gaps, ethical concerns such as data privacy and biases, and resistance to change. This paper emphasizes strategic solutions to address these challenges, recommending scalable AI adoption, transparent practices, enhanced digital literacy, and robust performance monitoring. Financial institutions and SMEs can unlock significant competitive advantages by aligning AI implementation with organizational objectives, driving growth and innovation in an increasingly technology-driven landscape.

Suggested Citation

  • Hope Ehiaghe Omokhoa & Chinekwu Somtochukwu Odionu & Chima Azubuike & Aumbur Kwaghter Sule, 2024. "Building High-Performance Teams and Enhancing Staff Training Through AI-Driven Solutions in Financial Institutions and SMEs," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(12), pages 2976-2984, December.
    • Handle: RePEc:bcp:journl:v:8:y:2024:i:12:p:2976-2984
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    References listed on IDEAS

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    1. Günter K Stahl & Martha L Maznevski, 2021. "Unraveling the effects of cultural diversity in teams: A retrospective of research on multicultural work groups and an agenda for future research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 52(1), pages 4-22, February.
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