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<p>Technological micro and small enterprises (MSEs) face growing pressure to adopt artificial intelligence (AI) to remain competitive while simultaneously meeting sustainability demands. However, many of these firms lack structured Strategic Human Talent Management (SHTM) systems capable of supporting effective AI adoption and sustainability-oriented practices. This study examines how SHTM, enhanced through AI, influences organizational sustainability (S) in technological MSEs in Lima, Peru, particularly in the telecommunications, systems development, and technical vocational education sectors. Using a PLS-SEM structural model, data were collected through a validated questionnaire applied to 277 employees. The results show that SHTM has a significant direct effect on AI adoption (β = 0.796; <i>p</i> &lt; 0.001; R2 = 63.4%) and on Sustainability (β = 0.800; <i>p</i> &lt; 0.001). AI also exerts a positive effect on Sustainability (β = 0.480; <i>p</i> &lt; 0.001) and partially mediates the relationship between SHTM and S (indirect effect = 0.382; VAF = 44.32%). The model integrates the Resource-Based View, Sociotechnical Systems Theory, and the Triple Bottom Line framework, confirming that human talent, when strategically managed and aligned with AI, is a key driver of sustainable organizational performance. The findings provide theoretical contributions to digital transformation and sustainability research and offer practical guidance for managers and policymakers promoting human-centered AI adoption in emerging economies.</p>

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AI-powered strategic human talent management to promote sustainability in technological MSEs in Lima, Peru

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月16日

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  • Francisco Javier Arias Montoya,
  • Hugo Alvarez Aranzamendi,
  • Cecilia Carmen Cabrera Galarza,
  • Mario Ever Minaya Flores,
  • Rocío Muñoz Camero,
  • Reiter Alonso Vilela Montenegro

摘要

Technological micro and small enterprises (MSEs) face growing pressure to adopt artificial intelligence (AI) to remain competitive while simultaneously meeting sustainability demands. However, many of these firms lack structured Strategic Human Talent Management (SHTM) systems capable of supporting effective AI adoption and sustainability-oriented practices. This study examines how SHTM, enhanced through AI, influences organizational sustainability (S) in technological MSEs in Lima, Peru, particularly in the telecommunications, systems development, and technical vocational education sectors. Using a PLS-SEM structural model, data were collected through a validated questionnaire applied to 277 employees. The results show that SHTM has a significant direct effect on AI adoption (β = 0.796; p < 0.001; R2 = 63.4%) and on Sustainability (β = 0.800; p < 0.001). AI also exerts a positive effect on Sustainability (β = 0.480; p < 0.001) and partially mediates the relationship between SHTM and S (indirect effect = 0.382; VAF = 44.32%). The model integrates the Resource-Based View, Sociotechnical Systems Theory, and the Triple Bottom Line framework, confirming that human talent, when strategically managed and aligned with AI, is a key driver of sustainable organizational performance. The findings provide theoretical contributions to digital transformation and sustainability research and offer practical guidance for managers and policymakers promoting human-centered AI adoption in emerging economies.