Rivan Prasetya
Universitas Buana Perjuangan Karawang

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AI-ENABLED LEADERSHIP AGILITY: A SYSTEMATIC REVIEW INTEGRATING TALENT MANAGEMENT, GREEN FINANCE, AND SUSTAINABLE BUSINESS Wike Pertiwi; Budi Rismayadi; irwan Purwanto; Dandan Rolis Harnika; Rivan Prasetya
Journal Of Resource Management, Economics And Business Vol. 5 No. 2 (2026): Journal Of Resource Management, Economics And Business (REMICS)
Publisher : PT. Berkah Digital Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58468/remics.v5i2.283

Abstract

Purpose: This study examines the role of artificial intelligence (AI) in leadership agility and its integration with talent management, green-finance decision processes, and sustainable business outcomes. Research Methodology: This study uses a PRISMA 2020-aligned systematic literature review. Peer-reviewed English-language journal articles published from 2013 to the final search date in 2026 were identified through Scopus and Web of Science, screened using predefined eligibility criteria, appraised using design-appropriate quality criteria, and synthesized through thematic coding. Results: The synthesis identifies AI-enabled decision support as a potential enabler of leadership agility; talent intelligence as a workforce-adaptation capability; and AI-supported green-finance processes as mechanisms for ESG and climate-risk-informed decisions. Data quality, AI literacy, human oversight, governance, transparency, privacy protection, and credible ESG data emerge as key boundary conditions. Limitations: The review is limited to English-language peer-reviewed articles and provides thematic synthesis rather than meta-analytic causal estimates. Contribution: This study contributes to leadership, strategic management, human resource management, sustainable finance, and responsible-AI research by proposing an integrative framework linking AI infrastructure, leadership agility, talent intelligence, green-finance decisions, and multidimensional sustainable business outcomes.