Artificial Intelligence and Business Sustainability: Data-Driven Approaches for Resilient Organizations

Organizations worldwide struggle to translate AI ambition into measurable sustainability outcomes — this volume provides the evidence and frameworks to close that gap. Thirty-six chapters across seven thematic parts connect AI and data-driven methods directly to organizational performance: banking stability, investment efficiency, insurance service quality, logistics optimization, and cybersecurity governance. The approach is distinctive in integrating empirical research with dedicated governance and ethics chapters — responsible AI, environmental footprint, and circular-economy systems — within a single coherent framework. Geographic and sectoral breadth is a further differentiator: contributors draw on evidence from Jordan, Oman, the Gulf, Malaysia, Iraq, and Lebanon, spanning banking, insurance, public administration, engineering, and water utilities. Doctoral students and researchers gain replicable methodologies; executives and policymakers gain practical benchmarks for AI adoption decisions.