AI-Driven Predictive Analytics

AI-driven predictive analytics is essential for attaining business excellence in fluctuating markets, though there are gaps in combining ethics, governance, and Enterprise Architecture (EA). This chapter addresses the research questions: (1) How does predictive analytics enhance strategic decision-making and sustainability? (2) What ethical, cultural, and regulatory barriers hinder adoption? (3) How can organizations align analytics with EA for future-ready excellence? Employing a conceptual synthesis of literature and case studies, we review theoretical foundations, applications, challenges, and trends. Key findings show advantages including increased efficiency and ESG alignment tempered against hazards including integration failures and bias. Contributions include a conceptual model connecting analytics to dynamic capabilities and RBV, regulatory frameworks (e.g., NIST, OECD), and a practical roadmap with human-in-the-loop (HITL) tactics. theory helps managers to promote resilient, ethical AI adoption.