AGILE INTELLIGENCE IN MANAGERIAL DECISION-MAKING: A STRATEGIC MODEL FOR MITIGATING LATENCY, ENHANCING RESPONSIVENESS, AND STRENGTHENING ETHICAL GOVERNANCE

Abstract

Modern organizations operate in environments of uncertainty, complexity, and rapid change, where traditional decision-making approaches are increasingly insufficient. This study introduces the concept of Agile Intelligence in Managerial Decision-Making (AIMDM) as a strategic model that integrates real-time analytics, explainable artificial intelligence (XAI), and agile methodologies to enhance responsiveness, transparency, and ethical governance in organizational contexts. The proposed framework addresses key challenges such as decision-making latency, cognitive bias, information overload, and lack of accountability, which often hinder managerial effectiveness. By embedding human-in-the-loop oversight and ethical governance protocols, AIMDM ensures that decisions are not only rapid but also explainable, auditable, and compliant with organizational values.

A case study implementation in a mid-sized manufacturing firm demonstrated tangible benefits: a 65% reduction in decision turnaround time, a 14% increase in forecasting accuracy, an improvement in managerial satisfaction scores, and a significant reduction in cognitive load. Comparative benchmarking against conventional BI systems, standalone AI-DSS, and cognitive DSS models further validated AIMDM’s superior performance in balancing speed, accuracy, and ethical compliance. The study contributes to theory by linking agility, AI ethics, and managerial cognition in a unified framework, and to practice by providing a replicable model that organizations can adopt to navigate digital transformation with responsiveness, trust, and integrity.