Abstract: Managerial decision-making in complex, data-rich environments demand tools that go beyond reporting to deliver actionable intelligence. Traditional enterprise dashboards and analytics platforms are designed for data analysts, not operational managers, creating a persistent gap between insight and action. This paper introduces AI-MDE: AI-Based Micro Decision Engine for Managers, a compact, AI-powered decision support system engineered to translate raw operational data into context-aware recommendations in real time. Built with modern web technologies (React, Vite, Tailwind CSS) and powered by Google’s Gemini API, AI-MDE delivers predictive analytics, risk scoring, and scenario modelling through an intuitive manager-first interface. We present the system architecture, design principles, implementation, and evaluation, demonstrating its effectiveness, usability, and scalability for mid-level and senior managers across industries. In controlled evaluations, AI-MDE achieved 89% decision recommendation accuracy, a System Usability Scale score of 84.2, and average recommendation latency of 1.76 seconds, outperforming baseline statistical models by 18 percentage points.

Keywords: Micro Decision Engine, AI-Powered DSS, Managerial Analytics, Predictive Decision Support, Gemini API, Operations Intelligence, Real-Time Risk Scoring, Workforce Planning, Scenario Modelling.

Downloads: | DOI: 10.17148/IARJSET.2026.13355