AI-Powered Quality Assurance and MIS Analytics: Building Resilient and Intelligent Digital Economies
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Abstract
Artificial intelligence (AI), predictive analytics, and management information systems (MIS) are all converging to remake U.S. companies into smart, adaptive ecosystems that can sustain economic resilience, cybersecurity, and software quality assurance (QA). This study synthesizes the empirical and conceptual findings of 20 peer-reviewed articles published between 2023 and 2025 to establish an integrated AI–MIS–QA Resilience Framework (AMQRF) that synthesizes automation, analytics, and governance in critical sectors such as IT, health, energy, and supply-chain infrastructure. The meta-synthesis reveals predictive QA with AI reduces software defect rates by 25–45%, MIS-based analytics increase operational visibility levels by 30–35%, and AI-driven cybersecurity models improve the accuracy of threat detection by up to 40%. All combined these flips enterprise resilience as an enterprise function of interconnected digital smartness and organizational learning. The study concludes by recommending a governance-aware architecture in which predictive QA, business analytics, and MIS co-evolve to facilitate sustainable competitiveness and national digital security.
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References
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