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AI-Powered Decision Intelligence in Enterprise Systems Engineering: A Framework for Next-Generation Business Operations

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  • Praveen Kumar Guguloth

    (State University of New York at Binghamton, USA)

Abstract

The integration of AI-powered decision intelligence systems in enterprise environments represents a transformative shift in business operations and strategic planning. This advancement addresses the limitations of traditional decision-making frameworks by introducing sophisticated machine learning algorithms, knowledge graphs, and cognitive automation capabilities. The framework encompasses comprehensive data integration, analytical processing, and decision execution layers, enabling organizations to process vast amounts of structured and unstructured data while maintaining human oversight for critical operations. Through systematic implementation strategies, enterprises across financial services, manufacturing, and IT sectors have achieved substantial improvements in operational efficiency, risk management, and customer satisfaction. The incorporation of AI-driven systems has revolutionized fraud detection, supply chain optimization, and incident resolution processes while significantly reducing human error rates and operational costs. This technological evolution demonstrates the potential of AI-powered decision intelligence to enhance enterprise performance through improved prediction accuracy, reduced decision latency, and optimized resource allocation.

Suggested Citation

  • Praveen Kumar Guguloth, 2025. "AI-Powered Decision Intelligence in Enterprise Systems Engineering: A Framework for Next-Generation Business Operations," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(3), pages 677-682, April.
    • Handle: RePEc:alk:jcsts0:v:7:y:2025:i:3:id:9423
    DOI: 10.32996/jcsts.2025.7.3.77
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