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

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.

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Publication Details

Journal
Journal of Computer Science and Technology Studies
Published
2025-05-08
DOI
https://doi.org/10.32996/jcsts.2025.7.3.77
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

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

Praveen Kumar Guguloth
1 citations
Journal of Computer Science and Technology Studies
Big Data and Business Intelligence
2.28
article

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

Praveen Kumar Guguloth
article en
1 citations

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.

Journal of Computer Science and Technology StudiesVol. 7(3)
Binghamton University (US)
Openalex Percentile: Top 12%
Big Data and Business Intelligence
2.28
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