Leveraging Artificial Intelligence for Business Analytics: A Data-Science based Decision Support System Framework

Artificial Intelligence (AI) transforms business intelligence (BI) by enhancing decision-making speed, accuracy, and depth in today’s data-driven landscape. Traditional Decision Support Systems (DSS), once foundational to BI, struggle to handle modern data's complexity, scale, and diversity, often resulting in limited decision-making agility. Integrating AI into DSS has become essential to bridge this gap, enabling these systems to process vast datasets in real-time and make predictive, data-informed recommendations. This study presents an AI-powered DSS framework designed to address the limitations of conventional DSS by incorporating machine learning, natural language processing, and adaptive feedback mechanisms. Through real-world simulations and industry-specific use cases, the framework demonstrates marked improvements in decision quality, response times, and user satisfaction compared to traditional systems. Findings suggest that AI-driven DSS can substantially enhance BI processes, equipping organizations with a proactive, scalable approach to decision support. By addressing key technical and ethical challenges, this research offers valuable insights for businesses aiming to leverage AI to stay competitive in increasingly complex environments, positioning AI-powered DSS as critical to the future of BI.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-07
DOI
https://doi.org/10.5281/zenodo.14964501
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

Leveraging Artificial Intelligence for Business Analytics: A Data-Science based Decision Support System Framework

Zenodo (CERN European Organization for Nuclear Research)
Big Data and Business Intelligence
article

Leveraging Artificial Intelligence for Business Analytics: A Data-Science based Decision Support System Framework

article en

Abstract

Artificial Intelligence (AI) transforms business intelligence (BI) by enhancing decision-making speed, accuracy, and depth in today’s data-driven landscape. Traditional Decision Support Systems (DSS), once foundational to BI, struggle to handle modern data's complexity, scale, and diversity, often resulting in limited decision-making agility. Integrating AI into DSS has become essential to bridge this gap, enabling these systems to process vast datasets in real-time and make predictive, data-informed recommendations. This study presents an AI-powered DSS framework designed to address the limitations of conventional DSS by incorporating machine learning, natural language processing, and adaptive feedback mechanisms. Through real-world simulations and industry-specific use cases, the framework demonstrates marked improvements in decision quality, response times, and user satisfaction compared to traditional systems. Findings suggest that AI-driven DSS can substantially enhance BI processes, equipping organizations with a proactive, scalable approach to decision support. By addressing key technical and ethical challenges, this research offers valuable insights for businesses aiming to leverage AI to stay competitive in increasingly complex environments, positioning AI-powered DSS as critical to the future of BI.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 41%
Big Data and Business Intelligence
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Leveraging Artificial Intelligence for Business Analytics: A Data-Science based Decision Support System Framework · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS