Revolutionizing Information Management: AI-Driven Decision Support Systems for Dynamic Business Environments

The need of more sophisticated decision making tools in modern businesses is largely influenced by the pace and intricacy of new business markets. The use of Artificial Intelligence (AI) is transforming Decision Support Systems (DSS), inforamtion technology, and maagement strategies. This paper seeks to analyze how AI technology is changing the business decision making processes with and emphasis on its use in DSS. The application of AI, machine learning (ML), natural language processing (NLP), and predictive analysis have radically transformed the efficiency and effectiveness of decision making processes. These changes enable timely and accurate relavant decisions which improves overall efficiency and responsiveness to market dynamics. AI empowered DSS are more valuable in retail, manufactury, and finance industries where complex decisions are accompanied by time sensitive data. AI application in these fields not only enhanced the decision making accuracy, but also greatly minimized adverse human factors, dwindling resources, and time wastage. This research was carried out using a mixed-method approach of qualitative and quantitative techniques. The qualitative case study method consists of multi-industry studies which have implemented AI based DSS systems, aiding in understanding the processes, complications, and results of such systems. Moreover, additional data was collected through Industry expert and decision-maker surveys and interviews to evaluate the effects of AI on business functions and processes. The work furthers comprehension regarding the influence of AI automation on DSS integration by explaining the value added from more accurate, scalable, and responsive decision-making from AI technologies. Automated decision systems of AI driven DSS do not only facilitate decisions but also forecast critical insights to help organizations strategically plan, avert threats, and succeed. This underscores what is increasingly becoming a central concern in business strategy and policy formulation - the application of AI in operational and strategic decision-making processes of firms.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-04-11
DOI
https://doi.org/10.52783/jisem.v10i35s.6010
Citations
5
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
11.42
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article

Revolutionizing Information Management: AI-Driven Decision Support Systems for Dynamic Business Environments

Anjani kumar Polinati
5 citations
Journal of Information Systems Engineering & Management
Big Data and Business Intelligence
11.42
article

Revolutionizing Information Management: AI-Driven Decision Support Systems for Dynamic Business Environments

Anjani kumar Polinati
article en
5 citations

Abstract

The need of more sophisticated decision making tools in modern businesses is largely influenced by the pace and intricacy of new business markets. The use of Artificial Intelligence (AI) is transforming Decision Support Systems (DSS), inforamtion technology, and maagement strategies. This paper seeks to analyze how AI technology is changing the business decision making processes with and emphasis on its use in DSS. The application of AI, machine learning (ML), natural language processing (NLP), and predictive analysis have radically transformed the efficiency and effectiveness of decision making processes. These changes enable timely and accurate relavant decisions which improves overall efficiency and responsiveness to market dynamics. AI empowered DSS are more valuable in retail, manufactury, and finance industries where complex decisions are accompanied by time sensitive data. AI application in these fields not only enhanced the decision making accuracy, but also greatly minimized adverse human factors, dwindling resources, and time wastage. This research was carried out using a mixed-method approach of qualitative and quantitative techniques. The qualitative case study method consists of multi-industry studies which have implemented AI based DSS systems, aiding in understanding the processes, complications, and results of such systems. Moreover, additional data was collected through Industry expert and decision-maker surveys and interviews to evaluate the effects of AI on business functions and processes. The work furthers comprehension regarding the influence of AI automation on DSS integration by explaining the value added from more accurate, scalable, and responsive decision-making from AI technologies. Automated decision systems of AI driven DSS do not only facilitate decisions but also forecast critical insights to help organizations strategically plan, avert threats, and succeed. This underscores what is increasingly becoming a central concern in business strategy and policy formulation - the application of AI in operational and strategic decision-making processes of firms.

Journal of Information Systems Engineering & ManagementVol. 10(35s)
Openalex Percentile: Top 2%
Big Data and Business Intelligence
11.42
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