Role of AI in Business Analytics: Predictive Insights for Future Trends

In the current corporate environment, combining Artificial Intelligence (AI) using Cloud corporate Intelligence (CBI) is a revolutionary way to improve data visualisation and predictive analytics. This article examines how cloud-based solutions and AI technologies work together, emphasising how both have an effect on decision-making. The ability to make decisions is significantly enhanced by AI-driven systems, which provide precise real-time insights and predictive analytics. In this article, we look at the many benefits of integrating AI with BI, including improved operational efficiency, personalised customer experiences, and predictive analytics accuracy. This capacity is particularly relevant in the fast-paced market climate of today, when a variety of elements, from social media trends to economic realities, are progressively influencing customer behaviour. The research looks at a number of AI methods, including deep learning, machine learning, and natural language processing, emphasising how they might improve prediction accuracy. For example, complicated and large-scale data may be processed by machine learning algorithms to estimate customer demand and find hidden relationships. Analysis of written content from reviews, social media, and other sources is made possible by natural language processing, which offers a better comprehension of customer sentiment and new trends. With the help of sophisticated neural networks, deep learning models are able to identify complex patterns in data and further improve predictions. Businesses have several challenges, including the requirement for specialised knowledge in data science and artificial intelligence, privacy issues, and data quality and integration. The research highlights how crucial it is to deal with these issues in order to properly use AI's promise in predictive analytics. To sum up, AI-powered predictive analytics provides revolutionary tools for identifying and predicting market trends. It helps companies to remain ahead of their competitors and successfully meet changing market needs by offering accurate and useful insights about customer behaviour. In order to improve the precision and usefulness of AI-driven analytics for prediction in a variety of market situations, the study emphasises the need for ongoing research and development.

Authors

Publication Details

Journal
International Journal of Computer Science and Mobile Computing
Published
2025-03-11
DOI
https://doi.org/10.47760/ijcsmc.2025.v14i03.001
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
Controls
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article

Role of AI in Business Analytics: Predictive Insights for Future Trends

N V Rama Sai Chalapathi Gupta Lakkimsetty
1 citations
International Journal of Computer Science and Mobile Computing
Big Data and Business Intelligence
2.28
article

Role of AI in Business Analytics: Predictive Insights for Future Trends

N V Rama Sai Chalapathi Gupta Lakkimsetty
article en
1 citations

Abstract

In the current corporate environment, combining Artificial Intelligence (AI) using Cloud corporate Intelligence (CBI) is a revolutionary way to improve data visualisation and predictive analytics. This article examines how cloud-based solutions and AI technologies work together, emphasising how both have an effect on decision-making. The ability to make decisions is significantly enhanced by AI-driven systems, which provide precise real-time insights and predictive analytics. In this article, we look at the many benefits of integrating AI with BI, including improved operational efficiency, personalised customer experiences, and predictive analytics accuracy. This capacity is particularly relevant in the fast-paced market climate of today, when a variety of elements, from social media trends to economic realities, are progressively influencing customer behaviour. The research looks at a number of AI methods, including deep learning, machine learning, and natural language processing, emphasising how they might improve prediction accuracy. For example, complicated and large-scale data may be processed by machine learning algorithms to estimate customer demand and find hidden relationships. Analysis of written content from reviews, social media, and other sources is made possible by natural language processing, which offers a better comprehension of customer sentiment and new trends. With the help of sophisticated neural networks, deep learning models are able to identify complex patterns in data and further improve predictions. Businesses have several challenges, including the requirement for specialised knowledge in data science and artificial intelligence, privacy issues, and data quality and integration. The research highlights how crucial it is to deal with these issues in order to properly use AI's promise in predictive analytics. To sum up, AI-powered predictive analytics provides revolutionary tools for identifying and predicting market trends. It helps companies to remain ahead of their competitors and successfully meet changing market needs by offering accurate and useful insights about customer behaviour. In order to improve the precision and usefulness of AI-driven analytics for prediction in a variety of market situations, the study emphasises the need for ongoing research and development.

International Journal of Computer Science and Mobile ComputingVol. 14(3)
Openalex Percentile: Top 14%
Big Data and Business Intelligence
2.28
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