Application of Generative Artificial Intelligence in Business Analytics: Innovations and Challenges

Generative Artificial Intelligence (GAI) is increasingly being used in the field of business analytics (BA) and has important research significance. The main question of this study is to explore how GAI can improve the efficiency of BA and solve existing problems. Through literature review and case analysis, this paper deeply explores the application of GAI in predictive analysis, sentiment analysis and customized services, as well as its actual cases in real estate search and enterprise operations. The main conclusion is that GAI can significantly improve the efficiency and effectiveness of BA through efficient data processing and analysis, personalized services and operational optimization. However, GAI also faces challenges such as data accuracy, copyright infringement and complexity of the generation process, which need to be addressed by enhancing content accuracy and transparency and strengthening data security measures. This paper recommends the formulation of relevant regulations to ensure the ethical use of GAI and promote the continuous improvement of technology to achieve the best application of GAI in BA.

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Publication Details

Journal
Advances in Economics Management and Political Sciences
Published
2024-10-12
DOI
https://doi.org/10.54254/2754-1169/99/2024ox0206
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Application of Generative Artificial Intelligence in Business Analytics: Innovations and Challenges

Ying Zhou
Advances in Economics Management and Political Sciences
Big Data and Business Intelligence
article

Application of Generative Artificial Intelligence in Business Analytics: Innovations and Challenges

Ying Zhou
article en

Abstract

Generative Artificial Intelligence (GAI) is increasingly being used in the field of business analytics (BA) and has important research significance. The main question of this study is to explore how GAI can improve the efficiency of BA and solve existing problems. Through literature review and case analysis, this paper deeply explores the application of GAI in predictive analysis, sentiment analysis and customized services, as well as its actual cases in real estate search and enterprise operations. The main conclusion is that GAI can significantly improve the efficiency and effectiveness of BA through efficient data processing and analysis, personalized services and operational optimization. However, GAI also faces challenges such as data accuracy, copyright infringement and complexity of the generation process, which need to be addressed by enhancing content accuracy and transparency and strengthening data security measures. This paper recommends the formulation of relevant regulations to ensure the ethical use of GAI and promote the continuous improvement of technology to achieve the best application of GAI in BA.

Advances in Economics Management and Political SciencesVol. 99(1)
The University of Western Australia (AU)
Openalex Percentile: Top 72%
Big Data and Business Intelligence
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