Big Data and Artificial Intelligence: Implications and Strategies for Business Development in Indonesia

The rapid development of digital technology has significantly influenced business growth in Indonesia. Big Data and Artificial Intelligence (AI) have emerged as crucial tools in optimizing decision-making, improving operational efficiency, and enhancing business competitiveness. This study aims to conduct a Systematic Literature Review (SLR) to analyze the utilization of Big Data and AI in business development in Indonesia. The research identifies key benefits, challenges, and strategies for technology adoption. The findings highlight that Big Data enables businesses to extract valuable insights from vast datasets, while AI facilitates automation and predictive analytics to enhance marketing strategies, customer experience, and supply chain efficiency. However, several challenges hinder widespread adoption, including limited digital infrastructure, a shortage of skilled professionals, high investment costs, and regulatory concerns regarding data security and privacy. The study suggests that strengthening digital literacy, improving technological infrastructure, and fostering collaboration between government, academia, and industry are critical to accelerating the adoption of these technologies. By leveraging Big Data and AI effectively, businesses in Indonesia can enhance their competitive advantage and drive sustainable economic growth in the digital era.

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Publication Details

Journal
Journal of Marketing Management and Innovative Business Review
Published
2025-03-20
DOI
https://doi.org/10.63416/mrb.v3i1.321
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Big Data and Artificial Intelligence: Implications and Strategies for Business Development in Indonesia

Maria Yessica Halik, Hugo Sahetapy, Hendi William Sino, Joe Roland Setiyawan Bokau
Journal of Marketing Management and Innovative Business Review
Data Mining and Machine Learning Applications
article

Big Data and Artificial Intelligence: Implications and Strategies for Business Development in Indonesia

Maria Yessica Halik, Hugo Sahetapy, Hendi William Sino, Joe Roland Setiyawan Bokau
article en

Abstract

The rapid development of digital technology has significantly influenced business growth in Indonesia. Big Data and Artificial Intelligence (AI) have emerged as crucial tools in optimizing decision-making, improving operational efficiency, and enhancing business competitiveness. This study aims to conduct a Systematic Literature Review (SLR) to analyze the utilization of Big Data and AI in business development in Indonesia. The research identifies key benefits, challenges, and strategies for technology adoption. The findings highlight that Big Data enables businesses to extract valuable insights from vast datasets, while AI facilitates automation and predictive analytics to enhance marketing strategies, customer experience, and supply chain efficiency. However, several challenges hinder widespread adoption, including limited digital infrastructure, a shortage of skilled professionals, high investment costs, and regulatory concerns regarding data security and privacy. The study suggests that strengthening digital literacy, improving technological infrastructure, and fostering collaboration between government, academia, and industry are critical to accelerating the adoption of these technologies. By leveraging Big Data and AI effectively, businesses in Indonesia can enhance their competitive advantage and drive sustainable economic growth in the digital era.

Journal of Marketing Management and Innovative Business ReviewVol. 3(1)
Universitas Kristen Indonesia (ID), Handan College (CN), Australian National University (AU)
Openalex Percentile: Top 90%
Data Mining and Machine Learning Applications
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Big Data and Artificial Intelligence: Implications and Strategies for Business Development in Indonesia — Maria Yessica Halik, Hugo Sahetapy, et al. · Journal of Marketing Management and Innovative Business Review (2025) | TGRS Research Map | TGRS