Artificial Intelligence and Data-Driven Innovation: A Comprehensive Multidisciplinary Review of Machine Learning, Big Data Analytics, Healthcare, Industry, Business, and Intelligent Decision-Making

Advanced analytics, predictive modelling and intelligent decision making are reshaping a wide range of industries with the help of artificial intelligence (AI) and data innovation. This review compares the applications of machine learning, deep learning and big data analytics in healthcare, business, manufacturing, agriculture, smart-cities and public governance. It delves into their role in enhancing operational efficiency, predictive intelligence, resource optimization, and quality management. Key challenges that are included in the discussion are data privacy, algorithmic bias, cybersecurity, scalability, and model interpretability. In addition, new developments like federated learning, edge computing, and generative AI are taken into account. The proper application and good governance of technologies is still necessary for sustainable technological development.

Authors

Publication Details

Journal
Global Trends in Science and Technology
Published
2026-10-29
DOI
https://doi.org/10.70445/gtst.2.5.2026.40-68
Primary Topic
Artificial Intelligence Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence and Data-Driven Innovation: A Comprehensive Multidisciplinary Review of Machine Learning, Big Data Analytics, Healthcare, Industry, Business, and Intelligent Decision-Making

Mohammad Ali, George Edison, Alaxendra Harry
Global Trends in Science and Technology
Artificial Intelligence Applications
article

Artificial Intelligence and Data-Driven Innovation: A Comprehensive Multidisciplinary Review of Machine Learning, Big Data Analytics, Healthcare, Industry, Business, and Intelligent Decision-Making

Mohammad Ali, George Edison, Alaxendra Harry
article en

Abstract

Advanced analytics, predictive modelling and intelligent decision making are reshaping a wide range of industries with the help of artificial intelligence (AI) and data innovation. This review compares the applications of machine learning, deep learning and big data analytics in healthcare, business, manufacturing, agriculture, smart-cities and public governance. It delves into their role in enhancing operational efficiency, predictive intelligence, resource optimization, and quality management. Key challenges that are included in the discussion are data privacy, algorithmic bias, cybersecurity, scalability, and model interpretability. In addition, new developments like federated learning, edge computing, and generative AI are taken into account. The proper application and good governance of technologies is still necessary for sustainable technological development.

Global Trends in Science and TechnologyVol. 2(5)
Openalex Percentile: Top 13%
Artificial Intelligence Applications
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