Data-Driven Intelligence: Emerging Architectures for Scalable and Responsible AI Systems

Authors

  • A Singh University of North America Author

DOI:

https://doi.org/10.70445/gtst.2.2.2026.240-262

Keywords:

Data driven intelligence, Scalable AI architectures, Responsible AI, Machine learning, Deep learning

Abstract

This review examines information-driven intelligence and future AI designs with emphasis on scalability and responsible system design. It underlines the use of large-scale data, enhanced machine learning models, and distributed computing in the modern AI to achieve high performance in a variety of applications. Among the major ones are deep learning, federated and edge computing, data governance, explain ability, robustness, and ethical aspects. The paper also looks at real-life use in the field of healthcare, finance, smart cities, and autonomous systems with a particular emphasis on their effect on society. It addresses key challenges including bias, privacy, computational cost and security and open research directions towards constructing transparent, efficient and trustworthy AI systems.

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Published

2026-05-01

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Vol. 2 No. 2 (2026): Special Issue : Emerging Trends in Science and Technology

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Articles

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Copyright (c) 2026 A Singh (Author)

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