Business intelligence systems integrating artificial intelligence, big data analytics, machine learning, internet of things, and blockchain
Abstract
The rise of digital transformation has posed challenges on organizations like never before due to the exponential growth, which has created the need to have a competitive edge that is obtained through using data in decision-making. The conventional business intelligence solutions have problems in managing the enormous amount, speed, and diversity of data produced by business organizations today leading to the provision of delayed insights and loss of opportunities. This literature review provides an analysis of the intersection of Artificial Intelligence, Big Data Analytics, Machine Learning, Internet of Things, and Blockchain technologies in transforming the business intelligence systems. The presented research applies a systematic review based on the PRISMA methodology in order to explore the opportunity of these new technologies to work together in order to enhance predictive analytics, automate business processes, guarantee information integrity, and generate business value never experienced before. Exploring a wide range of implementation applications in optimization of supply chains, customer experience improvement, fraud detection, and strategic planning, the review evaluates the implementation structures, technical architecture models and algorithm types. Among the core conclusions, it is possible to note that integrated AI-ML-Big Data environments will provide better predictive quality, IoT allows acquiring real-time operational intelligence, and Blockchain guarantees data provenance and trust. Nevertheless, there remain serious challenges such as quality of data, complexities of integrating the data, skills gap, ethical considerations and regulation compliance.
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Copyright (c) 2026 Nitin Liladhar Rane, Obizue Emmanuel Chika , Jayesh Rane (Author)
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Copyright (c) 2025 International Journal of Applied Resilience and Sustainability (IJARS) 
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