Title: Application-based integration of artificial intelligence and block chain through bibliometric-content analysis

Authors: Diwakar Chaudhary; Mohit; Sapna Sugandha; Khadilkar Sujay Madhukar; Shubhash Kumar Verma; Rashi Baliyan

Addresses: GLA University, Mathura, Uttar Pradesh, India ' Institute of Management Studies and Research, Maharshi Dayanand University, Rohtak, India ' Mahatma Gandhi Central University, Motihari, India ' Kolhapur Institute of Technology, Gokul Shirgaon, India ' Noida International University, Noida, India ' Noida International University, Noida, India

Abstract: Industry 4.0 (IR 4.0) is accelerating digital transformation, with rapid advancements in artificial intelligence (AI) and blockchain technologies fostering their convergence. Although prior studies have examined the adoption and technical integration of AI and blockchain, there remains limited consensus regarding the concrete business benefits arising from their combined application. Addressing this gap, the present study investigates the applications and advantages of blockchain-integrated AI systems across diverse business sectors. Using bibliometric analysis, the study systematically examines existing literature to identify influential publications, citation patterns, and key intellectual structures shaping this research domain. The analysis highlights dominant themes, emerging research characteristics, and underexplored areas within the intersection of AI, blockchain, and business. The findings demonstrate that AI-blockchain integration represents a significant and growing global phenomenon with substantial potential to enhance transparency, efficiency, and decision-making in business operations. The study underscores the need for further empirical research to address unresolved issues and guide future investigations in this evolving field.

Keywords: artificial intelligence; block chain; Industrial Revolution 4.0.

DOI: 10.1504/IJAISC.2026.153148

International Journal of Artificial Intelligence and Soft Computing, 2026 Vol.10 No.1, pp.71 - 89

Received: 19 Jun 2024
Accepted: 27 Jun 2025
Published online: 23 Apr 2026 *

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