Evaluation of Artificial Intelligence–Blockchain Technology Integration in the Industry 4.0 Era: Systematic Literature Review

Authors

  • Aripin Sidabukke Universitas Mikroskil
  • Jonsen Wijaya Universitas Mikroskil
  • Agata Theodora Febriani Br. Tarigan Universitas Mikroskil
  • Vandika Pratama Universitas Mikroskil
  • Aldo Lotandes Universitas Mikroskil
  • Joosten Joosten Universitas Mikroskil

DOI:

https://doi.org/10.61722/jmia.v2i5.6882

Keywords:

Blockchain, Artificial Intelligence, Industry 4.0, Smart Manufacturing, Supply Chain

Abstract

This study aims to analyze the integration of Artificial Intelligence (AI) and Blockchain technology to optimize processes within the Industry 4.0 framework. The background of this research is the increasing demand for operational transparency, data security, and autonomous decision-making in modern manufacturing and supply chains. While Industry 4.0 generates massive data (Big Data), it faces challenges in data integrity and intelligent automation. The research method used is a Systematic Literature Review (SLR) with a qualitative approach, analyzing academic publications from 2020 to 2025. Data were collected from databases such as IEEE Xplore, Scopus, and ScienceDirect, focusing on integration architecture and use cases. The results show that AI integration (specifically machine learning) on the Blockchain enables decentralized predictive maintenance, autonomous smart contracts, and secure data provenance for AI training. The synergy between AI's analytical power and Blockchain's immutability shows significant potential to increase efficiency, reduce fraud, and build trust among stakeholders. This indicates that the AI-Powered Blockchain model has a positive and significant effect on optimizing Industry 4.0 systems. Thus, this integration can be recommended as an innovative framework for building autonomous, transparent, and intelligent industrial systems.

References

Alazab, M., & Alhyari, S. (2024). Industry 4.0 innovation: A systematic literature review on the role of blockchain technology in creating smart and sustainable manufacturing facilities. Information, 15(2), 7 https://doi.org/10.3390/info15020078

Bhumichai, D., Smiliotopoulos, C., Benton, R., Kambourakis, G., & Damopoulos, D. (2024). The convergence of artificial intelligence and blockchain: The state of play and the road ahead. Information, 15(5), 268. https://doi.org/10.3390/info15050268

Casino, F., Dasaklis, T. K., & Patsakis, C. (2019). A systematic literature review of blockchain-based applications: Current status, classification and open issues. Telematics and Informatics, 36, 55–81. https://doi.org/10.1016/j.tele.2018.11.006

Jagatheesaperumal, S., Sundaresan, R., & Senthil Kumar, R. (2021). Artificial intelligence and machine learning in smart manufacturing: A review. International Journal of Intelligent Engineering and Systems, 14(4), 124–139. https://doi.org/10.22266/ijies2021.0831.12

Javaid, M. (2021). Blockchain technology applications for Industry 4.0. Computers & Industrial Engineering, 157, 107432. https://doi.org/10.1016/j.cie.2021.107432

Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. EBSE Technical Report, EBSE-2007-01.

Kumari, P. (2023). Blockchain challenges and opportunities in industrial automation systems. Journal of Industrial Information Integration, 29, 100375. https://doi.org/10.1016/j.jii.2023.100375

Palwe, S., & Sirsikar, S. (2021). Integrating artificial intelligence and blockchain for secure industrial automation: A conceptual framework. International Journal of Advanced Computer Science, 12(9), 52–63.

Peres, R. S., Jia, X., Lee, J., Sun, K., Colombo, A. W., & Barata, J. (2020). Industrial artificial intelligence in Industry 4.0 – Systematic review, challenges, and outlook. IEEE Access, 8, 220121–220139. https://doi.org/10.1109/ACCESS.2020.3042874

Petticrew, M., & Roberts, H. (2006). Systematic reviews in the social sciences: A practical guide. Malden, MA: Blackwell Publishing.

Polas, M., Ahmed, R., & Hoque, M. R. (2022). Integrating AI and blockchain for sustainable industrial operations: Challenges and future prospects. Sustainability, 14(12), 7442. https://doi.org/10.3390/su14127442

Ruoti, S., Kaiser, B., Yerukhimovich, A., Clark, J., & Cunningham, R. (2020). Blockchain technology: What is it good for? Communications of the ACM, 63(1), 46–53. https://doi.org/10.1145/3369752

Soori, M., Dastres, R., & Arezoo, B. (2024). AI-powered blockchain technology in Industry 4.0: A review. Journal of Economy and Technology, 1(1), 222–241. https://doi.org/10.1016/j.ject.2024.01.001

Tathavadekar, R., & Mahankale, S. (2025). Leveraging blockchain and AI integration in smart industry ecosystems. Procedia Computer Science, 218, 340–351. https://doi.org/10.1016/j.procs.2024.12.034

Wang, Y., Li, M., & Yang, J. (2022). A comprehensive review of AI–blockchain integration in digital business systems. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2022.3167421

Zonta, T., Costa, C. A. D., Righi, R. R., Lima, M. J. D., Trindade, E. S., & Li, G. P. (2020). Predictive maintenance in the Industry 4.0: A systematic literature review. Computers & Industrial Engineering, 150, 106889. https://doi.org/10.1016/j.cie.2020.106889

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Published

2025-10-31

Issue

Vol. 2 No. 5 (2025): Oktober

Section

Articles

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