Integrating Artificial Intelligence with Blockchain: A Literature Review on Opportunities, Challenges, and Applications
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Abstract
The integration of Artificial Intelligence (AI) and Blockchain represents a paradigm shift in digital transformation, offering enhanced security, scalability, and automation. While previous research has explored these technologies independently, this study provides a comprehensive review of their convergence, synthesizing insights across multiple domains such as finance, healthcare, and supply chain management. The findings highlight the bidirectional enhancement of AI-Blockchain integration: Blockchain reinforces AI’s reliability by ensuring data immutability and transparency, whereas AI optimizes Blockchain efficiency through intelligent consensus mechanisms and fraud detection. However, significant challenges remain, including scalability constraints, computational overhead, and regulatory concerns. This study contributes to the theoretical understanding of AI-Blockchain synergy by integrating concepts from Computational Trust Theory and Decentralized Ledger Theory. Practically, it provides actionable insights for industry stakeholders, particularly in decentralized finance, privacy-preserving AI models, and secure digital transactions. The novelty of this research lies in its examination of AI-Blockchain integration through geographical and temporal trends, revealing disparities in adoption and regulatory responses. Despite its potential, real-world implementation remains limited, necessitating further empirical validation and exploration of emerging technologies such as quantum computing and the Internet of Things (IoT). By addressing these gaps, this study serves as a foundation for future research and policy development, advocating for interdisciplinary collaboration to ensure secure, efficient, and ethical AI-Blockchain ecosystems. The implications extend beyond academia, offering strategic guidance for practitioners and policymakers navigating the complexities of this technological convergence.
References
1
R. Almashawreh, M. Talukder, S. K. Charath, and M. I. Khan, "AI Adoption in Jordanian SMEs: The Influence of Technological and Organizational Orientations," Glob. Bus. Rev., Jun. 2024. https://doi.org/10.1177/09721509241250273
2
A. J. R. Torres, J. M. C. Alberto, A. P. J. Guieb, and J. A. Villarama, "Language, Identity, and Ethics in AI-Driven Art: Perspectives from Human Artists in Digital Environments," Lang. Technol. Soc. Media, vol. 3, no. 1, pp. 17-29, 2025. https://doi.org/10.70211/ltsm.v3i1.137
3
D. Bhumichai, C. Smiliotopoulos, R. Benton, G. Kambourakis, and D. Damopoulos, "The Convergence of Artificial Intelligence and Blockchain: The State of Play and the Road Ahead," Information, vol. 15, no. 5, p. 268, May 2024. https://doi.org/10.3390/info15050268
4
A. Bin Rashid and M. A. K. Kausik, "AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications," Hybrid Adv., vol. 7, p. 100277, Dec. 2024. https://doi.org/10.1016/j.hybadv.2024.100277
5
V. Charles, A. Emrouznejad, and T. Gherman, "A critical analysis of the integration of blockchain and artificial intelligence for supply chain," Ann. Oper. Res., vol. 327, no. 1, pp. 7-47, Aug. 2023. https://doi.org/10.1007/s10479-023-05169-w
6
M. Riad, M. Naimi, and C. Okar, "Enhancing Supply Chain Resilience Through Artificial Intelligence: Developing a Comprehensive Conceptual Framework for AI Implementation and Supply Chain Optimization," Logistics, vol. 8, no. 4, p. 111, Nov. 2024. https://doi.org/10.3390/logistics8040111
7
M. Javaid, A. Haleem, R. P. Singh, R. Suman, and S. Khan, "A review of Blockchain Technology applications for financial services," BenchCouncil Trans. Benchmarks, Stand. Eval., vol. 2, no. 3, p. 100073, Jul. 2022. https://doi.org/10.1016/j.tbench.2022.100073
8
E. Sánchez-García, J. Martínez-Falcó, B. Marco-Lajara, and E. Manresa-Marhuenda, "Revolutionizing the circular economy through new technologies: A new era of sustainable progress," Environ. Technol. Innov., vol. 33, p. 103509, Feb. 2024. https://doi.org/10.1016/j.eti.2023.103509
9
I. H. Sarker, "Machine Learning: Algorithms, Real-World Applications and Research Directions," SN Comput. Sci., vol. 2, no. 3, p. 160, May 2021. https://doi.org/10.1007/s42979-021-00592-x
10
M. Soori, F. K. G. Jough, R. Dastres, and B. Arezoo, "AI-Based Decision Support Systems in Industry 4.0, A Review," J. Econ. Technol., Aug. 2024. https://doi.org/10.1016/j.ject.2024.08.005
11
C. Chakraborty, M. Bhattacharya, S. Pal, and S.-S. Lee, "From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare," Curr. Res. Biotechnol., vol. 7, p. 100164, 2024. https://doi.org/10.1016/j.crbiot.2023.100164
12
C. Di Ciccio, "Blockchain and Distributed Ledger Technologies," in The Role of Distributed Ledger Technology in Banking, Cambridge University Press, 2024, pp. 11-34. https://doi.org/10.1017/9781009411783.003
13
K. R. Ballamudi, "Blockchain as a Type of Distributed Ledger Technology," Asian J. Humanit. Art Lit., vol. 3, no. 2, pp. 127-136, Dec. 2016. https://doi.org/10.18034/ajhal.v3i2.528
14
L. Theodorakopoulos, A. Theodoropoulou, and C. Halkiopoulos, "Enhancing Decentralized Decision-Making with Big Data and Blockchain Technology: A Comprehensive Review," Appl. Sci., vol. 14, no. 16, p. 7007, Aug. 2024. https://doi.org/10.3390/app14167007
15
H. L. J. Ting, X. Kang, T. Li, H. Wang, and C.-K. Chu, "On the Trust and Trust Modeling for the Future Fully-Connected Digital World: A Comprehensive Study," IEEE Access, vol. 9, pp. 106743-106783, 2021. https://doi.org/10.1109/ACCESS.2021.3100767
16
Q. Wang, W. Hong, and C. Huang, "Study on the Computational Trust and Its Model," IOP Conf. Ser. Mater. Sci. Eng., vol. 790, no. 1, p. 012136, Mar. 2020. https://doi.org/10.1088/1757-899X/790/1/012136
17
N. Hakimi Aghdam, M. Ashtiani, and M. Abdollahi Azgomi, "An uncertainty-aware computational trust model considering the co-existence of trust and distrust in social networks," Inf. Sci. (Ny.), vol. 513, pp. 465-503, Mar. 2020. https://doi.org/10.1016/j.ins.2019.10.067
18
J. Wang, Y. Li, Y. Wu, W. Zheng, S. Zhou, and X. Xiong, "Blockchain sharding scheme based on generative AI and DRL: Applied to building internet of things," Internet Things Cyber-Physical Syst., vol. 4, pp. 333-349, 2024. https://doi.org/10.1016/j.iotcps.2024.11.001
19
K. Lu, X. Zhang, T. Zhai, and M. Zhou, "Adaptive Sharding for UAV Networks: A Deep Reinforcement Learning Approach to Blockchain Optimization," Sensors, vol. 24, no. 22, p. 7279, Nov. 2024. https://doi.org/10.3390/s24227279
20
E. Ferrara, "GenAI against humanity: nefarious applications of generative artificial intelligence and large language models," J. Comput. Soc. Sci., vol. 7, no. 1, pp. 549-569, Apr. 2024. https://doi.org/10.1007/s42001-024-00250-1
21
R. Kaur, D. Gabrijelčič, and T. Klobučar, "Artificial intelligence for cybersecurity: Literature review and future research directions," Inf. Fusion, vol. 97, p. 101804, Sep. 2023. https://doi.org/10.1016/j.inffus.2023.101804
22
J. M. Borky and T. H. Bradley, "Protecting Information with Cybersecurity," in Effective Model-Based Systems Engineering, Cham: Springer International Publishing, 2019, pp. 345-404. https://doi.org/10.1007/978-3-319-95669-5_10
23
S. T. Hossain, T. Yigitcanlar, K. Nguyen, and Y. Xu, "Local Government Cybersecurity Landscape: A Systematic Review and Conceptual Framework," Appl. Sci., vol. 14, no. 13, p. 5501, Jun. 2024. https://doi.org/10.3390/app14135501
24
I. Oncioiu et al., "The Impact of Big Data Analytics on Company Performance in Supply Chain Management," Sustainability, vol. 11, no. 18, p. 4864, Sep. 2019. https://doi.org/10.3390/su11184864
25
A. Alenizi, S. Mishra, and A. Baihan, "Enhancing secure financial transactions through the synergy of blockchain and artificial intelligence," Ain Shams Eng. J., vol. 15, no. 6, p. 102733, Jun. 2024. https://doi.org/10.1016/j.asej.2024.102733
26
D. Ressi, R. Romanello, C. Piazza, and S. Rossi, "AI-enhanced blockchain technology: A review of advancements and opportunities," J. Netw. Comput. Appl., vol. 225, p. 103858, May 2024. https://doi.org/10.1016/j.jnca.2024.103858
27
M. Usman and U. Qamar, "Secure Electronic Medical Records Storage and Sharing Using Blockchain Technology," Procedia Comput. Sci., vol. 174, pp. 321-327, 2020. https://doi.org/10.1016/j.procs.2020.06.093
28
Z. Wang, Q. Shen, S. Bi, and C. Fu, "AI Empowers Data Mining Models for Financial Fraud Detection and Prevention Systems," Procedia Comput. Sci., vol. 243, pp. 891-899, 2024. https://doi.org/10.1016/j.procs.2024.09.107
29
J. Wu, L. Yuan, T. Xie, and H. Dai, "A sharding blockchain protocol for enhanced scalability and performance optimization through account transaction reconfiguration," J. King Saud Univ. - Comput. Inf. Sci., vol. 36, no. 8, p. 102184, Oct. 2024. https://doi.org/10.1016/j.jksuci.2024.102184
30
S. K.M. et al., "Privacy-preserving in Blockchain-based Federated Learning systems," Comput. Commun., vol. 222, pp. 38-67, Jun. 2024. https://doi.org/10.1016/j.comcom.2024.04.024
31
W. Hua, Y. Chen, M. Qadrdan, J. Jiang, H. Sun, and J. Wu, "Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review," Renew. Sustain. Energy Rev., vol. 161, p. 112308, Jun. 2022. https://doi.org/10.1016/j.rser.2022.112308
32
A. M. Shamsan Saleh, "Blockchain for secure and decentralized artificial intelligence in cybersecurity: A comprehensive review," Blockchain Res. Appl., vol. 5, no. 3, p. 100193, Sep. 2024. https://doi.org/10.1016/j.bcra.2024.100193
33
Z. Zhang et al., "TbDd: A new trust-based, DRL-driven framework for blockchain sharding in IoT," Comput. Networks, vol. 244, p. 110343, May 2024. https://doi.org/10.1016/j.comnet.2024.110343
34
L. Zhou, A. Diro, A. Saini, S. Kaisar, and P. C. Hiep, "Leveraging zero knowledge proofs for blockchain-based identity sharing: A survey of advancements, challenges and opportunities," J. Inf. Secur. Appl., vol. 80, p. 103678, Feb. 2024. https://doi.org/10.1016/j.jisa.2023.103678
35
M. Hiwale, R. Walambe, V. Potdar, and K. Kotecha, "A systematic review of privacy-preserving methods deployed with blockchain and federated learning for the telemedicine," Healthc. Anal., vol. 3, p. 100192, Nov. 2023. https://doi.org/10.1016/j.health.2023.100192
36
J. Yuan, W. Liu, J. Shi, and Q. Li, "Approximate homomorphic encryption based privacy-preserving machine learning: a survey," Artif. Intell. Rev., vol. 58, no. 3, p. 82, Jan. 2025. https://doi.org/10.1007/s10462-024-11076-8
37
S. Stein Smith, Blockchain, Artificial Intelligence and Financial Services, in Future of Business and Finance, Cham: Springer International Publishing, 2020. https://doi.org/10.1007/978-3-030-29761-9
38
P. Radanliev, "AI Ethics: Integrating Transparency, Fairness, and Privacy in AI Development," Appl. Artif. Intell., vol. 39, no. 1, Dec. 2025. https://doi.org/10.1080/08839514.2025.2463722
39
Z. Liu, X. Yu, N. Liu, C. Liu, A. Jiang, and L. Chen, "Integrating AI with detection methods, IoT, and blockchain to achieve food authenticity and traceability from farm-to-table," Trends Food Sci. Technol., p. 104925, Feb. 2025. https://doi.org/10.1016/j.tifs.2025.104925
40
Y. Ikeda, R. Hadfi, T. Ito, and A. Fujihara, "Anomaly detection and facilitation AI to empower decentralized autonomous organizations for secure crypto-asset transactions," AI Soc., Jan. 2025. https://doi.org/10.1007/s00146-024-02166-w
41
R. Teixeira, G. Baldoni, M. Antunes, D. Gomes, and R. L. Aguiar, "Leveraging decentralized communication for privacy-preserving federated learning in 6G Networks," Comput. Commun., vol. 233, p. 108072, Mar. 2025. https://doi.org/10.1016/j.comcom.2025.108072
42
N. Etemadi, P. Van Gelder, and F. Strozzi, "An ISM Modeling of Barriers for Blockchain/Distributed Ledger Technology Adoption in Supply Chains towards Cybersecurity," Sustainability, vol. 13, no. 9, p. 4672, Apr. 2021. https://doi.org/10.3390/su13094672
43
Y. I. Alzoubi and A. Mishra, "Blockchain consensus mechanisms comparison in fog computing: A systematic review," ICT Express, vol. 10, no. 2, pp. 342-373, Apr. 2024. https://doi.org/10.1016/j.icte.2024.02.008
44
M. Soori, R. Dastres, and B. Arezoo, "AI-powered blockchain technology in industry 4.0, a review," J. Econ. Technol., vol. 1, pp. 222-241, Nov. 2023. https://doi.org/10.1016/j.ject.2024.01.001
45
J. Bughin, J. Seong, J. Manyika, M. Chui, and R. Joshi, "Notes From the AI Frontier: Modeling the Impact of AI on the World Economy," Model. Glob. Econ. impact AI | McKinsey, no. September, pp. 1-61, 2018. https://www.mckinsey.com/featured-insights/artificial-intelligence/notes-from-the-ai-frontier-modeling-the-impact-of-ai-on-the-world-economy
46
L. Willcocks, "Robo-Apocalypse cancelled? Reframing the automation and future of work debate," J. Inf. Technol., vol. 35, no. 4, pp. 286-302, Dec. 2020. https://doi.org/10.1177/0268396220925830
47
D. Hayati and S. Sinha, "Decoding Silence in Digital Cross-Cultural Communication: Overcoming Misunderstandings in Global Teams," Lang. Technol. Soc. Media, vol. 2, no. 2, pp. 128-144, 2024. https://doi.org/10.70211/ltsm.v2i2.60
48
M. Garlinska, M. Osial, K. Proniewska, and A. Pregowska, "The Influence of Emerging Technologies on Distance Education," Electronics, vol. 12, no. 7, p. 1550, Mar. 2023. https://doi.org/10.3390/electronics12071550
49
X.-Y. Wu, "Exploring the effects of digital technology on deep learning: a meta-analysis," Educ. Inf. Technol., vol. 29, no. 1, pp. 425-458, Jan. 2024. https://doi.org/10.1007/s10639-023-12307-1
50
Y. K. Dwivedi et al., "Setting the future of digital and social media marketing research: Perspectives and research propositions," Int. J. Inf. Manage., vol. 59, p. 102168, Aug. 2021. https://doi.org/10.1016/j.ijinfomgt.2020.102168
51
A. Samara, K. Smith, H. Brown, and E. Wonnacott, "Acquiring variation in an artificial language: Children and adults are sensitive to socially conditioned linguistic variation," Cogn. Psychol., vol. 94, pp. 85-114, May 2017. https://doi.org/10.1016/j.cogpsych.2017.02.004
52
P. Schueffel, "DeFi: Decentralized Finance - An Introduction and Overview," J. Innov. Manag., vol. 9, no. 3, pp. I-XI, Nov. 2021. https://doi.org/10.24840/2183-0606_009.003_0001
53
L. Lin, D. Zhou, J. Wang, and Y. Wang, "A Systematic Review of Big Data Driven Education Evaluation," Sage Open, vol. 14, no. 2, Apr. 2024. https://doi.org/10.1177/21582440241242180
54
J. Jeon, S. Lee, and H. Choe, "Beyond ChatGPT: A conceptual framework and systematic review of speech-recognition chatbots for language learning," Comput. Educ., vol. 206, p. 104898, Dec. 2023. https://doi.org/10.1016/j.compedu.2023.104898
55
L. Li, "Colocalized, bidirectional optogenetic modulations in freely behaving mice with a wireless dual-color optoelectronic probe," Nat. Commun., vol. 13, no. 1, 2022. https://doi.org/10.1038/s41467-022-28539-7
56
M. El Hajj and I. Farran, "The Cryptocurrencies in Emerging Markets: Enhancing Financial Inclusion and Economic Empowerment," J. Risk Financ. Manag., vol. 17, no. 10, p. 467, Oct. 2024. https://doi.org/10.3390/jrfm17100467
57
U. Sulubacak et al., "Multimodal machine translation through visuals and speech," Mach. Transl., vol. 34, no. 2-3, pp. 97-147, Sep. 2020. https://doi.org/10.1007/s10590-020-09250-0
Author Biographies
Adu Emmanuel Ifedayo
Department of Educational Technology
Damola Olugbade
Center for Languages and General Studies
Shazia Hamid
Language and Literacy Program, College of Education
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Copyright (c) 2025 Adu Emmanuel Ifedayo, Damola Olugbade, Shazia Hamid
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Last checked 23 Sep 2026.How to Cite
Ifedayo, A. E., Olugbade, D., & Hamid, S. (2025). Integrating Artificial Intelligence with Blockchain: A Literature Review on Opportunities, Challenges, and Applications. Blockchain, Artificial Intelligence, and Future Research, 1(1), 52–69. https://doi.org/10.70211/bafr.v1i1.179