Blockchain Enabled AI for Transparency and Operational Efficiency in Digital Business Ecosystems

Authors

DOI:

https://doi.org/10.34306/ajri.v8i1.1610

Keywords:

Blockchain, Artificial Intelligence, Digital Business Ecosystems, Transparency, Systematic Literature Review

Abstract

The rapid advancement of digital technologies has encouraged organizations to integrate emerging innovations to improve business performance, transparency, and operational efficiency. Among these technologies, blockchain and Artificial Intelligence (AI) have gained significant attention due to their complementary capabilities. Blockchain provides decentralized, transparent, and secure data management, while AI enables intelligent decision making through advanced data analytics. The integration of these technologies offers substantial opportunities for transforming digital business ecosystems. This study aims to systematically examine the role of blockchain enabled artificial intelligence in enhancing transparency and operational efficiency within digital business environments, as well as identifying key benefits, challenges, and future research directions. A Systematic Literature Review (SLR) approach was employed by analyzing peer reviewed articles published between 2020 and 2025. Relevant studies were collected from major academic databases using predefined inclusion and exclusion criteria. The selected literature was then synthesized and categorized based on application domains, technological contributions, and business outcomes. The findings indicate that the integration of blockchain and AI significantly improves business transparency through immutable record keeping, traceability, and secure data sharing. Furthermore, AI driven analytics combined with blockchain infrastructure enhances operational efficiency by automating business processes, optimizing resource allocation, improving supply chain visibility, and supporting real time decision making. The review also reveals challenges related to scalability, interoperability, data privacy, implementation costs, and regulatory compliance. Blockchain enabled AI represents a transformative approach for modern digital business ecosystems by strengthening transparency, security, and operational performance, while providing future research opportunities for sustainable and intelligent business innovation.

Article metrics

16 Views
6 Downloads

All recorded visits and downloads

Downloads

Download data is not yet available.

References

[1] E. J. Omol, “Organizational digital transformation: from evolution to future trends,” Digital Transformation and Society, vol. 3, no. 3, pp. 240–256, 2024.

[2] M. Thanasi-Boc¸e and J. Hoxha, “Blockchain for sustainable development: a systematic review,” Sustainability, vol. 17, no. 11, p. 4848, 2025.

[3] Q. Aini, D. Manongga, U. Rahardja, I. Sembiring, and Y.-M. Li, “Understanding behavioral intention to use of air quality monitoring solutions with emphasis on technology readiness,” International Journal of Human Computer Interaction, pp. 1–21, 2024.

[4] Y. Luo, S. Chen, and P. Zhang, “A review of research on data security risk: Consequences, mechanisms, and response,” Journal of Economic Surveys, 2026.

[5] 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, 2024.

[6] U. Rahardja, Q. Aini, A. S. Bist, S. Maulana, and S. Millah, “Examining the interplay of technology readiness and behavioural intentions in health detection safe entry station,” JDM (Jurnal Dinamika Manajemen), vol. 15, no. 1, pp. 125–143, 2024.

[7] O. Kuznetsov, P. Sernani, L. Romeo, E. Frontoni, and A. Mancini, “On the integration of artificial intelligence and blockchain technology: a perspective about security,” IEEE Access, vol. 12, pp. 3881–3897, 2024.

[8] H. Cheng, J. H. Husen, Y. Lu, T. Racharak, N. Yoshioka, N. Ubayashi, and H. Washizaki, “Generative ai for requirements engineering: A systematic literature review,” Software: Practice and Experience, vol. 56, no. 2, pp. 141–170, 2026.

[9] R. Sivaraman, M.-H. Lin, M. I. C. Vargas, S. I. S. Al-Hawary, U. Rahardja, F. A. H. Al-Khafaji, E. V. Golubtsova, and L. Li, “Multiobjective hybrid system development: To increase the performance of diesel/photovoltaic/wind/battery system.” Mathematical Modelling of Engineering Problems, vol. 11, no. 3, 2024.

[10] J. Singh, S. Bharany, S. Rani, A. U. Rehman, B. M. Taye, R. Pant, and U. Kaur, “A systematic review of blockchain, ai, and cloud integration for secure digital ecosystems,” International Journal of Networked and Distributed Computing, vol. 13, no. 2, p. 28, 2025.

[11] D. S. Bindeeba, E. K. Tukamushaba, and R. Bakashaba, “Digital transformation and its multidimensional impact on sustainable business performance: evidence from a metaanalytic review,” Future Business Journal, vol. 11, no. 1, p. 90, 2025.

[12] E. Susetyono, D. S. Priyarsono, A. Sukmawati, and P. Nurhayati, “Improving risk management maturity in ultra micro soe holding companies,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 310–324, 2026.

[13] S. Sorooshian, “The sustainable development goals of the united nations: A comparative midterm research review,” Journal of Cleaner Production, vol. 453, p. 142272, 2024.

[14] T. Muciaccia and P. Tedeschi, “Future scenarios for the infrastructure digitalization: The road ahead,” Frontiers in the Internet of Things, vol. 2, p. 1140799, 2023.

[15] Y. D. Anna, H. Djajadikerta, and A. Setiawan, “Strengthening the foundations of socialpreneurship through integrated reporting a systematic bibliometric perspective,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 296–309, 2026.

[16] S. Kumar, W. M. Lim, U. Sivarajah, and J. Kaur, “Artificial intelligence and blockchain integration in business: trends from a bibliometric content analysis,” Information systems frontiers, vol. 25, no. 2, pp. 871–896, 2023.

[17] E. O. Udeh, P. Amajuoyi, K. B. Adeusi, and A. O. Scott, “The role of iot in boosting supply chain transparency and efficiency,” Magna Scientia Advanced Research and Reviews, vol. 12, no. 1, pp. 178– 197, 2024.

[18] E. T. Rusmiati, L. Febrina, Y. Sari, and E. M. S. Sakti, “Adoption of ai driven ecological preaching systems using sem pls analysis,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 284– 295, 2026.

[19] H. Shafa, “Artificial intelligence-driven business intelligence models for enhancing decision-making in us enterprises,” ASRC Procedia: Global Perspectives in Science and Scholarship, vol. 1, no. 01, pp. 771–800, 2025.

[20] D. Chenger and R. N. Pettigrew, “Leveraging data driven decisions: a framework for building intracompany capability for supply chain optimization and resilience,” Supply Chain Management: An International Journal, vol. 28, no. 6, pp. 1026–1039, 2023.

[21] M. D. T. P. Nasution, Y. Rossanty, R. Harahap, A. R. Tanjung, and T. A. M. Nasution, “Technology driven resource utilization and integration to enhance firm performance,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 268–283, 2026.

[22] A. S. Al Najjar and M. S. Qandeel, “Operational strategy, capabilities, and successfully accomplishing business strategy,” Journal of Applied Research in Technology & Engineering, vol. 6, no. 1, pp. 1–11, 2025.

[23] R. E. Indrajit, M. V. A. Sin, E. A. Nabila, W. N. Wahid, and N. Septiani, “Optimizing business process efficiency through artificial intelligence integration in industry 4.0,” Smart Human centered Emerging Research in Machine Intelligence, vol. 1, no. 2, pp. 47–55, 2025.

[24] E. Arif, S. Suherman, and A. P. Widodo, “Analyzing public sentiment on digital banks in indonesia via social media x,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 253–267, 2026.

[25] Y. Shahsavari, Y. Baseri, A. Hafid, O. A. Dambri, and D. Makrakis, “Integration of federated learning and blockchain in health care: Tutorial on medical data, architectures, privacy, security, and regulatory compliance,” Journal of Medical Internet Research, vol. 28, p. e80178, 2026.

[26] D. Pasurangga and S. Baltasar, “Data driven predictive maintenance framework for railway safety in indonesia,” ADI Journal on Recent Innovation, vol. 7, no. 1, pp. 75–87, 2025.

[27] G. Carlo Torres, L. Ledbetter, S. Cantrell, A. R. L. Alomo, T. J. Blodgett, M. V. Bongar, S. Hatoum, S. Hendren, R. Loa, S. Montana et al., “Adherence to prisma 2020 reporting guidelines and scope of systematic reviews published in nursing: A cross-sectional analysis,” Journal of Nursing Scholarship, vol. 56, no. 4, pp. 531–541, 2024.

[28] M. F. Djamali, D. Lusiana, A. Parastry, and O. A. Al-Kamari, “Optimizing business workflow using ai integrated blockchain platforms,” ADI Journal on Recent Innovation, vol. 7, no. 1, pp. 62–74, 2025.

[29] N. El Akrami, M. Hanine, E. S. Flores, D. G. Aray, and I. Ashraf, “Unleashing the potential of blockchain and machine learning: Insights and emerging trends from bibliometric analysis,” IEEE access, vol. 11, pp. 78 879–78 903, 2023.

[30] T. Pujiati, M. Kamil, N. Silawati, and R. S. Ikhsan, “Integrating ai-driven predictive analytics and smart contracts for data-driven supply chain risk management,” ADI Journal on Recent Innovation, vol. 7, no. 1, pp. 50–61, 2025.

[31] E. C. Martinez, P. E. G. Hasbun, V. P. S. Vargas, O. Y. Garc´ıa-Gonz´alez, M. D. F. Madera, D. E. R. Capistr´an, T. C. Carmona, C. S. Cruz, and C. T. Hooper, “A comprehensive guide to conduct a systematic review and meta analysis in medical research,” Medicine, vol. 104, no. 33, p. e41868, 2025.

[32] C. S. Bangun, S. Solahudin, A. Sutarman, and S. Dlamini, “The role of application programming interface in transforming restaurant delivery operations,” Startupreneur Business Digital (SABDA Journal), vol. 5, no. 1, pp. 88–95, 2026.

[33] A. Viet Tran and B. T. Khoa, “Systematic review of blockchain business applications and the metaverse,” Sage Open, vol. 15, no. 4, p. 21582440251398266, 2025.

[34] D. Manongga, I. Kovac et al., “Cyberpreneurial mindset as a driver of digital startup success in emerging digital economies,” Startupreneur Business Digital (SABDA Journal), vol. 5, no. 1, pp. 67–77, 2026.

[35] S. N. Kaldeh, H. Yousefi, M. Abdoos, M. A. Shirazi, and Y. Noorollahi, “Mapping thermal energy storage research in buildings (2020–2025): a bibliometric analysis of trends, themes, and global collaboration,” Energy Conversion and Management: X, p. 101345, 2025.

[36] R. Indrawan, E. D. Very, D. Tribuana, and E. A. Nabila, “Aiot driven smart solar system for real time predictive sustainable energy management,” International Transactions on Artificial Intelligence, vol. 4, no. 1, pp. 105–114, 2025.

[37] G. M. Zebari and N. Al Musalhi, “A comprehensive review of integrating ai and blockchain security: Innovations, challenges, and future directions,” Security and Privacy, vol. 8, no. 5, p. e70094, 2025.

[38] E. Setiawati, J. Edwards, M. M. Siahaan et al., “Increasing accessibility and personalization in distance learning through adaptive e learning technology,” Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi, vol. 4, no. 1, pp. 20–29, 2025.

[39] H. Han, R. K. Shiwakoti, R. Jarvis, C. Mordi, and D. Botchie, “Accounting and auditing with blockchain technology and artificial intelligence: A literature review,” International journal of accounting information systems, vol. 48, p. 100598, 2023.

[40] L. Meria, M. S. Gunawan, S. Solahudin, U. Rahardja, and A. Patel, “Enhancing digital business students competence through ui/ux design training for digital product development,” ADI Pengabdian Kepada Masyarakat, vol. 6, no. 2, pp. 133–144, 2026.

[41] L. M. Gelsomino, S. Sardesai, M. Pirttil¨a, and M. Henke, “Addressing the relation between transparency and supply chain finance schemes,” International journal of production research, vol. 61, no. 17, pp. 5806–5821, 2023.

[42] M. S. Gunawan, U. Rahardja, A. Ardien, J. Edwards, and D. I. Desrianti, “Enhancing audience engagement through interactive aidriven narrative structures,” Bridging of Emerging AI and Media Broadcasting (BEAM), vol. 1, no. 2, pp. 87–98, 2026.

[43] Y. Saidu, S. M. Shuhidan, D. A. Aliyu, I. A. Aziz, and S. Adamu, “Convergence of blockchain, iot, and ai for enhanced traceability systems: A comprehensive review,” IEEE Access, vol. 13, pp. 16 838–16 865, 2025.

[44] Ministry of Administrative and Bureaucratic Reform of the Republic of Indonesia, “Ministry of PANRB: Digital Transformation and Bureaucratic Reform,” https://www.menpan.go.id/,2024, accessed:Sep. 30, 2026.

Downloads

Published

2026-09-30

Issue

Section

Articles

How to Cite

Blockchain Enabled AI for Transparency and Operational Efficiency in Digital Business Ecosystems. (2026). ADI Journal on Recent Innovation (AJRI), 8(1), 110-121. https://doi.org/10.34306/ajri.v8i1.1610