Optimizing Business Workflow Using AI Integrated Blockchain Platforms - Djamali, Muhammad Fadheel; Lusiana, Dewi; Parastry, Annisa; Al-Kamari, Omar Arif (ADI Publisher, 2025)
In today’s fast evolving digital economy, business workflows often suffer from inefficiencies, data silos, and security vulnerabilities, particularly in environments relying on legacy systems and centralized control. To address these challenges, this study investigates the integration of Artificial Intelligence (AI) and blockchain technologies as a unified platform for enhancing workflow efficiency, transparency, and security across business operations. The primary objective of this research is to analyze how combining AI’s predictive and automation capabilities with blockchain’s decentralized and immutable ledger can optimize key workflow processes such as approval cycles, data validation, and task automation. This study adopts a qualitative case study approach, supported by system modeling and comparative analysis between conventional workflows and AI blockchain enabled systems within a mid sized logistics enterprise. The findings reveal that the integrated platform significantly reduces processing time, enhances traceability, and minimizes errors, especially in interdepartmental transactions and decision making processes. In addition, the use of smart contracts triggered by AI based insights eliminates redundant steps, enabling real time process adaptation. These results confirm that the fusion of AI and blockchain delivers measurable improvements in workflow optimization, offering a scalable and secure foundation for digital transformation. In conclusion, this research demonstrates that AI integrated blockchain platforms not only optimize operational workflows but also provide strategic value for organizations seeking long term agility and resilience in the face of rapid technological and market shifts.