From Data Analytics to Blockchain: AI-Driven Business Intelligence Systems in Securing Digital Assets

Authors

  • Christopher Waylon, Andrew Roman Department of Computer Science, University of Bosnia and Herzegovina Author

Keywords:

AI, blockchain, business intelligence, data analytics, digital assets, security

Abstract

The rapid evolution of digital assets has intensified the need for robust security measures, making the integration of AI-driven business intelligence systems pivotal in safeguarding these assets. This paper explores the transition from traditional data analytics to innovative blockchain solutions, emphasizing the role of artificial intelligence in enhancing security and operational efficiency. By leveraging AI’s predictive analytics and pattern recognition capabilities, organizations can identify potential threats and vulnerabilities in real-time. Additionally, blockchain technology offers decentralized, immutable record-keeping, ensuring transparency and trust in digital transactions. The synergy between AI and blockchain not only enhances the security of digital assets but also facilitates informed decision-making through comprehensive data insights. This study presents a framework that outlines the integration of AI-driven business intelligence systems with blockchain technology, highlighting best practices and real-world applications across various industries. By illustrating the transformative potential of this integration, the paper aims to provide organizations with strategic insights into securing their digital assets while optimizing operational performance.

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Published

2024-12-07