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Blockchain is a shared, immutable ledger that facilitates recording transactions and tracking assets in a business network (Sylim et al., 2018). As a disruptive technology that provides businesses with greater trust, security, and efficiencies. Its applications span various fields, with a market expected to exceed 10 billion US dollars by 2022 (Petroc, 2022).
Despite these advantages, blockchain technology still faces challenges in its business applications (Xing & Marwala, 2018), and Artificial intelligence (AI) may be one of the most important tools to solve these challenges. While blockchain serves as a ledger, it lacks sufficient capabilities to make complex decisions or deal with security threats (Xing & Marwala, 2018). By contrast, AI technologies may extract and transform data into valuable insights (e.g., neural networks, data mining) and generative solutions (e.g., genetic algorithm, machine learning) for blockchain applications. AI-enabled blockchain refers to integrating AI and blockchain, where AI enables analytics and decision-making based on data collected, shared, and stored by blockchain (Xiong et al., 2020). The synergy between AI and blockchain is akin to the cooperation between the body and the brain. Blockchain acts as a body, collecting and storing data and sharing it with the AI system, which acts as a brain, performing analysis, deciding, and supporting the operation of the blockchain.
Recently, a growing number of AI-enabled blockchain applications have already been developed in finance (Y. Wang et al., 2022), smart manufacturing (Teng et al., 2022), supply chain (Y. Wang, 2021), healthcare (Al-Otaibi, 2022), transportation (S. Wang et al., 2022), and other business fields, exerting a significant influence over the industries. Despite the growing importance of AI-enabled blockchain, the current literature primarily focuses on the individual applications and ethical considerations of AI in the blockchain. However, AI is an emerging and promising technology that can contribute to blockchain's technological development and empowerment in business. Therefore, it is essential to explore the general business application scenarios of AI-enabled blockchain and understand the role that AI plays in enhancing blockchain applications.
In addition, while AI can enhance blockchain applications by improving sustainability, scalability, risk identification, and business innovation (Alkan, 2022; Wang et al., 2021), developers and service providers across various application scenarios must also consider the potential negative impacts of AI on ethical issues such as privacy, fairness, and dignity. The ethical issues posed by AI have attracted increasing research attention (Kazim & Koshiyama, 2021). For example, AI may violate citizens' dignity (Morse et al., 2021) and privacy (Campbell et al., 2020), and it is prone to algorithm bias (Akter et al., 2022). Integrating AI in commercial blockchain applications raises inevitable ethical concerns. Therefore, besides exploring the business implications, it is critical to better understand the ethical implications of AI-enabled blockchain.
While there are some review papers on the intersection of blockchain and AI, few have focused specifically on AI-enabled blockchain from a business and management perspective. For example, Hussain and Al-Turjman (2021) analyze the technical aspects of AI and blockchain without considering their business implications, while Kumar et al. (2022) provide a general overview of integrating these technologies without a comprehensive analysis of AI's role in blockchain applications. Salah et al. (2019) investigate how blockchain enables AI, rather than how AI enables blockchain applications. In the last five years, this area of research has seen rapid growth, with nearly 100 papers being published annually. Given this substantial body of literature, it is crucial to conduct a systematic review to gain a deeper understanding of the current state of research and identify future research directions.