The use of smart contracts in areas such as DeFi and tokenization has not yet reached the desired efficiency level. It can be said that there are many reasons for this. First, since smart contracts are a piece of code, creating smart contracts requires coding knowledge. Even if the best software developer writes this code, it may contain bugs. Smart contracts cannot automatically adapt to these changes when conditions change for transaction parties, because these software programs lack dynamic decision-making feature. Smart contracts are closed to change due to the “tamper-proof” feature of the blockchain. The programming language used in smart contracts is rigid. Additionally, difficulties are encountered in the enforcement of court decisions in the blockchain ecosystem in general. Finally, undesirable results may occur in the execution of smart contracts due to incorrect data provided by oracles that carry external data to smart contracts.
Despite all these difficulties, the value of the global smart contract market was calculated to be 684.3 million dollars in 2022. From 2023 to 2030, this number is expected to increase at a compound annual growth rate (CAGR) of 82.2%. It seems that one of the most important factors underlying this growth will be the increasing interaction between artificial intelligence and blockchain.
Particular attention was drawn to the intersection of blockchain and smart contracts in the report titled Smart Contracts prepared by the EU Blockchain Observatory and Forum Report in 2022. “Several experts in this area suggest that the fields of AI and blockchain may benefit from each other’s defining characteristics. Smart contracts can benefit from the advanced computational capabilities and adaptive systems of AI technology, while AI implementations could utilise smart contract technology for its autonomous execution of sets of rules and to provide a secure environment for sensitive and valuable machine learning data to exist.” Thus, both artificial intelligence supports blockchain applications, and blockchain and blockchain applications can contribute to artificial intelligence mechanisms.
Similarly, the Bank of International Settlements, in its report published in May this year (“Crypto, tokens and DeFi: Navigating the Regulatory Landscape”), stated that resources and experiences are needed to understand and take action against the risks posed by crypto assets and DeFi ecosystems. It has been pointed out that new technologies, design features, and market participants are constantly improving this ecosystem. One of these technologies is the use of artificial intelligence tools, especially GenAI, that is, generative artificial intelligence technologies, in the development and coding of smart contracts.
More adaptable artificial intelligence systems such as logic and neural networks and artificial intelligence applications such as Natural Language Processing (NLP), machine learning, data mining, online analytical processing, business performance management, benchmarking, and predictive analytics can be used in smart contracts. Thus, smart contracts can learn from their own behavior, change their behavior to suit the circumstances, interpret ambiguous statements in traditional contracts, and even make effective decisions in situations in which transactions require interaction with the physical world.
Thanks to artificial intelligence integration, errors in the establishment of the smart contract can be detected in advance (before it is deployed). Systems based on machine learning can correct inadequate algorithms. By using deep learning applications, it may be possible to create smart contracts without bugs. In this context, artificial intelligence-supported smart contracts are expected to make suggestions regarding the content of contract clauses. With the support of artificial intelligence, a self-executing smart contract code can be created by analyzing a traditional contract. AI tools can examine the workflow of previous smart contracts and suggest better alternatives.
With natural language processing (NLP), the will of the smart contract parties can be analyzed, and possible disputes can be prevented from the very beginning by ensuring that the parties are parties to more appropriate contractual relationships. Artificial intelligence-supported smart contracts can provide a human-readable and understandable understanding of the purpose for which the smart contract was coded and its functions.
Nowadays, smart contracts seem to be preferred for simpler transactions. However, by integrating artificial intelligence (AI) even more complex smart contracts can be established and executed. By leveraging AI and machine learning algorithms, contract terms can be adapted to reflect current market conditions and asset performance.
It is believed that ChatGPT could have a significant impact on the creation and execution of smart contracts. ChatGPT may be used to analyze and interpret smart contract data. The AI language model helps build and test smart contract codes before they are deployed on blockchain networks. This makes it easier to identify errors or issues in the code. ChatGPT can even help developers write bug-free or more efficient codes. Also, the technical knowledge or coding experience needed for the establishment of a smart contract is eliminated. ChatGPT may also use network analysis data to detect unusual activity such as malicious transaction attempts or unauthorized access. Thanks to ChatGPT, smart contract-related risks may be easily understood and communicated to a wider audience. Thus, transparency and reliability may be increased in the use of smart contracts.