AI and blockchain may seem like polar opposites: Blockchain technology is deterministic, transparent and open to everyone – all transactions are immutably recorded on a public ledger – but it also has a steep learning curve and requires users to understand a complex protocol.
AI, on the other hand, often functions as a “black box,” making decisions based on model parameters and training data sets, providing probabilistic answers rather than strictly predictable answers. However, what these two technologies have in common is that they have both become buzzwords in recent years: venture capital funds are chasing them, and companies are working hard to implement them.
While the synergies between the two are not always obvious, they have great potential for mainstream adoption, especially in the area of decentralized finance. Here’s why:
Driving DeFi user adoption
One of the major obstacles to DeFi adoption is its complexity. AI can play a key role in simplifying user interactions with DeFi platforms, making them more approachable and user-friendly through AI-driven chatbots and virtual assistants that can guide users through complex DeFi protocols. “Mainstream users are only able to see the tip of the iceberg of what DeFi can offer, such as Coinbase Wallet, and the most powerful tools remain locked within the enthusiast community due to their complexity,” said Maxim Savelyev, CEO of Web3 consulting firm Empathy Consulting.
By analyzing users' portfolios, behavior, token trends, and blockbuster transactions, AI can provide tailored advice to users, helping them make informed decisions without deep technical knowledge. One example is Numerai, a decentralized hedge fund that uses AI and machine learning to crowdsource predictions from data scientists and use them to trade on the stock market. This approach demonstrates the potential of AI to drive investment strategies in a decentralized way. Additionally, AI-powered platforms such as AlphaPoint are leveraging AI to analyze on-chain data and predict future DeFi asset prices to help users make informed investment decisions.
Fraud prevention and auditing
According to Chainalysis, security is the biggest concern in DeFi, with 76 hacks occurring in 2023, totaling losses of around $1.1 billion. AI can detect anomalies and suspicious activity in real time, reducing fraud and maintaining trust in decentralized platforms. Lars Nyman of cloud provider CUDO Compute emphasizes that “AI can enhance security through anomaly detection and improve the functionality of smart contracts through predictive analytics.” AI also assists in the creation of smart contracts, a task previously only performed by technical personnel. By verifying smart contracts and identifying potential vulnerabilities, AI ensures higher security standards and increases trust in blockchain systems.
By doing so, decentralized exchange Uniswap
Uniswap
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Access to blockchain data
Blockchain's transparency is one of its greatest strengths, but the sheer volume of data can make it difficult to derive meaningful insights. AI can fill this gap by processing and summarizing large datasets, making blockchain data more accessible and smart contract execution more efficient. Adnan Masood of solutions provider UST highlights the importance of a hybrid approach, where AI processes data off-chain while maintaining on-chain integrity. By transforming raw blockchain data into understandable insights, AI democratizes access to information and empowers users to make better decisions.
One example is Chainalysis, which uses AI to monitor and analyze blockchain transactions to detect suspicious activity, making the data easier to analyze and improve security. Fetch.ai, another blockchain protocol, aims to integrate AI to optimize transaction timing and processing, reducing congestion.
Improving tools for blockchain developers
AI can also improve the quality of life for blockchain developers by offering solutions like low-code and Copilot. These tools can simplify the development process, reduce the need for extensive coding knowledge, and accelerate project timelines. One example is multi-chain protocol Guru Network, which offers a low-code solution that integrates traditional business process automation engines with AI snippets to streamline the creation of Web3 and AI applications. Developers can use pre-built components and templates, and GPT agents provide real-time, context-aware consulting from documentation and code repositories.
AI can help generate smart contracts, debug code, and predict potential issues before they occur. This not only speeds up development, but also reduces the room for error, allowing developers to focus on the more strategic and innovative aspects of their projects. AI can also help with the creation of smart contracts, making the development process more accessible to non-technical practitioners.
For example, the open-source framework OpenZeppelin uses AI to audit smart contracts to identify bugs and vulnerabilities before they are deployed. This proactive approach ensures that smart contracts are secure and function as intended, reducing the chance of errors and abuse. Similarly, Ocean Protocol uses AI to develop a deterministic model that aligns with the deterministic nature of blockchain, enhancing its overall development process.
AI is changing the DeFi landscape, bridging the gap between complex financial technology and everyday users. By strengthening infrastructure, improving user experience, providing robust security measures, and supporting developers, DeFi becomes more accessible and efficient.
As these technologies continue to evolve, we can expect to see AI play a more influential role in taking DeFi mainstream. By leveraging the analytical power of AI and its ability to process large datasets, DeFi platforms can provide safer, more efficient, and more user-friendly financial services, ultimately democratizing finance and empowering users around the world.
