DeFi allows borderless transactions, bankless lending and borrowing, and earning opportunities beyond stocks and bonds 24/7, year-round.
It monetises blockchains, giving them a practical purpose. You can swap, trade, farm, stake, and restake to earn massive income across protocols. You control your money your way.
DeFi screams financial inclusivity and freedom. But DeFi is COMPLEX and DAUNTING.
It requires you to be a nerd who can set up a decentralised wallet, manage private keys, sort gas fees, find a suitable DeFi opportunity at the right time, on the right protocol, on the right chain to be able to start earning. All this while making sure they don’t fall prey to any scam!
DeFi has a high learning curve and many barriers to entry, which is one of the main reasons it has never achieved the adoption it deserves or been fully utilised.
AI can help DeFi enhance its capabilities and manage its complexities. AI-led DeFi, or DeFAI, is the new age DeFi, taking the crypto world by storm. Picture an AI buddy, swapping, staking, and finding the best trading strategy for you on command. That’s DeFAI for you.
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What is DeFAI?
The term DeFAI is the combination of two acronyms–Decentralised finance (DeFi) and Artificial Intelligence (AI). AI, when integrated with DeFi, can help simplify complex interfaces and promote user participation by removing friction.
For instance, a regular DeFi transaction involves setting up wallets, navigating protocols, and searching for the best offer/opportunity. Instead, you can simply type a command as you do to ChatGPT: “ Swap $100 ETH for SOL.” And voila, the AI agent or DeFAI protocol does it for you. Hey Anon, Bankr Bot, Griffain, etc., are some of the popular DeFAI protocols, making DeFi simpler, friendlier, and more accessible for the everyday user.
Look at this screenshot of a conversation between a user and Bankr Bot. The user gives the commands on Twitter, and Bankr Bot instantly facilitates the transactions using AI-powered DeFi.
Source: X | Conversation between an AI Bot and a user
To put it succinctly, DeFAI is the next best iteration of DeFi–AI-enhanced DeFi–that even your grandma can use. (a bit of hyperbole but definitely feasible)
Several kinds of DeFAI projects are doing the rounds in the first wave of DeFAI. These protocols can be classified into three distinct categories: abstraction layers, AI-powered dApps, and autonomous trading agents.
Source: X | Top DeFAI Apps
The Evolution of DeFi and AI Integration
Both AI and DeFi have distinct histories. The DeFi AI integration via DeFAI will evoke a shared chapter in which intelligent, automated financial systems reign supreme.
Early Developments in DeFi
Decentralised finance took shape in the closed quarters of the Ethereum community. While Ethereum’s smart contracts laid the infrastructure for DeFi development in 2015, MakerDAO became the first protocol to launch a stablecoin (DAI) in 2017. The 2020 Summer became a time of explosive growth for DeFi, with protocols like Aave, UniSwap, and Compound getting birthed.
Today, the DeFi sector manages billions of assets (Ethereum is the biggest TVL holder). It comprises decentralised offerings such as trading, lending and borrowing, staking, swapping, yield farming, liquidity mining, etc. It has added new functionalities such as Liquid staking, staking, liquid restaking, and cross-chain interoperability.
However, DeFi continues to face challenges such as hacks, regulatory scrutiny, and complex and difficult UX. Together, these ills prevent DeFi from becoming the formidable force it deserves to be in global finance.
Advances in Artificial Intelligence
Artificial Intelligence isn’t a recent technology. Its origin goes back to the 1940s when McCulloch and Pitts created artificial neurons. Alan Turing built machine intelligence in 1950, and in 1956, John McCarthy coined the term artificial intelligence.
Earlier, AI was based on rule-based systems, but between the 1970s and 1990s, improved algorithms, big data, and machine learning advancements completely changed the face of AI. AI was used in high-frequency trading (HFT), fraud detection, and risk assessment models. Deep learning arrived on the scene in the 2010s.
AI powers intelligent automation, predictive analytics, neural networks, and autonomous systems in healthcare, agriculture, finance, medical diagnostics, and other fields. DeFAI is a breakthrough use case of AI in blockchain, but it isn’t the only one. AI and blockchain synergies can complement each other in never-seen-before ways.
Benefits of DeFAI
An X user calls DeFAI a ‘simplify everything’ spell. However, beyond that, AI agents and DeFAI protocols can handle vast amounts of data, analyse patterns, conduct safety drills, and perform human-like acts to alleviate most of the challenges DeFi faces today.
Source X: An X user Tony0x.eth calls DeFAI the final evolution of Web3
Enhanced Risk Management
There’s a lot AI can do to improve risk management in DeFi. For instance, it can improve DeFi security via machine learning algorithms that detect fraud. AI-driven risk assessments help identify patterns in attacks or user activities to reduce vulnerabilities and identify bugs to enhance protocol security.
Gauntlet uses AI-driven simulations to help reduce market risk and build capital efficiency for protocols like Aave and UniSwap. Mastercard acquired CipherTrace, which uses AI-powered blockchain analytics to detect fraud and illicit activities and follow compliance.
Automation and Efficiency
DeFi has been largely a do-it-yourself venture for users. Yes, you could use some protocols like yearn.finance to aggregate opportunities or CoW Protocol to get the best pricing across liquidity pools. But, navigating DeFi remained a cumbersome task. AI-powered DeFi automation can help automate trading, portfolio rebalancing, and loan approvals.
Abstraction layer projects like Griffain use Natural language processing (NLP) to simplify smart contract interactions and allow users to perform tasks such as launching memecoins, automating tasks, and conducting criteria-led airdrops.
Olas Network can build autonomous DeFi agents that can take care of your trading, lending, and AI-powered staking. Numerai Hedge Fund uses AI to sift through financial data to provide automated DeFi strategies.
Personalised Financial Services
Binance calls DeFAI your DeFi co-pilot, meaning DeFAI agents can perform trades, manage risks, identify market opportunities, and optimise yields on your behalf. Many DeFAI projects, such as Singularity DAO and Harvest Finance, can personalise their offerings today to help users maximise returns and auto-invest in high-yield DeFi opportunities.
Tokenisation of AI services
Have you heard about $GOAT–the millionaire AI agent with a market cap of $900 million? The AI agent token has achieved this success autonomously without any customer service or trading algorithms by setting up its own religion.
$GOAT is a bubble token. However, it opens up the potential to tokenise AI services and AI-driven tokenisation. These AI services tokens would be capable of attracting capital, demonstrating credibility, and autonomously catering to the demand as it arrives. The opportunities that lie are infinite.
Decentralised data marketplaces
Recently, Aura, the platform that tests and validates on-chain AI models, completed a successful seed financing round of $5.5 million. This feat is a key milestone towards having fully on-chain data marketplaces. On-chain data marketplaces can solve the problems the on-chain AI agent industry is facing, including limited monetisation opportunities, complexity in model selection, and fragmented model discovery.
The broader AI industry can also leverage the decentralisation benefits and remove bias and fragmentation clearly seen in current chatbots and data models like ChatGPT, DeepSeek, Grok, etc. These decentralised marketplaces can allow real-time analytics, AI-driven personalised recommendations, and better price discovery while selecting the right AI model.
High security
Blockchain is fundamentally a decentralised database that requires tech like AI and ML to analyse large amounts of data, identify patterns, detect anomalies, and present usable insights. Deep learning and AI-led fraud management systems can recognise patterns from past attacks and prevent any fraud, theft, or phishing attacks easily. AI-powered fraud management systems learn and adapt to improve their decision-making and provide better responses to hacks.
Source: Cointelegraph | How AI helps in strengthening security
Cybercrime is one area where AI can prove a vital force as a fraud management system capable of integrating with biometric authentication, identity verification, and other kinds of security systems.
For DeFi, especially, AI becomes crucial with its algorithms capable of detecting online fraud in financial transactions and flagging suspicious activities. DeepMind has collaborated with Ethereum and research is underway to integrate AI-driven code verification for detecting vulnerabilities in smart contracts. Openseppelin Defender uses AI monitoring to secure smart contracts.
Challenges & Considerations
Despite all the promises, potential challenges remain in the integration of Ai with DeFi:
Technical Complexities
AI models cannot do without advanced computing power and blockchain scalability. Both blockchain and AI are resource-intensive. This can be costly and not as seamless as it looks in theory. Most DeFAI projects are still in their early stages, and still need to show whether they can achieve product-market fit and sustain in the tough crypto landscape.
Security and Privacy Concerns
Data security is of paramount importance when it comes to AI-led management systems. Since AI functions on decentralised infrastructure without human intervention, there’s room for bias and AI hallucinations that could lead to significant security risks. Most AI projects have been criticised for lack of accountability and for using data without consent, which can again raise manifold privacy issues given the disintermediated nature of DeFi.
Trusted Execution Environments (TEEs) can help agents to operate securely with minimal privacy and security risks.
Regulatory and Ethical Issues
Most of the time, DeFAI projects do not fully disclose the risks and terms of use. There might be chances that the protocol has unauthorised access to your personal information without your knowledge. Generative AI is trained on data derived from PII (Personally Identifiable Information), which is unethical. With no clear guidelines and regulations in place, users may be left at the mercy of the protocols and may incur losses and their right to privacy.
Current Applications and Projects
Autonomous Trading Agents
These trading agents help to extract information from the ever-changing markets and provide the best alpha, automate trades, and optimise your portfolio. These agents reason against the predetermined objectives, identify patterns and plan better trades over time without the interference of the owners.
Bankr Bot: This DeFAI project is stirring every corner of the DeFi industry with incredible features like Grok integration and social limit orders. Users can buy and place limit orders on their social feed or in the Bankr private terminal and Bankr does the job.
Go HODL: A mobile app that uses AI to improve the trading experience on Sonic Labs.
Hey Anon: The DeFAI project has had several collaborations with protocols and can execute swaps, bridge assets, and manage your DeFi strategies.
AI-Powered Lending Platforms
AI automates repetitive tasks, streamlines processes like loan approvals and allows faster transactions for a great user experience. Moreover, with its ability to digest large chunks of data and push out analysis and patterns, AI can take away credit platforms from fraud and advanced threats like flash loan attacks or wash trading. Personalised portfolio management, better price discovery, and frictionless onboarding are other virtues credit platforms can enjoy.
Aave uses AI to enhance the platform's security and provide advanced lending and borrowing services. The AI algorithms help analyse market conditions and adjust interest rates to ensure users get competitive rates. UniSwap uses AI algorithms to analyse trading patterns and optimise the distribution of tokens within the liquidity pools to maximise liquidity and stability.
Infrastructure projects
These projects serve the infrastructural needs of other AI-led projects. Projects like Orbit add on-chain functionality to 117 chains and 200 protocols. Almanak provides institutional-grade AI agents to users and employs TEEs to ensure top-level security and privacy.
Vistara Labs is a one-click scalable DA (data availability) stack of dApps that allows real-time market intelligence and trustless storage for AI agents, DeFAI projects, etc. The project has backing from Celestia and is incubated under Binance Labs.
Source: X
Here’s a worth-reading article by Defi0xJeff on DeFAI agents and protocols. Crypto.com does a deep dive into a few current DeFAI projects in this piece.
Future Prospects of DeFAI
VanEck calls DeFAI the next big crypto narrative, with an estimated 1 million AI-agent tokens to be launched in 2025 alone. The current DeFAI scene is traversing from mostly memecoins pretending to be AI agent tokens to protocols simplifying user interactions, managing portfolios, and powering dApps.
The potential of AI teaming up with DeFi is unfathomable. DeFAI holds the promise of making crypto an everyday reality. Think of self-optimising DeFi ecosystems, AI-powered hedge funds, and automated lending and borrowing platforms. AI agents are reshaping Web3 by bringing automation, intelligence, and optimisation to DeFi.
As the DeFAI ecosystem matures, traditional players will throng the Web3 scene to leverage AI-led on-chain functionalities. We witnessed the migration first with ETFs and tokenisation. 2025 may turn out to be the ‘DeFAI Summer’. What do you say?
