ChainGPT Founder Expects AI Agent Adoption to Transform Crypto

Industry experts expect AI agents to benefit the crypto market and blockchain ecosystems extensively. These autonomous systems can improve investment strategies and execute trades more effectively while detecting and mitigating threats.

BeInCrypto spoke with ChainGPT Founder Ilan Rakhmanov about the industry areas AI agents will most profoundly affect and the risks that need to be addressed for the safe deployment of these emerging technologies.  

The AI Agents Market is Surging

AI agents represent a fundamental shift in the evolution of blockchain technology and the cryptocurrency market. These autonomous systems make decisions and perform tasks independently.

They can enhance intelligence, adaptability, and fairness in financial mechanisms. Unlike AI bots, AI agents adapt to tasks and handle multi-step processes with goal-oriented autonomy. 

“We believe that, in 2025, we may see the first AI agents “join the workforce” and materially change the output of companies. We continue to believe that iteratively putting great tools in the hands of people leads to great, broadly-distributed outcomes,” wrote OpenAI CEO Sam Altman in a blog post earlier this month.

In a recent report, asset manager Franklin Templeton also underscored the merits associated with AI agents. 

“We can envision a future where Al agents revolutionize content generation on social media and play an integral role across various industries and platforms. Like today’s human influencers, these agents could launch their own brands, products, music, movies, and more, driving significant economic value to their ecosystems,” it read. 

According to CoinGecko, AI agents took off as a market category shortly after Truth Terminal’s GOAT token launched on Solana last October. Currently, AI agent tokens have a market cap of more than $12 billion.

This is remarkable growth considering the fact that the majority of this market segment didn’t exist a year ago.

Currently, over 150 crypto tokens used for AI Agents are listed on CoinMarketCap. This number represents the surge in AI agent-related projects and their promise for the sector’s future.

AiXBT, ai16z, Virtuals Protocol, and Zerebro are among other notable examples. AI platforms like ChainGPT, Dall-E, and Midjourney are also driving innovation in the sector.

Given this dynamic growth, it’s safe to say that AI agents will continue to drive change in the dynamics of AI and crypto-related industries as adoption accelerates.

Changes in the way Crypto Markets Function

While last year saw these autonomous systems primarily used for content creation and social media engagement to generate attention, AI agents in crypto trading might be a defining trend in 2025. 

Though AI agents share some functionalities with AI trading bots, they represent a more advanced level of technology.

For instance, a defining characteristic of crypto AI agents is their inherent autonomy. This characteristic allows them to operate independently. AI agents can continuously monitor market conditions and execute actions based on pre-defined parameters without requiring constant user intervention. 

This level of autonomy distinguishes crypto AI agents from traditional trading bots. So, they can effectively function as self-reliant assistants for managing cryptocurrency portfolios and executing trading strategies.

“AI-powered trading bots are changing the way crypto markets function. They offer fast, precise, and data-driven decision-making. They can analyze market trends, execute trades, and manage portfolios far more efficiently than humans while also helping to reduce emotional decision-making,” Rakhmanov told BeInCrypto. 

A key feature distinguishing these tools is their ability to learn from historical market data and continuously refine their predictive models. 

This machine learning capability enables automated trading systems to operate continuously, identifying and capitalizing on trading opportunities that may not be instantly apparent to human traders due to limitations in time and attention scope.

Also, the capabilities of AI agents spill over to other areas of the cryptocurrency ecosystem, such as DeFi protocols.

Simplifying DeFi Protocols

AI agents’ ability to carry out tasks at rapid speeds makes them a critical tool in the decentralized finance (DeFi) sector. 

“AI has become a household name, and its impact is now reaching the world of decentralized finance (DeFi). By automating and optimizing processes, AI is making DeFi smarter and more efficient,” said Rakhmanov.

Crypto AI agents operate based on a three-step process: data collection, data analysis, and automated execution. In the first step, the AI agent collects substantial data from various sources, including market trends, blockchain transactions, and DeFi statistics. 

This data is then analyzed using advanced machine learning algorithms and predictive analytics techniques to identify patterns and determine the optimal course of action. 

Finally, based on this analysis, the AI agent autonomously executes the determined actions, such as placing trades, moving funds between wallets, or triggering the execution of smart contracts. 

“AI can improve risk assessment in lending protocols by evaluating borrowers more accurately, leading to better decision-making. It can also make liquidity pools work smarter by predicting user behavior and market trends, reducing waste and inefficiencies. Additionally, AI can enable smart contracts to adapt to real-world changes automatically, without needing human input,” Rakhmanov added.

By doing so, these AI agents greatly facilitate DeFi interaction.

“These innovations are making DeFi systems not only more effective but also more accessible and user-friendly, paving the way for broader adoption by people from all walks of life.”

Beyond their appeal to institutional investors or professional traders, AI agents can be leveraged to attract a wider audience to Web3 technologies in general.

AI Agents Increase Accessibility for Users

Autonomous agents could make the industry more accessible by fundamentally breaking down complex mechanisms and automatically executing them. 

“AI Agents can simplify interactions by providing real-time insights, educational tools, and personalized guidance tailored to each user’s needs. For instance, AI-powered assistants could explain complex DeFi protocols in plain language or recommend optimal investment strategies,” Rakhmanov told BeInCrypto.

They can be vital tools for inexperienced users because they can adapt to individual use cases.

“By prioritizing user-centric design and leveraging AI, the cryptocurrency ecosystem can attract a broader audience and lower barriers to entry,” he added. 

AI agents can also make the onboarding process easy for new users. If they were to spread globally, such systems could incentivize widespread adoption, according to Rakhmanov.

“The convergence of AI and blockchain could democratize access to financial systems, empower individuals with tailored tools, and enhance financial inclusion globally. Economically, AI-driven automation could reduce inefficiencies, lower transaction costs, and unlock new markets. Socially, decentralized AI systems like Decentralized Artificial Superintelligence (DASI) could promote fairness and reduce bias in financial decision-making.”

Leveraging Security and Scalability

AI agents have a completely different and more nuanced use case in terms of blockchain security. They can enhance the security and scalability of the entire blockchain network, safeguarding both experienced and inexperienced users from associated risks.

The security framework ensures the agent operates safely, protecting user data, private keys, and executed transactions.

Crypto AI agents incorporate thorough security measures, including encryption and multi-layer authentication, to ensure the security and privacy of user data.

“On the security front, they can detect and mitigate threats in real-time by analyzing patterns and identifying anomalies, reducing vulnerabilities to hacks and fraud,” Rakhmanov explained. 

A blockchain integration layer connects the agent to blockchain networks, enabling it to interact with smart contracts, wallets, and DApps. It bridges the agent and the blockchain, ensuring the agent can operate across multiple ecosystems.

The blockchain integration layer enables the agent to function seamlessly across multiple blockchains. This layer acts as a bridge connecting the agent to these networks and facilitating interoperability.

“For scalability, AI Agents can optimize resource allocation, improve consensus mechanisms, and streamline data validation processes,” he added. 

However, there are also associated security risks that come with AI agent integration. Given their autonomous nature, crypto AI agents are susceptible to cyberattacks.

Potential vulnerabilities include smart contract exploits, private key compromises, and the possibility of market manipulation.

Therefore, a strong security framework is essential.

Blockchain network congestion, characterized by delays and increased transaction fees, can hinder the performance of crypto AI agents. This issue is common on blockchains like Ethereum during periods of high activity.

Integrating crypto AI agents across different blockchains can also be challenging. This is due to each network’s varying protocols and decentralized infrastructures.

Other Associated Challenges With AI Agents

The benefits and potential of AI agents are evident. Yet, the technology is in its early stages, and there are more limitations to consider.

While the autonomous capabilities of AI agents offer significant advantages in terms of efficiency and responsiveness, they also raise important questions regarding accountability and risk management. 

“These advancements also pose risks, including job displacement and ethical concerns around data privacy,” Rakhmanov told BeInCrypto.

An autonomous AI agent’s actions can sometimes lead to unintended consequences, such as market instability. Determining responsibility and establishing accountability mechanisms in such situations can be challenging.

“As these bots become more common, they could make the market more volatile since they react instantly to price changes. To ensure everyone benefits, we’ll need to strike a balance between embracing innovation and putting in place thoughtful regulations,” he added.

The performance of AI agents is highly dependent on the quality of real-time data. Challenges such as inaccuracies in data provided by blockchain oracles and potential errors within smart contracts can significantly impact their decision-making capabilities.

“Decentralization helps mitigate some risks by removing single points of failure, but robust governance, transparency, and ethical AI design are essential to minimize unintended consequences,” Rakhmanov said.

Furthermore, constantly changing international regulations surrounding blockchain and AI present significant challenges for developing and deploying crypto AI agents. 

This context raises important questions regarding AI agents’ legal and regulatory compliance, particularly those engaged in financial operations such as trading and DeFi interactions.

“Proactive collaboration among stakeholders, including regulators, technologists, and communities, will be crucial to ensure equitable benefits for all.”

Given that these agents are only the tip of the artificial intelligence iceberg, addressing these challenges early on will prove vital for the effective and responsible development of these emerging technologies.