In 2025, the integration of AI and cryptocurrency transformed from conceptual noise into practical architecture, with agent economy and decentralized AI infrastructure becoming industry hotspots. However, behind this wave of enthusiasm, a certain 'AI intelligent trading' project led to a 70% loss for investors due to technological fraud, while a certain 'decentralized AI computing power' project went to zero upon launch. As an analyst who has experienced three cycles of bull and bear markets, I have witnessed countless investors suffer significant losses due to blindly following AI cryptocurrency projects. Today, I will share a set of market-validated screening criteria to help you seize real opportunities in the AI cryptocurrency boom while avoiding 90% of the traps.
🔍 1. The real value and potential risks of the AI + cryptocurrency sector.
The essence of AI + cryptocurrency: a revolutionary breakthrough in technological integration.
The core logic of AI and cryptocurrency integration is to combine artificial intelligence technology with blockchain technology to create new application scenarios and business models. Compared to traditional cryptocurrency projects, AI + cryptocurrency has the following advantages:
Improve efficiency: AI algorithms can optimize on-chain transactions, smart contract execution, and data analysis, significantly enhancing blockchain network efficiency.
Enhance security: AI-driven security monitoring systems can detect anomalous transactions and potential attacks in real-time, improving network security.
Create new economic models: New application scenarios such as agent economy and AI-driven DeFi protocols bring incremental value to the industry.
Potential risk: 90% of AI cryptocurrency projects are 'pseudo-AI.'
Although the AI + cryptocurrency concept is hot, there are currently only a few projects in the market with real technical strength and practical application scenarios, less than 10%. The main risks include:
Technical fraud: The project claims to have core AI technology but cannot provide verifiable technical documents or open-source code. In 2025, a certain 'AI intelligent trading' project was exposed for technical fraud, resulting in a 70% loss for investors.
Conceptual hype: The project only uses the concept of 'AI + cryptocurrency' for packaging, lacking practical application scenarios and user demand. A certain 'decentralized AI computing power' project went to zero upon launch.
Team fraud: Core team members have fabricated resumes or used AI-generated fake photos. In 2024, a certain 'AI public chain' project collapsed due to team information fraud.
Liquidity trap: Token trading volumes are extremely low, making it impossible for investors to sell after buying, becoming 'bag holders.'
💡 2. Three screening criteria for quality AI + cryptocurrency projects.
Standard 1: Technical strength - in-depth verification of technical authenticity.
Core principle: Quality AI + cryptocurrency projects must actively disclose technical details and reject any vague statements like 'business secrets.'
Operational guidelines:
Require the project team to provide a technical white paper: The white paper should detail the principles of AI algorithms, technical architecture, and implementation plans. For example, a certain quality AI public chain project disclosed detailed technical documents of its consensus algorithm and smart contract execution mechanism.
Check the open-source status of the code: Use platforms like GitHub to view whether the project code is open-source, as well as the frequency of code updates and the number of contributors. Quality projects usually have active open-source communities and ongoing code contributions.
Verify AI technology patents: Check whether the project party has applied for relevant AI technology patents or has collaborations with well-known AI research institutions.
Danger signal:
The project only uses terms like 'AI' and 'machine learning' for packaging but cannot provide specific technical details.
Code is not updated for a long time, or there are only a few contributors.
The technical white paper is empty, lacking specific implementation plans.
Standard 2: Application scenarios - finding real demand support.
Core principle: Quality AI + cryptocurrency projects must have clear application scenarios and real user demand, rather than purely speculative hype.
Operational guidelines:
Analyze market demand: Does the project address pain points in the blockchain industry? For example, AI-driven on-chain data analysis tools can enhance transaction efficiency and security.
Check user data: Does the project have real user and transaction data? Quality projects typically have active communities and a continuously growing user base.
Evaluate the business model: Does the project have a clear profit model and sources of revenue? For example, AI computing power networks generate income by providing computing power services.
Danger signal:
The project party cannot clearly explain application scenarios and user demand.
The token economic model is unreasonable and lacks practical application scenarios.
The community's activity level is low, lacking real users and transaction data.
Standard 3: Team and investors - institutional endorsement is an important reference.
Core principle: Quality AI + cryptocurrency projects typically have experienced technical teams and investments from well-known institutions, which enhances the credibility of the projects to a certain extent.
Operational guidelines:
Verify team backgrounds: Do core team members have work experience in the AI or blockchain fields? Have they worked at well-known companies or research institutions?
Check investor information: Has the project received investments from well-known investment institutions (such as a16z and Sequoia Capital)? The professional judgment of investment institutions can serve as a reference.
Focus on partnerships: Does the project have collaborations with well-known AI companies or blockchain projects? For example, partnerships with organizations like OpenAI and Google AI.
Danger signal:
Team members are anonymous or have fabricated resumes.
Investor information is vague and unverifiable.
Partnerships are only 'strategic collaborations' lacking specific cooperation content.
📊 3. Comparing practical cases: quality projects vs problematic projects.
Dimensions
Quality project (a certain AI public chain)
Problematic project (a certain AI intelligent trading)
Technical strength
Code is open-source, technical white paper is detailed, with AI algorithm patents.
The technical white paper is empty, and the code has not been updated for a long time.
Application scenarios
Solving on-chain transaction efficiency issues with real users and transaction data.
Application scenarios are vague and lack real demand.
Team background
Core members come from Google AI and OpenAI, and their resumes are verifiable.
Team members are anonymous, and resumes are fabricated.
Investor
Received investments from renowned institutions like a16z and Sequoia Capital.
Investor information is vague and unverifiable.
Community activity level
Community is active, with ongoing technical discussions and user feedback.
The community is inactive, only discussing prices.
🛡️ 4. Practical strategies for ordinary investors.
Strategy 1: Start from mainstream platforms.
Prioritize AI + cryptocurrency projects that are listed on mainstream exchanges and have high trading volumes, as these projects typically undergo exchange review and present relatively lower risks. Avoid participating in projects issued by unknown platforms, especially those promising high returns as 'shitcoin projects.'
Strategy 2: Small-scale trial, gradually increase positions.
Initial investment should not exceed 5% of the total investment portfolio, and consider increasing holdings after the project has run for 1-2 cycles. AI + cryptocurrency projects typically have high technical risks, so it is advisable to choose projects with short lock-up periods and good liquidity.
Strategy 3: Focus on technology-driven projects.
Prioritize projects with core technology and practical application scenarios, such as AI-driven on-chain data analysis tools and agent economy platforms. Avoid investing in purely speculative projects lacking technical support.
Strategy 4: Use regulatory sandboxes as filters.
Focus on AI + cryptocurrency projects that have passed regulatory sandbox tests. These projects have undergone preliminary compliance reviews and can serve as investment references. For example, the Hong Kong Monetary Authority's Ensemble sandbox has approved multiple AI + cryptocurrency projects.
⚠️ 5. Danger signals for high-risk AI + cryptocurrency projects.
Promises of high returns and capital protection: There are no 'low-risk high returns' in finance; the returns of AI + cryptocurrency projects should be roughly equivalent to similar traditional projects. Projects promising 'daily returns of 1%-2%' are essentially Ponzi schemes with annualized rates as high as 3678%.
The team is anonymous or has a vague background: Core members of compliant projects need to publicly disclose their real names and resumes. In 2024, a certain 'AI public chain' project collapsed when it was confirmed that team members' photos were AI-generated.
Technical information cannot be verified: The project claims to have core AI technology but cannot provide verifiable technical documents or open-source code.
No clear regulatory filing: Our country explicitly prohibits illegal token issuance and financing activities; losses from participating in unlicensed AI + cryptocurrency projects must be borne by the investors themselves.
💭 6. My personal views and operational suggestions.
Viewpoint 1: AI + cryptocurrency is a long-term trend, but rational allocation is necessary.
I believe the AI + cryptocurrency sector is an important bridge connecting traditional AI and blockchain, and its long-term value is beyond doubt. However, the current market is still in its early stages, and 'mixed quality' is a significant feature. Ordinary investors should remain rational and avoid blindly chasing highs due to FOMO emotions.
Viewpoint 2: Technical strength is core; speculative hype is a trap.
The core value of AI + cryptocurrency projects lies in technical strength and application scenarios, not speculative hype. Those that only use terms like 'AI' and 'machine learning' for packaging but lack specific technical details are likely scams.
Viewpoint 3: Control positions and diversify risks.
My suggestion is: AI + cryptocurrency positions should not exceed 10% of total assets, with 60% allocated to quality projects with technical strength and institutional endorsement, 30% to potential projects with practical application scenarios, and 10% as flexible funds. Additionally, set a stop-loss line (e.g., exit immediately at a 20% loss) to avoid deep entrapment.
My operational strategy:
Base position: A certain AI public chain project accounts for 5% of the total position and is held for the long term.
Swing trading: AI-driven on-chain data analysis tools account for 3% of the total position, adjusting based on market sentiment.
Cash reserves: Retain 2% in stablecoins, waiting for extreme market conditions to buy at lows.
🔮 7. Summary and outlook.
The long-term value of the AI + cryptocurrency sector is beyond doubt, allowing ordinary investors to participate in cutting-edge technology investments with lower thresholds. However, the current market is still in its early stages, and 'mixed quality' is a significant feature. As investors, we should remember:
AI + cryptocurrency is a tool, fundamentally aimed at improving blockchain efficiency and security, not creating excessive returns.
Any high return promises that violate economic laws are traps.
In the AI + cryptocurrency field, 'surviving longer' is more important than 'making quick profits.'
Looking to the future, as technology matures and regulations improve, the AI + cryptocurrency sector will usher in healthier development. However, before that, ordinary investors need to remain rational and adhere to the three principles of 'technical strength, application scenarios, and team background' to seize real opportunities amid the AI cryptocurrency boom and avoid 90% of the traps.