Key Findings

  1. 88% of AI agent tokens are dead.
  2. The average lifespan of an AI agent token is17 days.
  3. 75% of AI agent traders are losing money.
  4. AI16Z has an ROI of just 150%, with 72% of its portfolio comprising dead tokens.
Key Findings of report Nearly 90% of AI Agent Tokens are Dead

Methodology

We started by crawling 976 AI agent tokens from Dexscreener. About 90% of collected tokens are launched on Solana, the others are on Base. 

1/ To determine the percentage of dead tokens and their lifespan:

We classified a token as “dead” if it met any of the following criteria: a price drop of over 90% from its all-time high (ATH) or liquidity under $50K.

The lifespan is calculated from the token’s creation date to the date it became dead. Price and liquidity data were sourced from Dune Analytics.

2/ For the portfolio ROI comparison between AI16z and top-tier VCs:

  • We obtained the PnL of the AI16z wallet (AM84n1iLdxgVTAyENBcLdjXoyvjentTbu5Q6EpKV1PeG) from Dune Analytics. Note that we only included investments worth higher than $100K. 
  • ROI data for top-tier VCs was sourced from ChainBroker.

3/ To measure the impact of aiXBT mentions on token price:

We gathered sentiment, tweets, and token data from SentientMarket and calculated the 1-day price change before and after each mention.

Data is collected from January 2nd to January 14th, 2025.

The alarming fact: Nearly 90% of AI Agent Tokens are Dead

The numbers speak for themselves when it comes to the performance of AI agent tokens. A shocking 88% of AI agent tokens are dead, with the average lifespan of these tokens barely reaching 17 days. This highlights the high-risk, high-reward nature of investing in this space, where many projects fail to sustain investor interest.

Additionally, 75% of traders involved in AI agent tokens are at a loss, underscoring the volatility and uncertainty that surrounds these investments. The hype around AI agents might be enticing, but the majority of market participants are not seeing the returns they anticipated.

Return on Investment: The Long Road Ahead for AI16z to Beat A16z

AI16z, an AI-operated DAO, has posted a 150% ROI, which, while positive, is considered mediocre compared to A16z’s remarkable 980% ROI. This significant gap highlights the challenges AI16z faces in competing with more established firms like A16z, which has built a track record of high-performing investments.

Return on investments of AI16z and A16z

Additionally, 72% of AI16z’s portfolio consists of dead projects, reflecting the high-risk nature of AI-driven investments. 

These raise key questions about the ability of AI to make sound investment decisions: Can AI truly match the judgment and intuition of human investors with years of experience? Is AI capable of predicting long-term success in a rapidly evolving market, or is it still too early to trust it with crucial investment decisions? The road ahead is long, and AI16z must overcome these challenges to outperform A16Z, requiring careful management, innovation, and sustained growth.

How aiXBT mentions are moving token price

aiXBT, an AI agent influencer, plays a significant role in shaping market sentiment through its evaluations and opinions on crypto projects, particularly among low-cap tokens (those with a market cap below 20M). In these cases, positive mentions can trigger a price surge of 12.54%, while negative mentions cause prices to plummet by 48.43%. This stark contrast highlights the powerful role AI agents like aiXBT play in shaping market movements, particularly within vulnerable, smaller projects.

How aiXBT mentions are moving token price

A prime example of this is SNAI (SwarmnodeAI). When aiXBT first gave a positive mention at 5 AM on December 26, 2024, the token was trading sideways between 0.01 and 0.007. By 1 PM the same day, it had surged to 0.02.

aixbt shill SNAI
aiXBT shill SNAI
SNAI price rises after aixbt mention
SNAI price rises after aixbt mention

The Future of AI Agents

Although most AI agent tokens have failed so far, the long-term potential of AI agents in simplifying how users interact with Web3 is undeniable. To realize this potential, AI agent applications must expand into areas like DeFAI, AI Robotics, and Trading Agents/Investment DAOs. 

However, it’s important to acknowledge the challenges: many AI agents still lack significant use cases in Web3. AI agents need to be truly effective and provide a user-friendly experience, with a strong focus on simplifying complex tasks for users in Web3. Nonetheless, this is just the beginning of AI and blockchain integration, and the development potential remains vast. The key now is how developers effectively deploy these models.

Final Thoughts

The AI agent token market shows great promise, but the risks are considerable. With 88% of tokens failing and most traders facing losses, the market’s volatility is clear. To achieve long-term success, AI agents must venture into key areas like DeFAI, DAOs, and AI Gaming, while delivering user-friendly and effective experiences. Investors should approach with caution, as the market is still evolving, and the main challenge lies in how developers implement these models. While there is potential for significant rewards, navigating the risks is crucial for anyone involved.