It’s no secret that the emergence of ChatGPT in November 2021 caused a craze about the role of AI. Coincidentally, we’ve also witnessed a surge in the popularity of crypto projects that promise to leverage AI in their offerings. However, not all AI claims are created equal. Some projects seem to be jumping on the AI hype bandwagon and presenting roadmaps that may be too good to be true.
For those of you who are genuinely interested in understanding how AI can truly benefit the crypto industry, this blog is for you. We’ll delve deeper into the actual applications of AI in crypto, separate the hype from the reality, and explore the opportunities and challenges that lie ahead.
The Basics: Understanding Speculation in Crypto Projects
As of writing this blog, most crypto project tokens are speculative assets. When you buy a token, you rarely intend to use it. Instead, you buy and hold onto it, hoping that the price will increase in the future. AI projects in crypto can also be speculative in the sense that they may promise token holders a return if they hold onto their tokens. The idea is that a third party will eventually need the token and be willing to buy it at a higher price. However, such promises are often based on speculation and may not be grounded in reality. Let’s take a look at some examples.
A Classic Example of AI Hype in Crypto
Let’s take a classic example to illustrate how some AI projects in crypto can be highly speculative. A project might first claim that Web 2.0 is collecting users’ data for free, but in reality, that data is valuable. They may then claim to have built a data collection system that requires developers to buy their native token if they want access to users’ data. The tokens would be distributed to users who are willing to sell their data, with a portion going to the protocol.
While this sounds promising, there are too many “ifs” involved. For instance, the project is banking on developers building on their protocol, users of the app being willing to sell their data, and enough revenue being generated to sustain the project. The reality is that the success of such a project is highly uncertain, and investors may be better off buying the tokens at a discount and waiting for the hype to reach its peak before selling them.
AI Meme Tokens
AI meme tokens have had their fair share of success and criticism in the crypto market. While some early investors have seen significant profits, others view them as purely speculative with no real-world utility. The reality is that AI meme tokens should be treated similarly to other meme tokens. If you’re interested in that sort of thing, well, that’s up to you. Just be aware of the risks involved and approach with caution.
AI Trading Bots
It is worth noting that in recent years, there has been a trend of trading bots being marketed as using artificial intelligence (AI) to make more sophisticated trading decisions. While it is true that some bots may incorporate machine learning algorithms or other forms of AI, it is important to approach these claims with a healthy dose of skepticism. Just because a bot claims to use AI does not necessarily mean it is more effective or reliable than other bots. Ultimately, the decision to use a trading bot is up to the individual trader, but it is important to be aware of the potential risks and limitations.
Current Effective Use Cases of AI in Crypto
If you want to see projects that use AI and have a lot of people actually paying for it, look for projects that generate real revenue and don’t rely on dumping their tokens to fund development.
1. Data Analysis
One popular area where AI is being effectively used in the crypto industry is data analytics. Traders are increasingly looking for tools that can collect and analyze data from the blockchain, and filter out the relevant information that can inform their trading decisions. These tools can also send alerts and provide sorting features so traders can easily see which wallets belong to smart traders or insiders, and follow them. The ability to quickly and accurately process vast amounts of data is crucial for traders looking to gain an edge in the fast-paced world of crypto trading. Some good examples that are already gaining traction with paying users are Nansen and CryptoQuant, which offer powerful data analytics tools that enable traders to make more informed decisions based on real-time market data.
2. Fraud and Security Risk Detection
Another important use case for AI in crypto is fraud and security risk detection. With the rise of DeFi and decentralized exchanges, there is a greater need for effective security measures to protect user funds. AI can be used to identify potential security vulnerabilities, detect fraudulent activities, and prevent hacks and other security breaches. Some blockchain projects are already utilizing AI for these purposes, with Chainanalysis being a notable example of this.
Summary
Overall, there are several real-world use cases for AI in the crypto industry beyond pure speculation and hype. These use cases have the potential to bring real value to the market and improve the efficiency and security of the blockchain ecosystem.
