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AI and Crypto: How is AI Being Used in the Cryptocurrency Industry?

AI is marching fast into every sphere on the planet, and crypto is no exception. Here are the latest developments in the merging of crypto and AI.

In this article...

  • AI is creeping into every part of life
  • There are now many ways that AI works alongside crypto
  • Is this good or bad? We break it down in this article.
ai in crypto

How is AI reshaping the way we trade, invest, and interact with digital currencies?

Whether we like it or not, the integration of artificial intelligence into our lives is happening, and fast. The cryptocurrency ecosystem is no exception to this penetration by artificial intelligence.

AIs process vast amounts of data quickly and with ever improving accuracy — something human traders can’t always do. Why use a mere fallible human brain when an AI can do it?

There are some well known instances where AI isn’t always accurate, of course, so be aware of that. Sometimes, we meat suits are better, for now.

AI in the crypto industry

AI-powered trading bots are revolutionising crypto trading. These tools analyse historical data, market patterns, and real-time news to execute trades with precision in line with a predefined investment strategy.

For example, an AI bot may have the ability to spot a breakout trend for a coin before most human traders, giving users a competitive edge.

Personalised crypto experiences

AI can tailor your crypto journey to the way you see the crypto world. It could learn your trading habits and suggest strategies to possibly maximise investment returns.

AI can also crowdsource market predictions from data scientists worldwide. is a hedge fund that uses AI to do this very thing.

There are bots that do trading for you, like and . Other bots can be set to detect when Ethereum dips below a certain value, and automatically execute a buy order.

uses AI to analyse social media data and provide insights into cryptocurrency sentiment and market trends.

For example, an AI can scope X for mentions of a specific coin, and determine if the overall public sentiment is positive or negative. This sentiment is then used to predict short term price changes.

AI democratising data

Massive computational power is needed for artificial intelligence workloads. Data centres are centralised facilities packed with high-performance servers, GPUs (graphics processing units), and cooling systems. They require huge investments, specialised infrastructure, and long lead times for deployment.

Startups or smaller players can’t afford the upfront costs for access to hardware like cutting-edge GPUs. With AI-driven decentralisation, this could change.

Now, smaller players can tap into a global network of idle computers, a "sharing economy" for computing power, where anyone can contribute and earn money by leaving their device on overnight.

Instead of relying on a few giant data centres owned by big tech companies, AI workloads could be distributed across a network of everyday devices. This could be your laptop, your neighbor’s gaming PC, or even your grandma’s desktop.

Crypto and computing power

People who offer up their idle computing power become part of a decentralised system, earning rewards (often in crypto) for their contribution.

AI developers and startups can rent this collective power at a lower cost than building or leasing traditional data centre space.

Projects like (Artificial Superintelligence Alliance, involving ) are pushing this vision forward.

The rewards need to be worth it for participants. Leaving your computer on all night might earn you a few bucks, but it has to outweigh the electricity bill. If projects like ASI and Render crack these issues, they could make AI computing as accessible as any other service a startup uses. It’s early days, but this shift in the way AI and crypto are used together could redefine how we think about data centers altogether.

Improved protection

Machine learning models are used to help detect suspicious activity — like hacking attempts or fraudulent transactions — faster than traditional methods.

uses machine learning to analyse blockchain transactions and detect illicit activity, such as money laundering and fraud.

provides blockchain analytics and compliance solutions, using AI to identify and mitigate risks associated with cryptocurrency transactions.

Challenges to watch

Of course, AI-powered crypto does have some curveballs. Over-reliance on algorithms can lead to if the market behaves unpredictably. Plus, the technology requires significant computing power and expertise.

When AI-driven trading algorithms execute disastrously, who shoulders the blame: the developer, the user, or the inherently unpredictable AI?

AI hallucinations, where the system fabricates information leading to flawed investment decisions, could trigger cascading financial losses, with no clear recourse. Furthermore, the risk of a compromised AI, manipulated by malicious actors to drain crypto wallets or destabilise markets, looms large.

These all have to be overcome for AI to be truly relied upon.

The Future of AI and crypto

In the future, we could see fully autonomous trading ecosystems, AI-driven stablecoins that adapt to economic conditions, or even blockchain networks that self-optimise using machine learning. For now, it’s clear that AI is set to play a starring role in the next chapter of cryptocurrency.

coinjar author, best crypto exchange
CoinJarCoinJar is one of the longest-running cryptocurrency exchanges in the world. Since 2013, we’ve helped hundreds of thousands of people worldwide to buy, sell and spend billions of dollars in Bitcoin, Ethereum and dozens of other cryptocurrencies.

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