Top 10 Use Cases of AI in Blockchain and Web3

Nov. 13, 2023.
7 min. read. 8 Interactions

AI in Blockchain: Unearthing real-world applications, from fraud detection to supply chain mastery. Dive into the future of blockchain and stay ahead of the curve with our in-depth exploration.

About the Writer


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Werner Vermaak, who is based in Cape Town, South Africa, has been a crypto editor and writer since 2017. He previously lived in Asia for 15 years and is passionate about the power of Web3.

Credit: Tesfu Assefa

There has been lots of noise about artificial intelligence this year. We have heard that it will forever change every aspect of our lives. The same things were previously said about blockchain technology, which uses decentralized networks to offer cryptocurrency incentives to participants. 

The most prominent AI companies are still centralized Web2 behemoths like OpenAI, Microsoft, and Google, but there is increasing confluence between machine learning and blockchain as the world of business becomes more and more automated. 

Here are a few of the best use cases for a marriage between artificial intelligence and blockchain in 2024 and beyond.

10. Supply Chain Optimization

A 2023 study revealed that 29% of small and mid-sized businesses lost over 15% in revenue due to supply chain disruptions, with an additional 31% reporting losses of 7-15%. An integrated system of AI and blockchain could transform supply chain and logistics operations by making it more efficient and transparent, and helping better decision-making. 

Cutting-edge AI algorithms can predict demand, manage inventory, and automate specific logistics processes. This reduces costs and the risk of fraud and counterfeiting within the supply chain. For context, global companies lose $500 billion per year due to counterfeit products. 

AI and blockchain in supply chain processes can reduce errors and optimize resource allocation. This helps companies do what they love most: save time and money.

9. Market Analysis and Automated Trading

The crypto market is notorious for volatility and can move faster than traders can react. In August 2023, cryptocurrency traders lost $1 billion in liquidations due to a sudden sell-off.

Can traders or artificial intelligence counter these liquidations? Absolutely. By analyzing market data, social sentiment, and news in real time, AI can make predictions about future market trends and help traders with more efficient trading, improved risk management, and potentially higher profits. AI can detect pump-and-dump schemes (which are prevalent in the crypto space) to protect traders and investors.

AI can help traders identify crypto narratives in the early stages. For example, AI could have helped traders foresee the rise of AI cryptocurrencies or SocialFi and its importance to the creator economy. By picking the top 20 AI cryptocurrencies in early 2023, traders would have made sizable profits.

The rise of crypto trading bots on Telegram and Discord is a true reflection of AI’s growing influence in crypto trading. We hear that crypto builders are in it for the tech. But the traders are in it for the money, and bot trading when done right could be a viable way of getting that lambo one day, if you know what you’re doing and get lucky. 

8. Fraud Detection and Prevention

Blockchain is known for its robust security and transparency, but is not immune to acts of fraudulence such as market manipulation, fake trading volumes, and phishing scams. AI can help by detecting unusual patterns and behaviors within the blockchain to identify potential threats. By recognizing anomalies, AI can minimize fraud, whether it’s in unauthorized access to the blockchain network, identity theft, or financial transactions.

Of course, it’s not only crypto. The U.S. Federal Trade Commission (FTC) claims that consumers lost $8.8 billion to fraud in 2022, a worrying 44% increase from 2021. If AI and blockchain can reduce this figure, hopefully, some U.S. regulators hellbent on destroying crypto may start to see the potential it carries.

7. Personalized Recommendations

We have been using personalized recommendations for longer than we think. But through the power of Web3, AI, and blockchain, personalized recommendations can be taken to a whole new level. AI can be used on blockchain data to understand user preferences, and to provide users with tailored recommendations for new crypto, Web3, and NFT projects.

As the Web3 revolution accelerates, a decentralized web could help users own their data and achieve one of the leading promises of Web3: full privacy. 

Blockchain, a digital record, can be mined for insight into the provenance of the data that builds AI, addressing the challenge of ‘explainable AI’. This helps improve trust in data integrity and, by extension, in the recommendations that AI provides.

6. Data Analytics

Blockchains are immutable ledgers that provide rich data to analyze. AI can rapidly read, understand, and correlate data at incredible speed. This big-data processing brings a new level of intelligence to blockchain-based business networks, and centralized service providers will struggle to keep up.

By providing large volumes of data, blockchain helps AI provide more actionable insights, manage data usage and model-sharing. All these combine to make for a better and more trustworthy data economy. 

Credit: Tesfu Assefa

5. Smart Contract Auditing

It is estimated that the past decade has seen more than $4.75 billion in financial losses in Web3, caused by smart contract security flaws, with some estimates going as high as $12.3 billion.

AI can audit smart contracts, ensuring they function as intended, and are free from vulnerabilities and errors. This level of automation and assurance is crucial for the reliability and trustworthiness of smart contracts within the blockchain.

4. RWA Tokenization

Tokenization is a key concept in blockchain and Web3. A report by digital asset management firm claims that tokenized real world assets (RWAs) – crypto’s buzzword for bringing traditional financial products to various blockchain networks – could grow to $10 trillion by 2030.

AI can be used to create and manage tokens, ensuring that they are secure and compliant with regulations. This use case opens up new opportunities for businesses and individuals to tokenize assets, including real estate, art, fiat currency, and more. Stablecoins are so far the most successful application of tokenization of RWAs.

3. Healthcare Data Management

Healthcare providers must collect, transfer, and store sensitive data. This poses a big risk to the security and privacy of their users. In 2023, U.S. medical giant HCA Healthcare suffered a breach in which hackers stole data belonging to 11 million patients. How can healthcare facilities ensure data protection and privacy?

AI-driven blockchain systems can create and maintain secure, immutable patient records. This streamlines data access for healthcare providers, and also ensures the integrity and privacy of sensitive medical information.

The use of AI in healthcare can extend to clinical trials and research. Blockchain’s transparency and security, combined with AI, can optimize the management of clinical trial data. This can enable researchers to accelerate medical discoveries.

To go back to the realm of supply chain optimization, AI can aid in tracing the origins and journey of pharmaceuticals using blockchain technology to prevent counterfeit drugs from entering the market. It is estimated that nearly $83 billion of fake drugs are sold globally per year.

2. Energy Management

Arranging the clean energy transition is a key issue of our time. AI can optimize energy consumption, production, and distribution by studying usage patterns and predicting demand, while P2P blockchain trading can enable businesses and individuals to buy and sell excess energy directly from one another.

The two technologies of AI and blockchain can also speed up the development of smart grids that can efficiently distribute and manage energy resources. 

1. Gaming and Virtual Reality

As the gaming sector intertwines with blockchain, it is estimated that the market size of blockchain gaming will grow from $7.1 billion in 2022 to a projected value of $772.7 billion by 2032

Just like anything else in life, you can predict the future of blockchain gaming by following smart money, aka venture capital. Venture capital firms invested more than $2.3 billion in Web3 gaming in the first three quarters of 2023, showing the sector’s strength and resilience amid a brutal crypto winter.

What role does AI play in Web3 gaming and virtual reality? Generative AI can create immersive and responsive virtual worlds, enhance blockchain in-game experiences, and even optimize game development processes. 

From generating realistic non-player characters (NPCs) to predicting player actions, AI is revolutionizing the gaming and virtual reality industry within Web3.


It’s still early days for both blockchain and artificial intelligence, and both are rather unfairly misunderstood and maligned by the general public and media. Despite this, the evolving new economies around data, digital creators, and tokenized assets should solidify this alliance in the coming years, hopefully for the greater good. Blockchain establishes digital trust and proof, and AI can both benefit from it and boost its reach. 

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Comment on this article


3 thoughts on “Top 10 Use Cases of AI in Blockchain and Web3

  1. well said

  2. These changes through AI will make life for Sapiens so much better

    Right now things seem bleak to most but I am so happy to be alive right now to witness our evolution together

  3. At first, the marriage of these two (AI and Blockchain) will be rather dull, a bit like a couple teetering on the brink of divorce. However, with the passage of time, the technology in both fields will mature, and the use cases will be significantly enhanced.

    One thing that does make me ponder is the potential of AI for optimizing energy consumption in blockchain applications. We're aware that AI can enhance the data mining process, ultimately aiding in reducing the energy expended in mining.







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