David Streltsoff
5 min readJul 15, 2024

Enhancing User Experience in Crypto Platforms with AI

Image: Pexels

If you’ve been following the gradual evolution of crypto platforms, such as exchanges, you’ve likely noticed improvements in the user experience. These enhancements lead to more cohesive, safer, and usable platforms, making them more appealing to newcomers and longtime users.

But how do these platforms enhance the user experience in a meaningful way? While this process may seem straightforward, it’s incredibly involved, requiring the input of a qualified user experience (UX) designer.

The UX designer will work closely with a user interface (UI) designer and a graphic designer to create the look and feel of an assigned project. That project may involve the creation of a desktop, mobile, or web application, and crypto platforms fall comfortably within this domain.

The UX designer will receive a design brief or be required to conduct user research early on.

During the user research stage, the UX designer will pinpoint the pain points the target audience experiences. Furthermore, it’s crucial to identify user behaviors and what goals users wish to achieve. If the UX designer and the rest of the team craft a phenomenal user experience — this will lead to a user-friendly app and possibly a hit for the development team.

While this is well and good, how does artificial intelligence (AI) play into this? The stratospheric rise of generative AI these past two years has caused tech companies, enterprises, and crypto platforms to embrace it. And they’ve taken this route because they understand that the correct implementation of AI in their products and services adds value — particularly to the user experience.

Understanding Generative AI

Contrary to popular belief, generative AI is not new and didn’t start life as the popular chatbot — ChatGPT. It was during the 1960s that early examples of generative AI emerged. However, it only attracted significant media attention in 2014, as the latest generation of generative AI also benefited from machine learning (ML) implementations.

Researchers wanted to process large amounts of data, so they used these ML models with neural networks. They managed to gather and analyze information rapidly, and many large enterprises took interest — with Amazon, Google, and Microsoft at the forefront. With so much interest and investment channeled towards generative AI, it would quickly evolve beyond its original scope.

Today, generative AI has become the go-to tool for automated tasks, image creation, and virtual assistants. Users don’t need to engage with complex drag-and-drop interfaces or know a programming language to make the most of generative AI. Instead, users will instruct a generative AI model via text prompts in a human-understood language like English, in many cases.

But computing devices or applications don’t understand human language — so how is generative AI capable of doing so? Natural language processing (NLP) facilitates this easy and fluid interaction between humans and generative AI. It’s a technology based on ML and allows a computing device to understand and interact with human language in an almost human-like manner.

Overall, it’s a game-changer since it allows organizations of all sizes to streamline tasks in many fields. With only a bit of training, staff can complete more tasks during the workday with generative AI than with any other tool.

How Crypto Platforms Benefit From AI

While generative AI is already proving its worth in the enterprise space, it’s also making inroads in crypto. Since generative AI excels as a chatbot implementation, all crypto platforms can benefit from this. Onboarding new users is always challenging, leading to a high churn rate when poorly implemented.

An AI-powered chatbot that informs new users about a platform’s features in a clear and easy-to-understand manner will increase the possibility of those users staying with the platform. Furthermore, the chatbot will respond to users’ questions concisely. And if necessary, it will deliver longer and more detailed answers to more technical queries.

Another area where generative AI excels is in safeguarding data, intellectual property (IP), and non-fungible tokens (NFTs) on the blockchain. Increasingly, crypto exchanges are collecting more personal user data than before. Some require user biometrics for verification purposes, with face scans becoming increasingly popular.

The last thing any user wants is to have their data, including face scans, leak out. Hackers and other bad actors relentlessly target crypto wallets and exchanges. While their primary goal is to steal cryptocurrency, personal data is also valuable to them.

They can sell this information on the dark web, often to nefarious parties. These parties will use this personal data to hack into users’ other accounts or use face scans to create duplicate IDs for trafficking networks or other purposes. Given the high risk to users, crypto platforms can utilize generative AI to consistently check the integrity of the blockchain and identify unusual behavior in real-time.

Several Examples Of AI-Powered Crypto Platforms

AI-powered crypto platforms are impacting the user experience in positive ways, as these examples below:

  • Fetch AI: Developers who wish to make the most of the AI economy can use this platform to build their businesses. They can offer AI apps, integrations, and services in exchange for the platform’s FET cryptocurrency.
  • Covalent: This decentralized network pulls data from blockchains like Avalanche, Ethereum, and Polygon. It features an optimized AI model specifically for reducing the possibility of bias and manipulation.
  • Cryptohopper: Users seeking a solution to run automated and customized trades gravitate towards this crypto trading bot. Its AI component is comprehensive and lets the trading bot test and pick the best strategies put forward by the user.
  • iExec: Owners of digital assets requiring tools to monetize more effectively will benefit from this platform. The platform’s AI and tooling assists developers to create dApps with safety in mind.
  • Numerai: This network functions as a hedge fund and utilizes AI & ML to help traders predict the stock market more accurately. Numerai offers several Python and R scripts to augment the ML component.

In Conclusion

It’s only a matter of time before most leading crypto platforms will have an AI component in some form. With this growing adoption of AI, the user experience will improve with the correct implementation and UX design.