Web3 and AI: Enhancing Security, Efficiency, and User Experience

Paulina Lewandowska

12 Jan 2023
Web3 and AI: Enhancing Security, Efficiency, and User Experience

Introduction: Web3 and AI - A Match Made in the Digital World

Through machine learning and intelligent automation, artificial intelligence (AI) has the potential to revolutionize a variety of industries and applications. AI has the potential to improve the features and functionality of blockchain-based goods and services in the world of web3(third generation of the World Wide Web) providing users with even more value.

The term "Web3" describes the Internet's decentralized, peer-to-peer functionality made possible by blockchain technology. It enables the development of programs and services that run on a decentralized network of computers rather than being managed by a single organization. The addition of AI to web3 has the potential to greatly improve the functionality and capabilities of these goods and services while also enhancing user experience, security, and effectiveness.

This article will explore the usefulness of AI in web3, looking at the various applications of AI in blockchain-based goods and services. We will examine the advantages of AI integration in web3 as well as how AI will affect web3 and blockchain technology in the future. Come along as we explore the intriguing potential of AI in the web3 world.

AI 101: A Beginner's Guide to Artificial Intelligence in Web3/Blockchain

But what exactly is artificial intelligence, and how can it be applied to products for the web, blockchain, and cryptocurrency?

Artificial intelligence (AI) is the capacity of machines to carry out tasks that normally require human intelligence, such as problem-solving, learning, and judgment. This is accomplished with the aid of machine learning algorithms, which give computers the ability to examine data, spot trends, and then predict the future or make decisions based on those trends.

In order to improve the functionality and capabilities of web3/blockchain products, AI can be applied in a number of different ways. Several instances include:

  • AI can be used to enable chat bots or smart contracts that can comprehend and respond to human language, making them more user-friendly and effective. This is known as natural language processing.
  • Predictive analytics: AI can analyze market trends or asset pricing data to make future predictions that may be useful to traders or investors.
  • Artificial intelligence (AI) can be used to spot unusual patterns or behaviors that might be signs of fraud, enhancing the security of blockchain-based systems.
  • Supply chain management: AI can be used to improve efficiency and cut waste by optimizing the flow of resources and goods through a supply chain.

AI in Action: Real-World Examples of Artificial Intelligence in Web3/Blockchain Products

Let's examine some specific applications of AI in the market now that we have a better understanding of what AI is and how it can be applied to web3/blockchain products.

  1. AI-powered chatbots are a useful tool for customer service or support because they can comprehend and respond to human language. Natural language processing can also be used to improve the usability and comprehension of smart contracts, which are self-executing contracts with the terms of the agreement written in code.
  2. Another application of AI in web3/blockchain products is predictive analytics. AI can analyze market trends or asset pricing data to make future predictions, which can be useful for traders or investors. For instance, an AI-powered trading platform built on blockchain technology could analyze market data and suggest trades to users.
  3. Fraud detection in web3/blockchain products can also be done using AI. Data analysis using machine learning algorithms can spot unusual patterns or behaviors that could be signs of fraud, enhancing system security. An AI-based payment platform, for instance, could be used to identify and stop fraudulent transactions.
  4. Another application of AI in web3/blockchain products is predictive analytics. AI can analyze market trends or asset pricing data to make future predictions, which can be useful for traders or investors. For instance, an AI-powered trading platform built on blockchain technology could analyze market data and suggest trades to users.

Benefits of using AI in web3/blockchain products

So far, we've seen how AI can be applied to web3/blockchain products in a number of ways to improve their capabilities and functionality. But what advantages do these products' use of AI offer?

BenefitDescription
Improved user experienceNatural language processing and predictive analytics are made possible by AI, which makes web and blockchain products more approachable and simple to use.
Enhanced security and reliabilityAI can identify and correct errors in code or data, as well as detect and stop fraudulent activity, increasing the overall security and dependability of web3/blockchain products.
Increased efficiency and automationAI can automate or improve supply chain management, freeing up time and resources for more difficult tasks..

All things considered, the incorporation of AI in web3/blockchain products has the potential to significantly improve user experience, security, and efficiency. Future applications and advantages of AI technology are likely to be even more creative as the field develops.

Web3/Blockchain's Future with AI: A Look at the Potential of Artificial Intelligence in Decentralized Technologies

As we've seen, AI has the potential to significantly improve the functionality and capabilities of web3/blockchain products, adding value for users and advancing a number of technical aspects. But what part will AI play in the development of blockchain and web3 technology?

  • Integration of AI into web3/blockchain products and services could improve decentralized finance (DeFi) platforms, allowing for more transparent and efficient financial transactions. Decentralized applications (DApps) could benefit from improved performance and user experience, and blockchain networks could benefit from increased security and dependability.
  • New blockchain protocols and standards could be created and put into use by using AI to analyze data and find patterns that could be used to create more secure or efficient blockchain systems. It could also be used to evaluate new protocols and help roll out updates and improvements to current systems.
  • Resolving issues with web3 and blockchain technology: AI could be used to improve the efficiency of blockchain networks or to create new applications and use cases that promote technology adoption. Additionally, it could be utilized to increase the scalability of blockchain systems or to help create new governance or regulatory frameworks..

Conclusion: Is AI an integral part of the web3 ecosystem?

As a result, it is evident that AI has the potential to significantly improve the functionality and capabilities of web3/blockchain products, enhancing user experience and advancing various facets of technology. The use of AI in web3/blockchain products spans a wide range of areas, including supply chain optimization, fraud detection, and predictive analytics.

But does the web3 ecosystem include AI in its entirety? Although it is unquestionably a potent tool that can benefit web3/blockchain products and services greatly, it is important to understand that AI is only one part of the ecosystem. Decentralized networks, blockchain technology, and other innovations all contribute to the web3 ecosystem and its future development.

The use and integration of AI with other technologies will ultimately determine its place in the web3 ecosystem. As AI technologies develop, it's critical to think about the ethical, legal, and social ramifications of their use and to make sure they're applied responsibly and advantageously.

Tagi

Most viewed


Never miss a story

Stay updated about Nextrope news as it happens.

You are subscribed

AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
Nextrope Logo

Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series

AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

Gracjan Prusik

11 Mar 2025
AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

AI Revolution in the Frontend Developer's Workshop

In today's world, programming without AI support means giving up a powerful tool that radically increases a developer's productivity and efficiency. For the modern developer, AI in frontend automation is not just a curiosity, but a key tool that enhances productivity. From automatically generating components, to refactoring, and testing – AI tools are fundamentally changing our daily work, allowing us to focus on the creative aspects of programming instead of the tedious task of writing repetitive code. In this article, I will show how these tools are most commonly used to work faster, smarter, and with greater satisfaction.

This post kicks off a series dedicated to the use of AI in frontend automation, where we will analyze and discuss specific tools, techniques, and practical use cases of AI that help developers in their everyday tasks.

AI in Frontend Automation – How It Helps with Code Refactoring

One of the most common uses of AI is improving code quality and finding errors. These tools can analyze code and suggest optimizations. As a result, we will be able to write code much faster and significantly reduce the risk of human error.

How AI Saves Us from Frustrating Bugs

Imagine this situation: you spend hours debugging an application, not understanding why data isn't being fetched. Everything seems correct, the syntax is fine, yet something isn't working. Often, the problem lies in small details that are hard to catch when reviewing the code.

Let’s take a look at an example:

function fetchData() {
    fetch("htts://jsonplaceholder.typicode.com/posts")
      .then((response) => response.json())
      .then((data) => console.log(data))
      .catch((error) => console.error(error));
}

At first glance, the code looks correct. However, upon running it, no data is retrieved. Why? There’s a typo in the URL – "htts" instead of "https." This is a classic example of an error that could cost a developer hours of frustrating debugging.

When we ask AI to refactor this code, not only will we receive a more readable version using newer patterns (async/await), but also – and most importantly – AI will automatically detect and fix the typo in the URL:

async function fetchPosts() {
    try {
      const response = await fetch(
        "https://jsonplaceholder.typicode.com/posts"
      );
      const data = await response.json();
      console.log(data);
    } catch (error) {
      console.error(error);
    }
}

How AI in Frontend Automation Speeds Up UI Creation

One of the most obvious applications of AI in frontend development is generating UI components. Tools like GitHub Copilot, ChatGPT, or Claude can generate component code based on a short description or an image provided to them.

With these tools, we can create complex user interfaces in just a few seconds. Generating a complete, functional UI component often takes less than a minute. Furthermore, the generated code is typically error-free, includes appropriate animations, and is fully responsive, adapting to different screen sizes. It is important to describe exactly what we expect.

Here’s a view generated by Claude after entering the request: “Based on the loaded data, display posts. The page should be responsive. The main colors are: #CCFF89, #151515, and #E4E4E4.”

Generated posts view

AI in Code Analysis and Understanding

AI can analyze existing code and help understand it, which is particularly useful in large, complex projects or code written by someone else.

Example: Generating a summary of a function's behavior

Let’s assume we have a function for processing user data, the workings of which we don’t understand at first glance. AI can analyze the code and generate a readable explanation:

function processUserData(users) {
  return users
    .filter(user => user.isActive) // Checks the `isActive` value for each user and keeps only the objects where `isActive` is true
    .map(user => ({ 
      id: user.id, // Retrieves the `id` value from each user object
      name: `${user.firstName} ${user.lastName}`, // Creates a new string by combining `firstName` and `lastName`
      email: user.email.toLowerCase(), // Converts the email address to lowercase
    }));
}

In this case, AI not only summarizes the code's functionality but also breaks down individual operations into easier-to-understand segments.

AI in Frontend Automation – Translations and Error Detection

Every frontend developer knows that programming isn’t just about creatively building interfaces—it also involves many repetitive, tedious tasks. One of these is implementing translations for multilingual applications (i18n). Adding translations for each key in JSON files and then verifying them can be time-consuming and error-prone.

However, AI can significantly speed up this process. Using ChatGPT, DeepSeek, or Claude allows for automatic generation of translations for the user interface, as well as detecting linguistic and stylistic errors.

Example:

We have a translation file in JSON format:

{
  "welcome_message": "Welcome to our application!",
  "logout_button": "Log out",
  "error_message": "Something went wrong. Please try again later."
}

AI can automatically generate its Polish version:

{
  "welcome_message": "Witaj w naszej aplikacji!",
  "logout_button": "Wyloguj się",
  "error_message": "Coś poszło nie tak. Spróbuj ponownie później."
}

Moreover, AI can detect spelling errors or inconsistencies in translations. For example, if one part of the application uses "Log out" and another says "Exit," AI can suggest unifying the terminology.

This type of automation not only saves time but also minimizes the risk of human errors. And this is just one example – AI also assists in generating documentation, writing tests, and optimizing performance, which we will discuss in upcoming articles.

Summary

Artificial intelligence is transforming the way frontend developers work daily. From generating components and refactoring code to detecting errors, automating testing, and documentation—AI significantly accelerates and streamlines the development process. Without these tools, we would lose a lot of valuable time, which we certainly want to avoid.

In the next parts of this series, we will cover topics such as:

Stay tuned to keep up with the latest insights!