The sports industry might be one of the most important branches for NFTs implementation. From rare collectibles to voting rights - NFTs revolutionize fan engagement.

Tokens come in 4 main types: security tokens, payment tokens, utility tokens and object of today’s insertion, non-fungible tokens (NFTs). Non-fungible meaning they are not interchangeable with other articles due to their intrinsic qualities. For example, you cannot exchange a fridge with a typewriter and vice versa. However, fungible items can be swapped, because they are defined by their value, not their unique properties. A prominent example would be Bitcoin or other cryptocurrencies such as Cardano which can be purchased and sold for money.

The boom of digital assets

Although initially, non-fungible tokens had limited popularity in the mass market, now they are advertised on billboards, stadiums, in media, and services. Public awareness rose with the proliferation of “Cryptokitties”, an online game where players can breed and collect virtual cats. $12 million raised in investments alone, some of the “cats” were sold for over $150,000 a piece.

Soon after, the videogame was added to the ERC-721, a free and open standard that trains users on how to build tokens on the Ethereum blockchain, thereby coining it for the first time as an NFT. Recording an overall sale of $250 million in 2020, Dap Radar’s data logged a staggering $2.47 billion in the first 6 months of 2021, an 888 % increase.

NFT space in a brief

NFTs vary in application, from digital art, gaming, music, and movies, now onto the final frontier of virtual reality, the Metaverse. The growing popularity of the token is that it provides an ownership alternative, enabling buyers to own items without having to compromise with media platforms. Ownership terminates only when the owner decides to sell the item. The key advantage is a unique and integrated blockchain mechanism that indicates effective ownership history and easily detects the authenticity of an NFT.

Moreover, the potential is believed to be transformative. As DLT economies grow and the benefits of decentralized economies become undeniable for key investment players, there will be a shift towards decentralized finance. Tokens, amongst which NFTs, are the “lifeblood of this new system” (Tech Crunch).

Where will non-fungible tokens take us?

In a standard economy, and therefore in a DLT transition, sport is a major business. Consulting agency Kearney estimates that the industry is currently worth circa $620 billion, growing faster than the global GDP, making it an el dorado for those seeking fortune. The value generated and the prospects it offers make what first appears as a strange “collaboration”, only a natural step in the next gen of value creation. That begs the question, how does this collaboration work and how can the NFTs increase the involvement of sports fans?

Fan participation framework

In the conventional, physical world, there are many ways to get involved in sports and all the entertainment around it. Some buy the merchandise, some wait for their heroes’ autograph in the blistering cold and some pass their time on collectibles, panini for example, a card cult in Italy. There is unquestionably a nostalgia and psychological dimension powering sports industry which attempts to merge innovative tech solutions to increase fans’ participation. The most recent examples of world’s most popular disciplines prove that.

Why sports fans are interested in NFTs?

The use of NFTs is purposed towards more meaningful fan-club interactions. Collectibles or player cards are virtual, allowing fans to gather and swap stickers with unique highlights from their athletes. These cards have levels of rarity, some entering the market with a thousand-dollar price tag. That excites supporters, as it has for decades in a non-virtual environment and are thrilled to buy cards of their favorite sportsmen, even if pricey.

Case in point is Dapper Labs’ NFT marketplace platform NBA Top Shot where the lowest asking price for Ja Morant’s dunk series 1 is $475,000. Lebron James topped his legendary 32 at $535,000. Derrick Rose’s legendary 59 is currently valued at 1 million dollars.

Where new technologies meet fan base

The list goes on. The assurance to the fan is that the card becomes a non-exchangeable unit of data, meaning it holds a stamp of authenticity through the blockchain, annulling potential for fraud or mistake. The fan can trade safely, and the athlete can in fact create a novel source of income. Tampa Bay’s tight end Rob Gronkowski recently launched his personalized set of digital cards which show himself in action, removing elements that may infringe image rights, but nevertheless good enough to profit almost $ 2 million in sales.

The next level of fan engagement

Other than a business-grounded optic, NFTs encourage athletes to redefine their relationships with the public. That can be in the form of exclusive career content or rewards for the best fans including personal visits, online contact, gifts etc…. At this stage, this is hypothetical talk but done correctly, can bring the stands closer to the pitch, a dream every supporter holds.

Fantasy sports leagues

In some cases, NFTs can also be used within fantasy sports league applications, with each NFT representing a player who could be part of a team entered into season-long competitions. In the Fantasy League, an e-sports platform where users set up their own teams based on existing clubs, NFTs radically transformed the way how digital interactions related to sports now occur.

With Sorare, you create Fantasy Football lineups using NFT cards that you actually own. When the players score on the field, you win real money. The match in Russia notched Anderson a prize of 0.25 ETH (now worth around $500) and additional NFTs – more player cards – now worth over $2,000. Sorare doles out these prizes constantly. “I saw the potential right away,” says Anderson. “This is fun and engaging, and I can win NFTs and [ETH] using my passion for football and sports.” Anderson is part of a rabid group of soccer fans (120,000 active monthly users) obsessing over Sorare – an addictive blend of fantasy football, collecting and the wheeling and dealing of crypto trading. He loves it so much he started The Sorare Podcast, where guests join him to geek out over strategy.

Sportswear as a digital product

A step further past collectibles is wardrobe. Now more than ever have fashion and sports been synonymous of one another. Nike has become a dominant force in streetwear apparel besides brands such as Puma, Adidas, and Champion. Buying sportswear is a fashion statement, one that NFTs are starting to introduce in digital form. For example, Gucci Virtual 25 replicates a shoe design that can only be used in augmented reality.

Gamers (including sporting players) buy “skins” to give themselves a unique look, one that makes them stand out, and this has been going on since 2012, so the idea already exists. Until now, the industry has topped at relatively basic gear and memorabilia but with the creation of the metaverse, nothing is off the table.

How did the championship ring become a digital asset?

In basketball, 15 years onwards from Miami heat’s first championship glory, the NBA commemorated the event with an NFT collection, where virtual championship rings of the time, alongside banners and flags were offered on their digital platform. In football, ACF Fiorentina delivered special edition merchandise of jerseys for their 95-year anniversary, 95 jerseys materially and digitally available. The project was conducted on the Genuino program, a fan engagement platform where fans can purchase digital collectibles, certified by blockchain technology.

All in all, the paradigm describes a parallel shift in engagement, from physical to digital, but NFTs can do more than switch scenery, they can so to speak, buy you that sunrise view.

Decision making in sports clubs

In Japan, clubs in the non-professional shallows up until first division (J1) are adopting the token model to manage ownership structures with fans, and the sponsorship deals that underlie them. YSCC Yokohama announced that they had sold half a million dollars of tradeable fan tokens from the beginning of May, promising fans the possibility to vote on matters such as uniform design, player of the week, attend pre-match meetings with staff and access to VIP tickets.

In Turin, Juventus’s stadium, the Allianz, blasted Blur’s “Song 2” every time the “vecchia signora” would score a goal. This was possible because fans on a blockchain ecosystem called Socios.com decided so. The platform sells tokens, and the more you own, the stronger your voting powers are. The founder Arthur Dreyfus discussed the globality of the sport and that this mechanism allows fans that are away to still be part of the event, especially in times of Covid.

In theory, a song played at the Olimpico di Roma or Rajko Mitić Stadium in Belgrade can be selected by fans in India or even the Mauritius. No limits – global inclusivity is the 1st rule. It must be clear that organizations are run by professionals, so boundaries are in place and they won’t budge. Fans must make content with their role as fans, but that doesn’t mean they can’t have their piece of the pie.

How we can use NFT in sports fan engagement

NFT fan engagement and the metaverse

A study by Deloitte predicted that by the start of 2023 already 5 million fans will have either acquired NFTs or received them as a gift. There is a lot of convincing evidence to believe that fan engagement will be bolstered by activity outside of sports. Art, music, gaming, the wider possibilities are what initially will drive the NFT model, but sports, with its billions of fans around the globe, will have its say.

As strange as it appears to purchase digital content, we must understand that it is a recent phenomenon, an oddity. But with the advent of gamer culture, this is no longer the case. In 2020’s second quarter, American consumers spent about $1 billion on gaming content. By 2022, especially in case of COVID induced lockdown, tens of billions of dollars will flow into purchases. In this context, we can only expect for tokens to increase in numbers, types, and functions, and expect them to enter our everyday lives in more ways than we first thought. The sports industry may be among the first ones to experience that radical change.

Master UI Component Creation with AI: The Ultimate Guide for Developers

Gracjan Prusik

24 Mar 2025

Master UI Component Creation with AI: The Ultimate Guide for Developers

Introduction

Modern frontend development is evolving rapidly, and creating UI components with AI tools is helping developers save time while enhancing interface quality. With AI, we can not only speed up the creation of UI components but also improve their quality, optimize styles, and ensure better accessibility.

This article explores how creating UI components with AI is transforming frontend development by saving time and improving workflows. Specifically, we will discuss:

Generating components from images,
AI for style analysis and optimization,
Automatic style conversion and code migration,
AI in generating UI animations.

Creating UI Components with AI from Images

One of the interesting applications of AI in frontend development is the ability to generate components from an image. AI can recognize the structure of the interface and generate HTML/CSS or JSX code that matches the provided image. One of the most popular tools for UI creation is Lovable.

For testing, let's see how the tool performs in creating a simple contact form from the page you are currently on, which is Nextrope.

Query:

"Recreate the image I've sent you in Next.js using CSS."

Sample image used in the query:

The result received:

Tworzenie komponentów UI - Wygenerowany widok

Lovable did an excellent job transforming the image into code. The view is fully responsive. It’s important to remember that the more precise the request, the better the AI will replicate the expected view. However, even with a simple command, the tool performed surprisingly well.

Of course, AI has its limitations. It still makes quite a few mistakes. The generated code still requires review and fixes from the developer, but in some cases, the entire process is significantly sped up—correcting the code often takes less time than creating the component from scratch.

Optimizing UI Components with AI Tools for Style Improvements

This problem of inaccurate code reproduction by AI can be partially addressed by using it to analyze and improve styles. Tools like ChatGPT, DeepSeek and Claude are capable of not only generating code but also diagnosing CSS errors and suggesting why a particular style might not be working as expected.

Simple example: Why is the div not centered?

Query: "Why is this div not centered?"

AI analyzes the code and provides the following response:

Problem: The parent container does not have a defined width or display: flex.
Solution: Add the appropriate styles to the parent container.

.parent {
  display: flex;
  justify-content: center;
  align-items: center;
  width: 100vw;
  height: 100vh;
}

AI for Automatic Style Conversion and Code Migration in UI Components

AI can assist with style conversion between different technologies, such as transferring code from traditional CSS to Styled Components or Tailwind CSS.

Let's assume we have a style written in traditional CSS:

.button {
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;
}

.button:hover {
  background-color: darkblue;
}

We can use AI for automatic conversion to Styled Components:

import styled from "styled-components";

const Button = styled.button`
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;

  &:hover {
    background-color: darkblue;
  }
`;

export default Button;

AI can also assist in migrating code between frameworks, such as from React to Vue or from CSS to Tailwind.

This makes style migration easier and faster.

How AI Enhances UI Animation Creation

Animations are crucial for enhancing user experience in interfaces, but they are not always provided in the project specification. In such cases, developers have to come up with how the animations should look, which can be time-consuming and require significant creativity. AI, in this context, becomes helpful because it can automatically generate CSS animations or animations using libraries like Framer Motion, saving both time and effort.

Example: Automatically Generated Button Animation

Suppose we need to add a subtle scaling animation to a button but don't have a ready-made animation design. Instead of creating it from scratch, AI can generate the code that meets our needs.

Code generated by AI:

import { motion } from "framer-motion";

const AnimatedButton = () => (
  <motion.button
    whileHover={{ scale: 1.1 }}
    whileTap={{ scale: 0.9 }}
    className="bg-blue-500 text-white px-4 py-2 rounded-lg"
  >
    Press me
  </motion.button>
);

In this way, AI accelerates the animation creation process, providing developers with a simple and quick option to achieve the desired effect without the need to manually design animations from scratch.

Summary

AI significantly accelerates the creation of UI components. We can generate ready-made components from images, optimize styles, transform code between technologies, and create animations in just a few seconds. Tools like ChatGPT, DeepSeek, Claude and Lovable are a huge help for frontend developers, enabling faster and more efficient work.

In the next part of the series, we will take a look at:

How AI helps in frontend code refactoring
Code review with AI: Which tools help analyze code?
Optimizing the performance of frontend applications with AI

If you want to learn more about how AI is impacting the entire automation of frontend processes and changing the role of developers, check out our blog article: AI in Frontend Automation – How It's Changing the Developer's Job?

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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?

Table of Contents

AI vs. Tradition: Key Implementations of AI in Real Estate
Integration of AI with Blockchain in Real Estate
The Future of AI in Real Estate: Trends and Forecasts
Conclusion

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.

The Future of AI in Real Estate: Trends and Forecasts

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

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