Making the Most of AI and GPT-like Models: An examination of the industries most suitable for integration

Paulina Lewandowska

19 Jan 2023
Making the Most of AI and GPT-like Models: An examination of the industries most suitable for integration

Introduction

The way businesses work is being revolutionized by artificial intelligence (AI) and language models like GPT. AI is quickly becoming a crucial tool for businesses wanting to stay competitive in today's fast-paced economy, from automating monotonous processes to offering insightful analysis and predictions. In this article, we'll look at how companies are using GPT-like models and AI to boost productivity, boost efficiency, and boost revenue. We will look at the numerous uses of AI in the corporate world, from customer service to financial analysis. We'll also look at how GPT-like models are specifically employed in content generation and natural language processing to scale up communication and human-computer interaction.

AI implementation by sector

AI and models like GPT can be particularly beneficial in a variety of sectors, including but not limited to:

SectorApplications
Natural Language Processing (NLP)Language Translation, Text Summarization, Question Answering
Content CreationAutomated written content generation (news articles, product descriptions, social media posts)
BusinessAutomating tasks (customer service, sales, marketing), Financial forecasting and analysis
HealthcareMedical Diagnosis, Drug Discovery, Personalized Medicine
EducationPersonalized learning experience, Grading and providing feedback
Transport and logisticsSelf-driving cars, Supply chain management
RoboticsObject recognition, Navigation, Manipulation
GamingRealistic and engaging gameplay, New types of games

GPT-like Models in NLP and Content Creation: Automating Writing and Personalizing Content

GPT-like models have demonstrated substantial skills in the areas of Natural Language Processing (NLP) and content generation. Language translation, text summarization, and question answering are just a few of the natural language processing activities that are catered to by language models like GPT-3.

Automated writing is one of the most well-liked uses of GPT-like models in NLP and content generation. GPT-3 is capable of producing written content such as blog entries, product descriptions, and social media updates automatically. By automating the process of content production, GPT-3 can save enterprises a significant amount of time and resources because it can produce cohesive and grammatically sound text. This makes GPT-3 perfect for jobs like writing reports, email drafts, and chatbot scripts for customer assistance.

GPT-like models have uses in personalized content creation for clients in addition to automated authoring. By evaluating consumer data and creating content that is specific to the user's interests and preferences, GPT-3, for instance, can be used to provide personalized product suggestions or targeted advertising. This might aid companies in enhancing their marketing initiatives and raising client involvement.

Automation: Using AI to Simplify Business Processes 

Automating processes is one of the most obvious ways that organizations are utilizing AI. AI can handle a wide range of monotonous activities, from customer care chatbots to automated financial analysis, freeing up employees to concentrate on more worthwhile work. Simple customer care requests, like responding to frequently asked queries, can be handled by AI-powered chatbots, while more sophisticated systems can even manage complicated problems. Additionally, financial analysis tasks like fraud detection and trend prediction can be automated using machine learning models.

AI-Assist in Healthcare Revolution: Diagnosis and Treatment 

AI is being applied in a variety of ways in the healthcare sector to improve efficiency and precision. AI-powered systems, for instance, can help clinicians diagnose illnesses by reviewing medical images and making recommendations. This raises diagnostic precision while lowering the possibility of human error. Drug development is another area where AI is being used in healthcare. AI is capable of analyzing enormous amounts of data, including genetic data, to find potential novel treatments and medications. AI is also being used to develop individualized treatment regimens for patients, which take into consideration aspects like medical history, genetics, and other personal traits.

Intelligent tutoring and Personalized Learning with AI in Education 

Similar to how it is being used in business, AI is being used in education to help teachers grade assignments and give feedback to students. Based on a student's skills, shortcomings, and preferred learning style, AI is used to generate customised learning plans for them. Additionally, it contributes to the development of intelligent tutoring programs that support teachers by offering tailored feedback and assistance to students both within and outside of the classroom. AI is also being used to automate grading and assessment, which can assist save teachers time and increase the effectiveness of the educational system.

AI-Optimized Logistics and Transportation: Supply Chain Management to Self-Driving Cars 

AI is also being used by the transportation and logistics sector to boost productivity and cut expenses. The development of self-driving automobiles is one example of how AI can be used to enhance road safety and lower the frequency of accidents brought on by human mistake. Another area where AI may be used to optimize is supply chain management. This is done by forecasting demand, analyzing data, and making better decisions. AI can also improve fleet management by tracking the whereabouts and condition of vehicles, anticipating maintenance requirements, and increasing productivity.

Enhancing Capabilities and Real-world Functionality of AI-Powered Robotics 

AI is being applied in the field of robotics to enhance the capabilities and usefulness of robots. Robots are now able to recognize and interact with items in the real world thanks to AI, for instance in the field of object recognition. Another area where AI is applied to help robots autonomously navigate in challenging settings is navigation. AI can also be utilized to enhance the manipulation abilities of robots, allowing them to carry out a larger variety of activities, like grabbing and manipulating real-world objects. Robots are improving their ability to work in real-world settings and do tasks that were previously insurmountable thanks to the incorporation of AI.

From Realistic Gameplay to Game Development: AI in the Gaming Industry 

AI is also employed in the video game industry to build new game genres and more realistic and captivating gameplay. By offering more lifelike AI-controlled characters and environments, game AI is one application of AI that aims to improve gameplay realism and engagement.

AI can also be applied to the creation of new game mechanisms and game genres, such as games that adjust to the preferences and skill level of the player. AI can speed up the process of finding and fixing flaws in games, giving gamers a better gaming experience. Game testing can also be improved by AI. We may anticipate even more advancements in the application of AI to gaming as it continues to develop, pushing the limits of what is feasible in the gaming sector.

Conclusion

In conclusion, the incorporation of AI and models resembling the GPT into numerous industries and businesses is proving to be quite advantageous. These technologies are transforming how we conduct business, improve medical diagnosis in healthcare, personalize education, optimize logistics and transportation, and even transform the gaming sector. GPT-like models have enormous potential for content creation and natural language processing. Businesses should be aware of the advantages and potential of these technologies. The integration of AI and GPT-like models in several industries has a promising future.

Tagi

Most viewed


Never miss a story

Stay updated about Nextrope news as it happens.

You are subscribed

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:

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?

Follow us to stay updated!

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