Artificial Intelligence is not science fiction; it is a present-day reality. It is no longer something distant, located in Silicon Valley. Today, it is integrated into your smartphone, customer support chats, YouTube recommendations, and the applications you use regularly. In the near future, it may even become a cornerstone of your own startup.

For those beginning their entrepreneurial journey and assessing the market, now is an ideal time to focus on AI. In 2024, the AI market was valued at nearly $280 billion, and this is merely the beginning — growth projections estimate an annual increase of almost 36% in the coming years. According to PwC, AI will contribute an estimated $15.7 trillion to the global economy by 2030. These are substantial figures, and the beneficiaries are not just large corporations; they also include startups, new teams, and innovative solutions. Perhaps your solution will be among them.    

Let’s explore the various domains of AI and where they can be applied within the broader economy. 

 

 

A Deeper Dive into the Theory: The Different Types of Artificial Intelligence

When discussing "AI", it is common to envision an advanced machine capable of everything: thinking, learning, generating ideas, and even engaging in debates with humans. However, the reality of AI today is not a singular, all-encompassing "intelligence", but rather a spectrum of technologies that are evolving incrementally. Broadly speaking, AI can be classified into three primary types:    

1. Narrow AI — The Existing Technology

This is the most prevalent and widely applied form of artificial intelligence. It is designed to solve a specific problem or a limited set of tasks, and it it excels within the confines of its intended purpose. However, it does not have the capability to perform tasks beyond those it has been programmed to handle.

Examples include:

• Voice assistants;
• Chatbots in customer support;
• Speech or facial recognition systems;
• Recommendation algorithms in platforms like YouTube or Spotify.

Why is it called "weak"? Because narrow AI lacks the kind of general reasoning or understanding that humans possess. It does not comprehend context, cannot improvise, and is incapable of going beyond the parameters defined by its algorithm. Despite these limitations, narrow AI forms the foundation for a wide array of products, from mobile applications to industrial systems.     

2. General AI (AGI) — The Ultimate Aspiration

Artificial General Intelligence (AGI) represents a much more ambitious goal. The aim of AGI is to develop an AI system that can perform any intellectual task as competently as a human. AGI does not rely on pre-programming for each specific task but instead learns, deduces conclusions, and transfers knowledge across various domains.

An AGI system have the ability to:

• Learn from its own experience;
• Analyze complex situations;
• Understand abstract concepts;
• Act without a precise algorithm.

As of now, AGI remains in the developmental phase. While it does not yet exist in practical applications, extensive research and experimental work continue in laboratories around the world.  

3. Superintelligence — AI That Surpasses Human Intelligence

At present, this level of intelligence belongs to the realm of science fiction, though it is also the subject of serious scientific discussions. Superintelligence refers to an AI that surpasses human capabilities in all cognitive domains — logic, intuition, creativity, and processing speed. 

If superintelligence were to emerge, it could:

• Solve problems that humans may not even be capable of identifying;
• Provide solutions instantaneously;
• Predict complex systems;
• Change the course of entire industries and even civilizations.

However, this remains speculative. No prototype exists, nor is there a clear pathway to achieving it. Superintelligence currently exists only in literature, cinema, and forward-looking discussions. Nonetheless, its potential implications are being rigorously studied, because the consequences of its emergence would be monumental. Perhaps, in the future, your startup could play a pivotal role in bringing humanity closer to this level of AI.    

 

 

What Powers AI Products

When you interact with a chatbot, observe AI completing lines of code, or see it generating an image based on a text prompt, you are witnessing the result of multiple advanced technologies working together. This is particularly evident in products such as ChatGPT, Midjourney, DALLE, and Suno, which are built on LLM (Large Language Models). 

However, LLMs are not standalone "magic" systems. They represent the integration of several powerful technologies, each playing a distinct role:

• Deep Learning (DL) — enables AI to identify complex patterns and "understand" context.
• Natural Language Processing (NLP) — allows AI to analyze and generate human-like text.
• Generative AI (Gen AI) — facilitates the creation of new text, images, music, videos, and even software code. 

To gain a deeper understanding of the technological foundation of AI-driven solutions, let us examine their core components.

Neural Networks

Neural networks, inspired by the structure of the human brain, rely on mathematical models and algorithms rather than biological neurons. These networks are capable of learning, recognizing complex patterns, processing speech, and even controlling autonomous systems. They underpin a wide range of applications, from Instagram filters to Tesla's autopilot.   

Machine Learning (ML)

Machine learning enables AI systems to learn from examples by analyzing thousands of similar cases and deriving insights. As a result, ML is widely used in industrial applications, including predictive maintenance, anomaly detection, and pattern recognition.

Deep Learning (DL)

Deep learning is an advanced subset of machine learning that utilizes multilayered neural networks, with each layer processing data at increasing levels of complexity. This advanced approach has revolutionized fields including medicine, finance, autonomous systems, and the creative industries. 

 

 

Industries Where AI Is Already Delivering Tangible Results

The technologies outlined above are already transforming numerous sectors by solving real-world challenges. Key applications include:  

• Natural Language Processing (NLP) — AI-powered tools can analyze vast volumes of textual and voice data. For example, by assessing customer feedback on social media, businesses can identify product issues and implement targeted improvements. 
• Computer Vision (CV) — enables systems to "see" and interpret visual information. From facial recognition in smartphones to object detection, medical diagnostics through imaging, and autonomous vehicle navigation, computer vision is revolutionizing various fields. 
• Generative AI (Gen AI) — creates original content, including text, images, videos, music, sound, and code. Unlike simple replication, Gen AI synthesizes and produces innovative outputs based on data-driven insights.

 

 

Figure 1: AI technology market

Introducing the AI Agent

An AI agent represents a convergence of multiple AI capabilities within a single system. These agents possess the ability to:

• See (computer vision);
• Understand and speak (NLP);
• Learn (ML and DL);
• Generate (Gen AI);
• Act (interact with humans or systems).

These agents work in real-time, adapt, make decisions, and achieve goals with minimal human input. Unlike traditional RPA that follow strictly defined commands, AI agents learn and modify their behavior, making them more flexible and effective.  

 

 

AI in Our Lives

Fintech

In banks, fintech startups, and investment firms, AI processes vast datasets, analyzes consumer behavior, and monitors risks. Through AI, it becomes possible to:

• • Rapidly assess creditworthiness;
  • Detect suspicious transactions and prevent fraud;
  • Construct a well-informed investment portfolio based on comprehensive analytics.

Healthcare

AI empowers healthcare professionals, augmenting their capabilities rather than replacing them. AI systems are proficient at:

• • Identifying diseases at early stages, such as through diagnostic imaging;
  • Recommending personalized treatment plans;
  • Continuously monitoring patient conditions in real-time;
  • Accelerating the development and testing of new pharmaceuticals.

E-commerce and Retail

AI plays an essential role in the online shopping experience:

• • Recommendation algorithms suggest products aligned with your preferences;
  • Chatbots offer 24/7 customer support;
  • AI systems forecast demand and manage inventory to ensure timely product delivery.

Logistics and Transportation

In logistics, AI excels at:

• • Optimizing route planning;
  • Managing delivery schedules based on real-time demand;
  • Overseeing autonomous vehicles and drones.

This contributes to reduced operational costs while improving delivery efficiency and accuracy.

Education

In education, AI enhances the student experience by:

• • Tailoring individual learning paths;
  • Assisting in the grading and evaluation of tests and exams;
  • Analyzing student performance to identify areas for improvement;
  • Serving as a virtual tutor and mentor.

Manufacturing

In industrial settings, AI is being integrated for its ability to:

• • Predict equipment failures before they occur;
  • Ensure the quality control of products;
  • Execute intricate tasks with AI-driven robotics on production lines.

Entertainment Industry

AI curates personalized experiences based on your preferences:

• • Suggesting music, films, and content on social media platforms;
  • Creating custom covers, videos, and even jokes;
  • Generating unique content in real-time tailored to individual tastes.

 

 

How to Launch Your Own AI Startup

Building an AI product does not necessitate a PhD or the development of a neural network from the ground up. The key to success lies in clearly defining the problem to be addressed and demonstrating persistence in execution.   

Key Steps to Getting Started:

1. Identify a Real-World Problem

Engage with industry professionals or observe daily processes. Where can automation replace manual work? Where is speed or accuracy lacking? AI is most effective in data-rich and repetitive workflows.

2. Analyze the Market

Research existing solutions and identify competitors' weaknesses. Consider how you can offer a faster, more efficient, or cost-effective alternative.

3. Build an MVP

Leverage ready-made APIs, open-source models, and platforms such as Hugging Face, OpenAI, or Google Cloud. The key is to test your idea and gather user feedback as early as possible.

4. Secure Investment

In 2025, two Uzbek AI startups — Datatruck and Unitlab — collectively raised $950,000 in funding, marking just the beginning.

Currently, 10 venture capital funds in Uzbekistan actively support early-stage startups, with IT Park Ventures prioritizing AI and ML projects.

 

 

Artificial Intelligence: A New Growth Opportunity Awaiting You

Not long ago, digitalization seemed like an abstract concept. Today, it is indispensable for the functioning of any business. The same transformation is underway with AI, and it has already begun. The most important step is not to wait for "perfection" but to take action now — whether with an idea, a prototype, an API request, or simply a conversation with a potential user.

If you aspire to stay at the forefront, develop your ideas, collaborate with like-minded individuals, and participate in real startup initiatives, register on the Startup Base platform. It is your gateway to the world of AI and innovation.