Today, artificial intelligence has already penetrated all spheres of our lives. Not long ago, it seemed that neural networks and artificial intelligence would not be able to perform most everyday human tasks. However, thanks to computational resources and machine learning algorithms, neural networks have learned not only to compose texts and solve mathematical equations but also to recognize objects in images and videos (for example, for autonomous vehicles), as well as to manage production lines and logistics (for example, to optimize delivery routes).
In today’s article, we will examine what artificial intelligence can do and what people use AI for in various areas of application. We will also explore real practical examples of using neural networks in everyday tasks.
Introduction to the Application of Artificial Intelligence
Artificial Intelligence (AI) is a branch of computer science that designs and creates systems intended to perform tasks that require human intelligence. Simply put, AI is a computer program that receives and analyzes data and then draws conclusions based on the results. AI is a multifunctional tool that covers a wide range of tasks: processing large volumes of data, learning, forecasting, speech, text, music recognition, and more.
Today, the capabilities of artificial intelligence have become practically limitless. Here are some tasks where AI is already successfully applied and even replaces humans:
- Processing large volumes of data (Big Data).
- Automating various routine processes (for example, in IT).
- Recognizing and analyzing text, images, videos, sound, etc.
- Forecasting and modeling (for example, in finance or medicine).
- Personalization (for example, recommendation systems on streaming platforms and online stores).
- Managing complex systems (autonomous vehicles, logistics, robotics).
This "explosion" in demand for AI is associated with the following advantages:
- Efficiency: significant acceleration of processes while reducing costs.
- Accuracy: minimizing human errors.
- Scalability: processing and analyzing enormous data volumes in real time.
- Innovation: AI can open new possibilities in fields such as medicine, transport, marketing.
- Accessibility of technology: with increased computing power and data volume, AI applications have become cheaper and more widespread, allowing penetration into many fields.
Main Areas of AI Application
Let’s look at what AI is being used for in various societal sectors.
Medicine and Healthcare
The medical and healthcare sector is one of the most promising areas for implementing neural networks and AI. The adoption and funding of AI in healthcare are continuously growing. For example, an analytical report by CB Insights noted a 108% global funding increase in 2021. Here are real examples of AI in medicine:
- In March 2025, an international group of scientists from the University of Hong Kong, InnoHK D24H lab, and the London School of Hygiene developed a special AI model for diagnosing thyroid cancer. Experiments showed the model’s accuracy exceeded 90%. One key benefit is nearly halving the time doctors spend preparing for patient appointments by analyzing medical documents using advanced tools like ChatGPT and DeepSeek.
- AI is also used beyond text data. For example, it can detect prostate cancer using MRI scans as input data.
- Major tech companies actively use AI in medical services. Google Health has developed an AI for analyzing mammograms to detect breast cancer.
- IBM, a pioneer in computing, is deploying AI to handle medical information and assist doctors in selecting personalized cancer treatments. IBM is also advancing generative AI chatbots (watsonx Assistant), which are used in healthcare.
Finance and Banking
The financial and banking sector is no exception. AI is widely used for forecasting (including risk assessment), detecting potential fraud, and offering clients personalized services and offers based on their spending patterns. Specially trained algorithms analyze transactions in real time, identifying suspicious and fraudulent activities. AI is well established in credit and mortgage markets, aiding credit scoring, market trend prediction, investment management, and trading. Some practical examples:
- Goldman Sachs, a major investment bank and financial conglomerate, employs smart assistants to help employees with tasks such as summarizing documents, editing emails, or translating texts.
- PayPal uses AI extensively to detect fraudulent transactions in real time, processing billions of operations annually.
- JPMorgan Chase uses the AI-powered Coin service to analyze legal documents, reducing document processing time from 360,000 hours per year to just seconds.
Industry and Manufacturing
In industry and manufacturing, AI primarily automates technological processes. It also handles equipment diagnostics and various tasks on assembly lines, helping companies reduce production costs, predict equipment failures, and minimize downtime.
- Siemens, a German conglomerate in electrical engineering, electronics, and energy equipment, uses AI to service its turbines by forecasting equipment failures and optimizing maintenance schedules.
- Major airlines such as Emirates and Delta Air Lines use the industrial software platform Predix for real-time predictive analytics. This AI usage has cut engine repair costs by 15% and reduced flight delays by 30% due to better failure prediction.
- French energy engineering company Schneider Electric employs Robotic Process Automation (RPA) to handle labor-intensive tasks related to preparing documents for switchboard operators and managing supply chains.
Transport and Logistics
In transportation, AI is heavily used in autonomous vehicles. AI processes data from cameras and radars to ensure safe movement. In logistics, AI focuses on optimizing delivery routes, performing analytics and forecasting, and managing warehouse inventories, thereby reducing costs and speeding up business processes. City transport authorities use AI to automatically assign drivers to routes or select buses for deployment on routes, taking passenger flow into account.
- Waymo, a manufacturer of autonomous vehicle technology, actively markets self-driving cars equipped with AI that are already transporting passengers in some U.S. cities.
- DHL, an international express delivery company, uses AI to optimize delivery routes, cutting time and costs. It also employs robotics extensively in warehouses and sorting centers.
AI in Everyday Life
AI and neural networks are not limited to large industries and companies. Millions of users worldwide use AI-integrated apps and services every day, including:
- Smart assistants: Voice assistants like Siri, Alexa, and Google Assistant use AI to process voice commands, answer questions, and control smart devices. They continuously learn to improve speech recognition and personalization.
- Streaming platforms: AI underpins recommendation systems on major platforms such as Netflix, YouTube, Amazon Prime, and Spotify. Algorithms analyze user preferences to suggest content likely to be enjoyed, increasing audience engagement and improving user experience.
- Natural language processing: AI is used in translators and chatbots—for example, translating between languages or providing customer support on airline and software manufacturer websites.
Promising Directions for AI Development
Although AI already handles many human tasks, its potential remains far from fully realized. Future trends in AI include:
- Quantum computing: Quantum computers promise to accelerate data processing dramatically, potentially leading to breakthroughs in AI. They will enable solving problems currently inaccessible even to the most powerful supercomputers, such as molecular modeling for pharmaceuticals.
- Neuromorphic technologies: Neuromorphic chips that mimic the human brain could make AI more energy-efficient and faster, especially valuable for IoT devices and autonomous systems.
Ethical Aspects of AI Application
Ethical issues arise with AI, such as algorithmic bias. Protecting data privacy is also crucial. Developing ethical standards for AI will be a key factor in the further use of neural networks and artificial intelligence.
The Future of Artificial Intelligence
According to some forecasts, by 2030, sectors already actively using AI will grow 3 to 5 times. Digital technology markets where AI is just gaining momentum will grow 6 to 11 times. The main global AI demand will come from retail, medicine, and transport, driven by the development of new solutions that facilitate production processes.
Additional future trends include:
- Mass adoption of robotics: The widespread use of autonomous vehicles, drones, and robots will expand into more areas, including science and education.
- Mass use of AI in education: New platforms will emerge, offering personalized learning tailored to each student’s abilities and creating individualized study plans.
- Development of generative AI: This technology creates text, images, music, conversations, stories, and more. It will be especially valuable for companies engaged in multimedia production, product design, and creative industries.
Limitations and Potential Risks
Rapid AI development and widespread use have introduced many risks, including job losses, data leaks, and AI misuse in criminal and fraudulent activities. To mitigate these threats, some countries are implementing AI regulations. For example, the European Union’s AI Act, effective from February 2, 2025, bans AI systems posing risks to safety, health, or fundamental rights—except for national security cases. It specifically prohibits programs that assess and score human social behavior.
Other limitations include the high cost of development, processing huge data volumes, and high energy consumption.
Conclusion
Today, we discussed various fields where neural networks and artificial intelligence are applied. In today’s reality, AI is everywhere—from algorithms in apps to complex production and healthcare systems. Despite widespread adoption, AI’s full potential is still unfolding, and we must prepare for the broader integration of new technologies into our lives.