Modern technologies are developing rapidly, and neural networks have become one of the main drivers of digital business transformation. They help companies automate routine tasks, analyze huge amounts of data, and improve customer service.
The popularity of neural networks in 2025 continues to grow. According to reports from analytical agencies, more than 70% of small and medium-sized businesses have already implemented at least one AI solution for process automation. In this article, we will look at how neural networks help in various areas of business, which services are the most popular, and which free solutions are available online.
How do neural networks help in different areas of business?
Modern neural networks are becoming an integral part of business processes, helping companies optimize operations, increase efficiency, and reduce costs. Artificial intelligence is actively used in many areas, from automating routine tasks to ensuring cybersecurity. Let's look at the main areas in which AI helps businesses.
1. Automation of routine tasks
Automation using neural networks allows businesses to significantly reduce costs, minimize errors, and speed up the execution of everyday tasks. The introduction of AI technologies frees employees from monotonous work, allowing them to focus on strategically important processes.
Examples of application:
Document processing – AI algorithms can automatically fill out forms, extract data from documents, convert them into digital formats, and check for errors.
Classification and sorting of letters – intelligent systems can filter emails, highlighting important messages and forwarding them to the right departments.
Order processing and warehouse management – neural networks analyze orders, manage inventory, and forecast demand, which reduces the risk of shortages or surpluses of goods.
Automated accounting – AI helps keep track of transactions, forecast payment obligations and automatically generate reports.
Benefits:
- Reduced operating costs.
- Minimized human errors.
- Increased data processing speed.
2. Improving customer service
Quality customer service is a key factor in competitive advantage. Neural networks help businesses quickly interact with customers, providing personalized solutions and reducing waiting times.
Application examples:
Chatbots and voice assistants – tools such as ChatGPT allow you to answer customer inquiries 24/7, process orders, and provide reference information.
Personalized recommendations – based on an analysis of customer preferences, AI offers relevant products and services, increasing sales.
Feedback and review analysis – AI systems can process thousands of reviews, identifying key problems and growth points for a business.
Automatic processing of complaints and requests– neural networks help analyze the content of requests and automatically forward them to responsible employees.
Advantages:
- Improving user experience.
- Increasing the speed of request processing.
- Optimizing the work of the support department.
3. Data Analysis and Forecasting
Modern companies work with huge amounts of data, which can become a powerful tool for decision-making. Neural networks allow you to quickly analyze information, identify trends and predict future events.
Application examples:
Financial analysis and risk management – AI helps predict market fluctuations, manage investments and reduce financial risks.
Demand forecasting – in retail and logistics, neural networks analyze consumer behavior and predict which products will be in demand in the future.
Anomaly detection – AI helps identify deviations in data, which is especially useful in the field of cybersecurity and fraud detection.
Supply chain optimization – by analyzing demand factors, logistics costs and weather conditions, neural networks can find the most profitable logistics solutions.
Benefits:
- Quickly identify trends.
- Reduce risks in decision-making.
- Improved strategic planning.
4. Marketing and advertising optimization
Marketing is becoming more personalized and effective thanks to artificial intelligence. Neural networks allow you to analyze customer behavior, develop customized offers, and improve advertising campaigns.
Application examples:
Content creation – AI can generate advertising texts, write articles, create product descriptions, and even develop video scripts.
Targeted advertising – by analyzing user behavioral data, AI helps find the target audience and display relevant advertising.
Advertising campaign budget optimization– neural networks analyze the effectiveness of various advertising channels and distribute the budget in order to get the maximum return.
Social media and feedback analysis– AI systems analyze publications on social media, identifying trends and audience sentiment.
Advantages:
- Increased conversion of advertising campaigns.
- Reduced customer acquisition costs.
- More precise adjustment of advertising strategies.
5. Improving Cybersecurity
With the development of digital technologies, the risks of cyberattacks and data leaks increase. Neural networks help companies protect their information systems by analyzing threats in real time.
Application examples:
Detecting abnormal behavior on the network – AI analyzes network traffic, identifying suspicious activities, such as hacking attempts.
Fraud prevention – banks and payment systems use AI to identify suspicious transactions and protect users from data theft.
Vulnerability analysis – neural networks help find weaknesses in security systems and offer solutions to eliminate them.
Automated incident response – AI can quickly block suspicious actions and notify responsible specialists.
Benefits:
- Reduced risks of data leaks and hacker attacks.
- Accelerated threat detection.
- Improved security of corporate systems.
Using neural networks in business opens up wide opportunities for companies:
- Automation of routine processes helps save time and resources.
- Improving customer service increases user loyalty.
- Advanced data analysis allows companies to make more informed decisions.
- Marketing optimization leads to increased sales and reduced advertising costs.
- Cybersecurity protects businesses from external and internal threats.
Every year, artificial intelligence is becoming more accessible, and its implementation is a necessity for successful business in the context of digital transformation.
Review of popular neural networks for business
Modern artificial intelligence technologies are rapidly developing, offering businesses innovative tools for automation and optimization of processes. In this section, we will consider in detail the most popular neural network solutions that can be used in various areas of business. We will analyze their main functions, advantages, disadvantages and provide links to services for easy access.
1. ChatGPT (OpenAI)
ChatGPT is a powerful language model from OpenAI designed for generating texts, conducting dialogues, writing scripts, automating responses to customer requests and other tasks. Companies use this tool for customer support, writing content and even creating program code.
Key features:
- Generate responses in real time.
- Creating and editing texts.
- Integration with various business tools and CRM systems.
Pros:
- High accuracy and depth of responses.
- Support for multiple languages.
- Possibility of training and adaptation to business tasks.
Cons:
- Sometimes generates inaccurate or irrelevant responses.
- Paid subscription for access to advanced features.
2. Midjourney (Midjourney)
Midjourney is one of the best neural networks for creating images from text descriptions. This tool is especially popular among designers, marketers and artists.
Key features:
- Generate images of various styles and quality.
- Use text prompts for detailed image customization.
- Ability to edit and improve images.
Pros:
- Create unique, detailed illustrations.
- Suitable for marketing materials, logos, concept art.
Cons:
- Paid access.
- Limited control over image parameters.
3. DALL·E (OpenAI)
DALL E is an innovative tool from OpenAI designed to create visual content based on text descriptions. It features high accuracy and unique artistic styles.
Key features:
- Generate images based on complex text queries.
- Recreate real objects and fantastic concepts.
- The ability to edit generated images.
Pros:
- Ease of use.
- High quality of image generation.
Cons:
- Paid access to advanced features.
- Sometimes images may contain artifacts or inconsistencies with the request.
4. Jasper AI (Jasper AI)
Jasper AI is one of the best tools for automated copywriting. This neural network generates texts for blogs, advertisements, email newsletters and other marketing materials.
Key features:
- Generate SEO-optimized texts.
- Automatic creation of titles, descriptions, meta tags.
- Ability to adapt style and tone to the brand.
Pros: Speeds up the content creation process. Large selection of templates for different types of texts.
Cons: Requires manual editing. Paid subscription.
5. Synthesia (Synthesia)
Synthesia is a powerful tool for creating videos with virtual avatars. The service allows you to quickly create video content without the need to involve actors and a film crew.
Key features:
- Generate videos with avatars that speak a given text.
- Support for multiple languages and accents.
- Ability to adapt the appearance and behavior of the avatar.
Pros:Saving your video production budget. Easy to use.
Cons: Limited character customization. In some cases, animation may look unnatural.
6. Runway ML (Runway)
Runway ML is a universal tool for video processing, animation, and content generation using artificial intelligence. Suitable for designers and videographers.
Key features:
- Automatic background removal.
- Create video clips based on text.
- Generate unique effects.
Pros: Simplifies the video editing process. Supports many file formats.
Cons: Paid access to advanced tools. Requires training for effective use.
7. Grammarly (Grammarly)
Grammarly is an AI assistant for checking grammar, punctuation, and style of texts in English.
Key features:
- Automatic error checking.
- Hints for improving sentence structure.
- Integration with browsers and office programs.
Pros: Improves the quality of texts. Easy integration with popular services.
Cons: Only supports English. Paid subscription for full functionality.
8. Craftum AI (Craftum)
Craftum AI is a neural network that allows you to create websites in minutes using text descriptions. The service automatically selects the structure, fills the pages with content and adds CTA elements.
Pros:Quick creation of full-fledged websites without the need for programming. Built-in SEO settings and responsive design.
Cons:Limited design customization options.
9. Pictory (Pictory)
Pictory is a neural network designed to generate videos based on text descriptions with automatic editing. Suitable for creating marketing videos, training videos and content for social networks.
Pros:Ease of use, no video editing experience required. High content creation speed.
Cons:Limited video customization and editing capabilities.
10. Descript (Descript)
Descript is a powerful tool for automatic audio and video transcription with the ability to edit via a text interface. Suitable for journalists, podcasters and video editors.
Pros: Highly accurate speech recognition. Ability to edit audio via a text interface.
Cons: Limited language support.
11. Gemini (Google Bard)
Google Bard is a neural network from Google, created for writing texts, generating answers to questions and automating work with information. It integrates with Google services, which makes it convenient for use in business. In February 2024, Google renamed Bard to Gemini, introducing it as a more advanced Model II, based on the Gemini family of models
Pros: High accuracy of answers. Deep integration with the Google ecosystem.
Cons: Limited availability in some regions. Potential data privacy issues.
12. Tome (Tome)
Tome is a tool for creating presentations using artificial intelligence. Allows you to automatically select a design, generate text and structure information.
Pros: Simplifies the process of creating presentations. Saves time on preparing materials.
Cons:Sometimes it requires modification for specific requirements.
Artificial intelligence technologies are rapidly developing, and their impact on business is becoming increasingly significant. Neural networks allow companies to automate processes, improve customer service, analyze data with high accuracy and reduce operating costs. Many organizations are already integrating AI into their work processes, and this trend will only gain momentum.
Forecast for the future
In 2025 and beyond, we will see even more examples of successful implementation of AI in business. It is expected that:
AI will become an integral part of strategic management – companies will use the analytical capabilities of artificial intelligence to predict market trends, manage supply chains and optimize business processes.
The development of generative models will lead to new opportunities in marketing and content – improved neural networks will be able to create not only texts and images, but also complex videos, interactive scenarios and personalized advertising campaigns.
The level of personalization of services will increase – AI will offer even more accurate recommendations to customers, adapt to their preferences and improve the quality of interaction.
Cybersecurity will reach a new level – artificial intelligence systems will not only prevent attacks, but also independently adapt to new threats, ensuring a high level of data protection.
Simplification of work with AI tools – thanks to cloud services and SaaS solutions (Software-as-a-Service), the implementation of neural networks will become more accessible even for small companies without significant infrastructure costs.
Why is it important to start implementing AI now?
Companies that start using neural network technologies today will gain a significant competitive advantage. Quick adaptation to new technologies will allow businesses to:
- Optimize costs and improve process efficiency.
- Improve customer interactions through personalized service.
- Automate routine tasks and increase employee speed.
- Anticipate market changes and adapt to them faster than competitors.
As of March 2025, Russia is actively developing its own neural networks, such as YandexGPT (from Yandex) and GigaChat (from Sberbank).
Summary
AI has already become an integral part of modern business, and its role will only increase. Organizations that are the first to start using neural networks in their processes will not only receive cost reduction and increased efficiency, but also leadership in their niche. It is important not to miss the moment and study the possibilities of artificial intelligence today to prepare for the future of digital transformation.
