Nowadays, it is impossible to imagine the development of IT products without AI tools. Artificial intelligence holds a high position in improving code quality, accelerating development, testing, and project management. In addition, AI tools help to automate routine tasks, increase development productivity, and even participate in creating new solutions.

In this article, we will analyse which AI tools are most in demand in the IT industry, how they help in the creation and development of new products, and what tasks they solve in order to achieve the goals of IT companies.

AI assistants, also known as "copilots," are tools that help with the daily work of creating IT products. They correct errors, optimise algorithms, and provide suggestions and best solutions. The advantage of AI assistants is that they help professionals save time and focus on the creative development process.

Auto completion and hints
Copilot analyses the written code and, based on the context, suggests options for continuing, automatically filling in the code lines. This can significantly speed up the development process, especially for routine operations or when a developer is looking for a solution to a standard task (such as connecting to a database or creating an interface).

Error and bug prediction
It can not only help you write code, but also immediately suggest possible fixes for errors that may occur. Copilot analyses the code for potential bugs or flaws and suggests optimal solutions.

Auto-generation of functions and methods
If a developer does not know how to implement a specific function or method, Copilot can generate this code by simply providing a task description. For example, you can write a comment like "create a function for image processing," and Copilot will suggest a ready-made code for this.

Learning and implementing best practices
Copilot is trained on a vast amount of source code and documentation, so it knows the best practices and patterns that are widely used in development. This helps not only to speed up the process but also to improve the quality of the code.

Assistance with documentation and comments
Copilot can generate comments for the code, making it much easier to understand and maintain. This is also useful for automatically writing documentation, especially for functions that may require detailed descriptions.

Support for different programming languages
Modern copilots can work with multiple programming languages, from Python and JavaScript to Go and Rust. This allows them to be used not only for specific tasks, but also for working on various projects.

The benefits of a copilot include:

• Time savings - employees spend less time on repetitive tasks
• Quality improvement - AI helps to avoid common mistakes and suggests optimal solutions
• Learning - For novice developers, Copilot is an excellent tool for learning and understanding the code structure

AI tools for all stages of software development
AI tools are divided into different categories, each of which helps to solve specific tasks in the creation of IT products. Currently, AI tools are taking over completely different areas. We will focus on such blocks as: analytics, interface design, software architecture design, software development, and software testing. In each block, we will take a closer look at the AI tools that support them, their functions, and tasks.

Analytics is one of the key disciplines in the IT industry at the moment. It helps to make strategic decisions, studies the collection, processing, and analysis of data obtained from various sources, and then selects only useful information for decision-making. Analytics helps companies to optimise processes, predict trends, and improve business efficiency. The main AI tools that help analysts and perform specific tasks are:

ChatGPT and similar Al-assistants. Such assistants allow analysts to quickly generate specifications, describe business processes, and analyse and structure large amounts of information. Tasks:

• Generation and analysis of requirements
• Automation of technical documentation
• Search and summarisation of information
• Generation of reports and recommendations

GitHub Copilot and CodeWhisperer. These tools help with coding, writing more optimised SQL queries, automating routine calculations, and quickly analysing data. Tasks:

• Automating SQL query writing
• Generating code for analytical scripts
• Providing data insights

Tableau GPT and Power Bl Copilot. Integrating AI into BI platforms allows analysts to find hidden patterns, generate reports, and visualise data with minimal effort. Tasks:

• Automatic data analysis
• Visualisation and creation of interactive dashboards
• Generation of data-based insights

DataRobot and H2O.ai . These tools allow analysts without deep knowledge of machine learning to develop predictive models and use them for business analytics. Tasks:

• Automatic construction of machine learning models
• Predictive analytics
• Analysis of trends and anomalies

Notion Al and Confluence Al. AI assistants built into knowledge management platforms help analysts keep documentation up to date, generate reports faster, and collect information on projects.[Разрыв обтекания текста]Tasks:

• Automation of documentation creation
• Generalisation and structuring of information
• Analysis and creation of notes

Interface design is the creation of the visual part of applications, websites. It includes the following stages: research, user scenario, interface structure, prototyping, style definition, design concept, design of all screens, interface animation, and preparation of materials for developers. These stages affect the user's perception, the usability of the product, and the level of engagement. With the help of modern tools, designers create high-quality interfaces, test their usability, and provide mockups to developers. The main tools that assist designers are:

Figma + Plugins c Al. These are among the most popular tools used by interface designers. Tasks:

• Auto-generation of interface elements
• Selection of color schemes, creation of layouts
• Acceleration of prototype creation

Uizard
Uizard helps in creating prototypes from scratch based on text descriptions.
Designers can enter text queries, and the system will generate interfaces that match the specified parameters. Uizard helps to quickly turn ideas into layouts and prototypes, saving time and effort.

Runway
This is an AI platform that helps designers generate images, videos, and other graphic elements. You can use Runway to create videos and other graphic elements. With Runway, you can create unique images for interfaces and even animations that are perfect for specific user scenarios.

Logojoy (or Looka)
AI is used to create logos and branding, which generates unique and stylish logos based on brand preferences and data.
It is an ideal tool for designers who need to quickly create a visual brand identity.

Magenta Studio
This tool uses AI to generate music and sound elements, which can be useful for interface designers who create interactive and multimedia applications. Artificial intelligence helps in creating sound design, which enhances the user experience.

Adobe Sensei
Integrated with Adobe products (Photoshop, Illustrator, etc.), Adobe Sensei uses AI to automate various tasks. For example, it can recognise objects in images, provide recommendations for improving visual elements, and help designers quickly edit and process photos and images.

Software design (SD) is a development phase that is considered the so-called foundation, on which the structure of the future system is built. Software design uses tools to avoid many problems during the development and operation process. Software designers model architecture, describe processes, and manage technical documentation. Tools that help in software design:

Here is a list of the most effective AI tools for software design:
ruGPT (based on ChatGPT 3.5 and 4)

Advantages:

• In-depth architecture analysis
• Technical documentation generation
• API design assistance
• Existing solutions optimisation

Features: support for multiple programming languages, including Java, Python, JavaScript

Chatinfo
Advantages:

• Automatic architecture documentation
• Code analysis and optimisation
• UML diagram generation
• Database design assistance

Features: 24/7 availability, high-precision responses

Pixel Tools Advantages:

• Technical documentation generation
• Performance optimisation
• Help with interface design
• SEO-optimization of documentation

Features: support for 24 languages, high-precision generation

GPT-tools

Advantages:

• Automatic code refactoring
• Test generation
• Micro-service design
• Optimisation of architectural solutions

Features: integration with popular IDEs

MitupAl

Advantages:

• Requirements analysis and architecture generation
• Help with REST API design
• Architecture-based code generation
• Performance optimisation

Features: support for modern frameworks

Practical recommendations for use:
1. For the initial design:

• Use ruGPT or Chatinfo to create a common architecture
• Generate UML diagrams using Chatinfo
• Create technical documentation

2. For detailed design:


• Use GPT-tools to work with specific components
• Use MitupAl to optimise performance
• Check the code for compliance with the architecture

3. For documentation:

• Use Pixel Tools to create technical documentation
• Automate the creation of README files
• Generate documentation using API

4. For optimisation:

• Use all the tools for performance analysis
• Use refactoring capabilities
• Optimise databases

It is important to remember that these tools are auxiliary and should be used in combination with the experience of a software architect.

They help to speed up routine tasks and provide new ideas for design, but the final decision always remains with a person.
When choosing a specific tool, it is recommended to:

• 1. Test several options
• 2. Consider the specifics of the project
• 3. Evaluate integration with existing tools
• 4. Check the support for the required programming languages
• 5. Ensure safe use