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Main article: Artificial Intelligence
Directions of AI application in industry
In 2024, Spydell Finance identified the following areas of application of AI in industry:
Deep automation of production processes with dynamic efficiency control
AI can contribute to the development and implementation of higher-level automated and robotic systems than in current ACS.
Risk and Safety Management
Risk and safety management, including predictive maintenance. Review process safety and risk data, helping to identify potential hazards and propose measures to mitigate risks, including using preventive measures to address emergency situations and replace and/or maintain equipment.
Optimization of production processes, resources, including supply chains and logistics
Analyze process data to optimize efficiency and reduce costs. This includes inventory management, production planning, equipment maintenance, and power consumption. AI can optimize logistics and supply chain management by analyzing data on demand, inventory and transport flows, which increases efficiency and reduces costs.
Product Quality and Process Control
AI can analyze data from production lines to control product quality, identifying defects and inconsistencies, which contributes to improving the overall quality of products.
Energy Management and Optimization
A more efficient distribution of energy resources reduces losses and excess or insufficient production, dynamically adjusting to demand.
History
2025
Machine vision began to be assisted by machine hearing in industry. Rusal has developed and implemented a new technology
The aluminum company Rusal first launched the technology of machine hearing in commercial operation to optimize the operation of mills in alumina production. The mathematical algorithm analyzes the vibroacoustic signals of the equipment and automatically regulates the loading of bauxite ore, which allows you to reduce wear and tear of mechanisms and reduce electricity consumption. The development was created by the RUSAL Engineering and Technological Center, and the tests were successfully completed at the small wet grinding unit of the Rusal Krasnoturinsk alumina plant on September 2, 2025. Read more here.
How generative AI is used in industry in Russia
The main part of projects on the use of generative artificial intelligence (GENI) falls on the optimization of business processes. At the same time, there is a significant increase in interest in its use in key production processes of industrial enterprises. This trend allows you to solve more complex industry problems and optimize key operations that directly affect performance and product quality. How Genii is used in industry in Russia is described in the material of the Center for Expertise and Commercialization of Information and Financial Technologies of the Skolkovo Foundation, which TAdviser got acquainted with in mid-August 2025.
In particular, Genii is used in the field of research and development. Thus, SIBUR, together with Sber and the CST, is implementing a project to model polymers and create materials with new properties. The goal is to predict the polymerization process and the properties of polymers, model formulations, additives, influence on the physical and mechanical properties of the material and finished products. Analysis of historical data, identification of key factors of influence on polymer characteristics at all stages and optimization of production modes for new products are carried out. Thanks to Genia, a significant reduction in time and scope of work is achieved.
Sberbank also takes part in a project with R-Pharm in the field of pharmaceuticals. It is noted that one of the most time-consuming phases in the creation of original drugs is the development of a molecule structure with the required characteristics that allow achieving the best performance and safety indicators of the future drug. As a rule, only this stage takes about two years of work of specialists.
Experts from the Sberbank Artificial Intelligence Laboratory and R-Pharm have developed an AI solution for generating antibodies, which potentially reduces this phase of work to two months. Another 10 months should take synthesis and confirmation of the properties of the generated structures in the so-called "wet" laboratory "R-Pharm."
At the same time, Rosneft and ITMO University have created a solution for the conceptual design of port industrial and logistics complexes in the Arctic zone using generative design methods. Its goal is to assess the potential for the development of the territory and the choice of basic technical and architectural solutions. The system is implemented as a client-server application with a module for 3D visualization. It uses AI algorithms to quickly generate many alternative scenarios (digital models) for the development of the territory based on various inputs and conditions. In this case, operational and extreme environmental parameters, such as temperature, wind, excitement and ice characteristics, are automatically taken into account.
KEAZ is implementing a project to optimize technological processes. The company is testing an AI and machine vision-based recommendation system that recognizes movements, identifies patterns of behavior and issues recommendations. The result is a 30% increase in labor productivity. In turn, the Дом.РФ Foundation and the Rocket Group company developed the first digital development concept using the rTIM AI platform.
Another project is being implemented by specialists: T-bank the first AI assistant in Russia is presented - the information security system. Safeliner Its technology is built on the analysis of potential vulnerabilities discovered by static analysis tools. Safeliner filters false positives, generates hints and descriptions of security problems that developers understand.[1]
2024: Growth in the number of enterprises in Russia using generative AI by 42% to 265 industrial enterprises
By the end of 2024, 265 industrial enterprises used generative artificial intelligence (Genii) in Russia. This is 42% more than in the previous year, when 187 companies applied such decisions. Relevant data are provided in the Strategy Partners review published on November 5, 2025.
The introduction of Genii in the industrial sector of the Russian Federation is at the initial stage. The penetration of technology among industry organizations as of 2020 was estimated at 0.1%, and by 2024 the figure rose only to 0.3%. The use of GeniI ensures the optimization of operating costs, as well as improving the quality of services.
The emergence of domestic large language models (LLM), as well as products based on them, has a positive impact on the market. In addition, the expansion of the industry is facilitated by the development of the Russian infrastructure for cloud computing GPUaaS (graphics accelerator as a service). The authors of the study identify six key scenarios for the use of Genia in Russia.
1. Assistants and Agents Based on AI
Based on corporate templates and databases, such systems perform routine operations and act as chatbots. AI agents use machine learning to collect and process large amounts of information in real time, helping organizations make better decisions at different levels of management.
2. Generative Engineering
We are talking about using topological optimization algorithms and multi-criteria modeling to generate CAD design options based on strength, weight and cost. This approach accelerates R&D (R&D) by allowing engineering teams to focus on final solutions.
3. Intelligent Process Optimization
By analyzing historical and current data, Genia automatically identifies inefficient operating algorithms and proposes specific changes (order of operations, equipment parameters, routes) to improve processes.
4. Synthesis of data for machine learning
GeneAI is capable of creating photorealistic images and various sets of information, providing training for predictive analytics and computer vision models.
5. Autonomous Digital Twin
A Genia-based system can automatically generate what-if scenarios for a digital twin, predict deviations, dynamically calculate and independently adjust the operating parameters of a physical object.
6. Federated Model Self-Learning
AI systems are additionally trained in local mode at the levels of the workshop, enterprise and holding, transfer only parameter updates for aggregation to the center: this increases the accuracy of the model used. LLMs trained on enterprise templates are able to quickly search internal libraries, as well as generate instructions, specifications and test reports, guaranteeing a single style, completeness of data and a tracked change history.
Conclusion
In 2025, the number of Russian industrial enterprises using Genii tools is expected to reach 371. Stimulating factors are the introduction of AI assistants in supporting processes, the adaptation of AI to the tasks of R&D and partial operational management, the emergence of industry standards for data collection and processing, as well as the development of domestic digital solutions. The industry may be negatively affected by the lack of budgets for digitalization and the technological lag of Russia in the field of hardware solutions.[2]
2023: Why is artificial intelligence difficult in industry?
The manufacturing industry worldwide is one of the most promising areas for the introduction of artificial intelligence technologies. In Russia, the current statistics are not so positive. According to experts, IT solutions based on AI are used in many enterprises inexpediently. Factories, introducing new technologies into their production, often do not change business processes - therefore they do not see efficiency. Why this happens, says Andrey Zakharov, Datana product director . Read more here.
2020: The center "Artificial Intelligence in Industry" will appear in St. Petersburg
In early November 2020, the Governor of St. Petersburg, Alexander Beglov, signed a decree on the creation of the Artificial Intelligence in Industry scientific and educational center in the city, which will develop and introduce AI technologies for the needs of the Russian economy.
 | Our task is to contribute to the emergence in St. Petersburg of scientific organizations that will conduct world-class research and development. In addition to the center "Artificial Intelligence in Industry," we have a REC in the field of 5G networks and promising networks 2030, a scientific and educational center "ITMO Highpark" is being created, - said the governor. |  |
It is noted that the document was developed in order to implement the decree of the President of Russia "On the national goals and strategic objectives of the development of the Russian Federation for the period up to 2024" and in accordance with the decree of the Government of the Russian Federation "On measures of state support for world-class scientific and educational centers based on the integration of educational organizations of higher education and scientific organizations and their cooperation with organizations operating in the real sector of the economy."
According to the press service of the city governor's administration, a world-class scientific and educational center is an association (without a legal entity) of federal state universities and (or) scientific organizations with enterprises in the real sector of the economy.
His activities are aimed at ensuring world-class research and development, obtaining new competitive technologies and products and their commercialization, as well as training personnel to solve large scientific and technological problems in the interests of developing the branches of science and technology according to the priorities of the scientific and technological development of Russia, the head of the city said in a statement.[3]
Notes
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