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without AI, new levels of productivity in oil and gas are unattainable / News of the economy of Krasnoyarsk and the Krasnoyarsk Territory / Newslab.Ru

Photo of Ashley Davis Ashley Davis10/10/2025
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10 October 10:33

Since 2022, the number of Russian oil and gas companies using AI has doubled and amounted to 58%. According to the Ministry of Energy, by 2027 the penetration level of neural network technologies will reach 70%. The growing interest is explained by the fact that businesses are striving to increase oil recovery and effectively launch new fields. In the refining segment, AI penetration has grown by almost 50% over the past three years, and in exploration and production technologies have shown an annual increase of about 14% since 2022.

According to a study by IT holding T1, the oil and gas industry ranks second among other industries in terms of spending on AI. In 2024, investments in neural network technologies and equipment reached 2.9 billion rubles. The high level of technology penetration, according to T1 experts, is due to the fact that the use of AI can reduce production costs by 10–15%, as well as ensure higher business sustainability and adaptability.

Most often, with the help of AI, businesses solve issues in the field of security (this priority was identified by 62% of companies), business administration (49% of companies) and to optimize production processes (43% of companies). Also, tools based on neural network technologies are used in logistics, marketing and HR activities.

The most common types of AI technologies in Russian oil and gas companies are:

  • computer vision (used by 73% of industry companies);

  • natural language processing (62.2%);

  • new AI technologies (54.1%)

  • intellectual support for decision making and management (45.9%);

  • speech recognition and synthesis (40.5%).

According to T1 experts, the drivers include: strengthening the role of Russian developers, the development of cloud solutions and integrated platforms, as well as strengthening regulatory requirements for cybersecurity.

“The industry has moved from the stage of AI experiments to mass implementation. We are seeing a dramatic strategic shift from chasing innovation for innovation's sake to focusing on real economic returns and security. In the coming years, it is the integration of intelligent solutions with existing production systems that will become a key test of industry maturity,” said Sergei Golitsyn, head of T1 AI.