At the International Scientific and Practical Conference “Artificial Intelligence in the field of antimonopoly regulation in the EAEU space,” held on February 17 at the Faculty of Law of Lomonosov Moscow State University, Alexey Ivanov, Director of the BRICS Competition Centre, discussed the potential of AI to transform antitrust work. The event was organized by Moscow State University and the Competition Unit of the Eurasian Economic Commission (EEC).
Today, artificial intelligence (AI) receives heightened attention: governments are passing specialized laws, developing AI strategies, and even creating AI ministries, as in Kazakhstan. In this context, antitrust authorities around the world are also implementing AI in their work. As noted by Maksim Yermalovich, Minister in charge of Competition and Antitrust Regulation of the Eurasian Economic Commission, AI can become a key tool for market analysis, cartel detection, automation of routine processes, and applying a risk-oriented approach to monitoring cross-border supplies and public procurement.
According to Sergey Puzyrevsky, Deputy Head of the Federal Antimonopoly Service of Russia, the digitalization of the economy is irreversible: by 2025, the turnover of Russian marketplaces exceeded 11 trillion rubles — about 5.5% of GDP — with over 6 billion orders, and this structural transformation of markets poses new challenges for regulators.
In the photo (from left to right): Veronika Illarionova, Sergey Puzyrevsky, Maksim Yermalovich, Evgeny Gubin, Vasilii Gromov © HSE University
“As an antitrust authority, we must mitigate AI-related risks, but we should not forget that AI also provides many benefits, allowing us to access a large number of price offers and better navigate the pricing space,”
he noted.
Alexey Ivanov Director of the BRICS Competition Centre, emphasized that while AI-driven monopolization represents a major challenge for competition policy, the same technologies can radically increase the efficiency of antitrust authorities themselves. He identified two systemic problems hindering regulatory development: fragmentation and poor analytical processing of data within agencies, and insufficient interagency and international information exchange. Consequently, regulators objectively lag behind global companies that actively consolidate and analyze large data sets to strengthen their market power.
As a solution, Ivanov proposed moving to the use of anonymized, aggregated data and creating an AI agent for antitrust authorities. Such a tool would enable not only analytical but also predictive insights, taking context into account — particularly important in antitrust analysis.
“This is about transitioning from fragmented, legally segmented data usage to aggregated and functionally meaningful application. Considering context in antitrust analysis — macroeconomic factors, diverse changes, trends, and even geopolitical situations — is always extremely complex. Many decisions in antitrust cases and investigations are based on classical methods for assessing market competition, which often insufficiently account for context, creating serious limitations on analytical quality and decision-making,”
he explained.
In the photo: Alexey Ivanov(on the screen), Maksim Yermalovich, Evgeny Gubin, Vasilii Gromov © HSE University
Ivanov also highlighted the idea of a “merger radar”— a system to monitor economic concentration processes, including strategic partnerships such as Microsoft–OpenAI, which may not formally qualify as classic deals but effectively reshape markets. He noted that existing procedures and the inertia of administrative thinking (“path dependency”) hinder modernization, and suggested using a technological leap — active AI adoption and automated data processing. Anonymizing information, he stressed, allows regulators to maintain confidentiality while significantly expanding analytical capabilities.
Ivanov concluded that delaying digital transformation carries a cost: while large companies have long operated in automated, global data environments, antitrust authorities risk remaining dependent on manual analysis. He emphasized that AI can bridge this gap and enable a more proactive, rather than reactive, competition policy.
Other speakers also addressed AI’s practical applications. GIS “Anticartel,” a specialized digital platform designed to detect and prevent anti-competitive agreements, was presented by Veronika Illarionova, Deputy Head of the Anti-Cartel Department at the Federal Antimonopoly Service of Russia. The system relies on big data and AI technologies, and machine learning algorithms enhance regulatory efficiency and accelerate the detection of violations.
Alexander Kurdin, Deputy Dean, Faculty of Economics – Lomonosov Moscow State University, Head of the Digital Economy Research Laboratory, raised the issue of balancing cooperation and competition in the digital economy given AI development. He noted that for economic growth, competition does not have to be intense, and high concentration in the digital economy, considering AI, can also be acceptable.
“Nevertheless, digital giants cannot be left alone — competition is important for frontier firms. At the same time, undermining incentives for super-profits through over-regulation can be risky for innovation,”
he emphasized.
Vasilii Gromov, Deputy Head, Professor, School of Data Analysis and Artificial Intelligence at the Faculty of Computer Science, HSE University, spoke about analyzing market processes using AI tools.
“The digitalization of the economy has significantly increased the number of transactions, primarily by reducing transaction costs. This trend is not yet fully realized, but in the coming years, as AI develops and can independently identify transaction participants, the number of transactions may grow exponentially, and we need to be prepared for this in advance,”
he noted.
© HSE University
Andrew Parinov, Chief Expert at the Centre for Language and Semantic Technologies, HSE University, discussed AI applications in detecting cartel agreements. The report “Analysis of AI Applications for Competition Protection in the Use of Digital Platforms” was presented by Louiza Khanchukaeva, Head of Antitrust Law at Samokat and Lecturer in the Master’s Program in Competition Law at the Faculty of Law, Moscow State University, and Maria Tuktarova, Head of Legal Support for Intellectual Property and IT at Samokat, patent attorney, and invited lecturer at HSE (St. Petersburg).
At the conclusion of the conference, Maksim Yermalovich noted that the discussion revealed more problems than expected, but “strangely, each of them has a solution.” He emphasized the need for a practice-oriented approach: initial market analysis in EAEU antitrust authorities and the Eurasian Economic Commission could be conducted without major financial costs, relying on the participants’ collective expertise, and proposed scheduling another joint AI-focused conference in the second half of the year.
The conference brought together representatives from antitrust authorities, Lomonosov Moscow State University, Saint Petersburg State University, HSE, and business stakeholders.
