The digitalization of the economy poses new challenges for economic science, which must take into account new factors that have not previously mattered. We are talking about qualitative changes in the economy and new tasks of economists facing the emergence of the data economy with Viktor Abramov, Doctor of Economics, Professor of the Department of Business Project Management at NRNU MEPhI.
– Viktor Ivanovich, can we talk about the qualitative transformation of the economy taking place before our eyes?
– There are very significant, radical changes in the economy. First, the concept of “digital economy” appeared – in our country, there is such a national project, since 2025 called “Data Economics.” This renaming itself is significant: data today is becoming an independent production resource and the driving force of socio-economic development – just like land, labor and capital. I am a physicist by education, graduated from MEPhI with a degree in theoretical physics, and defended my Ph.D. thesis in atomic nucleus physics. So, in physics, we study objects that remain the same for millions of years: Newton’s laws, Maxwell’s equations, the principles of quantum mechanics do not become obsolete and do not require revision – they remain an unchanged basis regardless of the technological context of the era. At the same time, everything that is happening now in the economy is qualitatively changing what happened before.
Previously, relatively speaking, the economy was predictable and linear, changes occurred gradually. However, today it is becoming non-linear, and this is due to the rapid development of information technologies: the pace of their development significantly exceeds the speed with which business and management manage to master them. Accordingly, a lot of “blind spots” are formed – situations when we do not yet realize what exactly is happening. This is not a market gap and it is systemic. “Economic elevators” have appeared – some digital economic giants today have capitalization under a trillion dollars. This unpredictability makes what is happening not only important, but really exciting – both for the researcher and for the practice. It is very interesting.
– Can we talk about any key elements of the ongoing changes?
– At the last SPIEF, Russian President Vladimir Putin spoke about the importance of platform development – and this is no coincidence. We see how marketplaces took off: the growth rates of Ozon and Wildberries until recently exceeded 40% per year. This is explained by the fundamental properties of platform business models – scalability and network effects, when the value of the system increases non-linearly with the number of participants. Marketplaces have the highest market power today.
The second key element is big data and AI as the technological basis for this entire transformation. The volume of world data is growing exponentially: if in 2010 it was about several zettabytes, then by 2028 multiple tenfold growth is expected. At the same time, 90% of all accumulated data is unstructured or semi-structured – and it is AI that opens up the opportunity to extract economic value from this previously “dead” resource.
The third most important element, especially relevant for the industrial sector, is digital twin technologies. A digital twin of an enterprise or a technological process is not just a mathematical model, but a dynamic system that communicates in real time with a physical object and can significantly improve the quality of management decisions. According to analysts, the introduction of digital twins can increase the operational efficiency of industrial companies by 15-35% due to predictive maintenance, reducing equipment downtime and optimizing resource consumption. This is the very bridge that connects the data economy with real production.
According to the calculations of leading digital companies, if end-to-end digital technologies are actively used in Russia, it is possible to reach a GDP growth rate of 7%.
– From this we can conclude that they are still not used enough?
– End-to-end digital technologies are actively used, but the potential remains large. McKinsey estimates that fully unleashing the economic potential of generative AI can create tens of trillions of dollars in added value globally, and this is just one element of this system.
What is really not enough today is digital money. In my understanding, digital money is a closing end-to-end digital technology, a kind of “last mile” of digital transformation of the economy. Judge for yourself: we have already switched a lot to dynamic mode – data is transmitted and processed in real time, platforms instantly adapt to user behavior, logistics are controlled algorithmically. However, our money is still static: ordinary money is just numbers in the account, it does not carry any built-in logic, no execution conditions. Tokenized money, including central bank digital currencies (CBDCs), stablecoins and tokenized commercial bank deposits, can be programmable: money itself “knows” under what conditions it should move from one participant to another, which radically reduces transaction costs and excludes intermediaries from a number of operations. That is why tokenization of money is not just a fintech innovation, but a backbone element of a mature digital economy. Only when money becomes as “alive” and programmable as data and platforms, the digital economic system will close into a full-fledged circuit, and then the full potential of end-to-end digital technologies can be fully realized.
– What does it mean?
– This means that we can measure the amount of money only at certain points in time. Each ruble is impersonal and “integrated” into the total amount on the account – we do not know where it came from, and we cannot set the conditions for its use. In the paradigm of digital money, there is a unique opportunity to manage flows, not amounts. The digital ruble is the same money, but each ruble has an individual mark, like the serial number of a banknote, and is implemented through the blockchain as a programmable object. We can track its path at any time. Of course, many fear total transparency – but digital money does not cancel either cash or non-cash payments. However, for the state, an effective mechanism of “colored” money appears: you can check whether the subsidy has reached the recipient, whether the budget grant has been mastered for its intended purpose. For corporations, this is the automation of settlements in supply chains. For the population – a convenient tool that will eventually open access to a wide range of token services. This is a transition to the dynamic logic of financial relations.
– What do you mean in this case by tokens?
– A token is essentially a digital asset with an individual label. For ordinary assets, such as stocks, the value is measured by money at a certain point in time – these are static assets, like non-cash money: we see only a “snapshot” of their value at a particular moment. Tokens are fundamentally dynamic assets that function in the logic of smart contracts: their owners can agree on the rules of interaction in advance, fix these conditions in the code, and the system will automatically execute exactly what the parties agreed on – without intermediaries, without the possibility of unilateral violation of agreements. Depending on the purpose, payment tokens, utility tokens and asset tokens are distinguished, each of which performs its function in the digital economic system.
– Why is this important?
– First of all – because it radically reduces transaction costs, eliminating entire intermediary links. Bitcoin and cryptocurrencies are considered by many to be a fraud tool. In reality, their demand is explained by the objective need to work in dynamic mode. The emergence of central bank digital currencies (CBDCs) is the right, but too long, answer to this need, with more than 134 countries already researching or implementing CBDC projects. In Russia, there is a clear delay with the digital ruble, although, for example, in China, the pilot project of the digital yuan e-CNY already reached in 2024 over 180 million users. One of the arguments against scaling the digital ruble is the lack of computing power to serve 140 million Russians. But Chinese experience shows that this is a technically solvable task.
– In addition to technical restrictions – what prevents Russia from quickly introducing digital rubles and tokens based on them?
– There are two main problems: the lack of mature legislation and the lack of a systemic blockchain infrastructure, although abroad large corporations are already actively using blockchain. Nevertheless, there is a deeper problem – institutional. The use and development of digital technologies and digital business models requires an environment of trust. Russian business is only about 35 years old, and a culture of trusting business relations is still being formed. Meanwhile, this is the key property of the blockchain: it allows to create trust environments technologically, without requiring pre-established relationships between participants. This property must be used to increase the efficiency of Russian business.
– What is the task of science in relation to these phenomena?
– Classical economics studied mainly the past – analyzed what had already happened, and extrapolated these patterns into the future. However, today we are facing a gap: the future is changing so rapidly that past experience has become irrelevant to the environment in which we already live and work. Therefore, a fundamentally different logic is needed – managerial decisions must be made in logic not from the past, but from the future.
This is especially important in the context of innovation. Product innovation gives from 10 to 30% additional profit. Business process innovation is about the same. But the innovation of the business model is able to ensure profit growth by more than 100% – this is exactly what Amazon demonstrated, and in Russia Ozon and Wildberries. They implemented a network business model based on a digital platform, and this network logic with its scalability and network effects ensured explosive growth. Science will have to answer the question: within what business models and rules of the game is it possible to maximize the potential of data and platform technologies to increase the efficiency of the economy as a whole?
– But Ozon and Wildberries are ready-made business models that can be copied.
– It is really possible to copy Ozon or Wildberries in technical terms, but it will not be possible to achieve their success by simple copying – network business models have an important feature: their main asset is a huge base of participants and an established environment of trust. It is impossible to copy it. Therefore, competing with them, creating just another marketplace, is pointless. In my opinion, the future lies in moving to the next stage: digital business ecosystems.
– What’s the difference?
– There are enough differences, but fundamental ones are these questions: where is the profit formed and who is its owner? On the platform, profits are concentrated on the platform owner, and he determines the rules of the game. In the ecosystem, regulations allow many participants to earn money at the same time – many enterprises compete for the client according to general rules, without the exclusive rent of the orchestrator, but with access to the general client analytics of the ecosystem.
The very concept of “ecosystem” entered the business not by chance: the forest after the fire is quickly restored. In a turbulent economy, business ecosystems have similar stability. Science must answer: how to build network economic relations so that the maximum number of participants benefits? These questions are especially interesting to me today – and they are what I do.
– Where are these phenomena studied at MEPhI?
– I work at FBIUKS, and we study these phenomena as part of the course “Digital Transformation of the Economy.” I would like to note that modern engineers also need to understand the economic component of their activities. MEPhI says a lot about startups. However, starting a project and scaling it to serious economic efficiency are different tasks. Without understanding how to create value for customers and monetize it, a startup will remain an idea on the shelf. Modern education should provide an understanding of the possibilities of the hybrid environment in which we live: today 67% of the world’s inhabitants use mobile Internet, in Russia this figure is even higher. The world has become both physical and virtual. The same digital twins in production clearly prove this. It is impossible to ignore its digital dimension. At the same time, the challenge for education is deeper than just adding new disciplines: the speed of technology for the first time in history exceeded the speed of their development by the academic system. The answer should be a paradigm shift – from the transfer of a fixed set of knowledge to the formation of a metacompetence of continuous learning. The university of the future should prepare a specialist who knows how to master new tools, embed them in business logic and create value on their basis. This is exactly what we are trying to do at our faculty, involving students in work on real digital transformation projects.
By Konstantin Frumkin