Artificial intelligence is already replacing some analytical and information-related functions, but productivity growth in itself does not automatically mean a reduction in employment. On the contrary, technological development can create new demand for goods and services and thereby generate a need for additional specialists. This was stated by economist Edward Sandoyan during the roundtable discussion “AI in Science and Industry: Challenges and Opportunities,” organized as part of the JINR Days in Armenia.

According to him, a significant share of analytical work is already being automated in the university environment, in particular the preparation of literature reviews, the collection and summarization of information, as well as certain functions related to process analysis.

Sandoyan noted that modern generative systems make it possible to complete in a matter of minutes tasks that just a few decades ago required a substantial amount of professional work. As an example, he cited the preparation of business plans: at the beginning of his career, he himself earned money by developing them as an economist, whereas today a similar task can largely be handled with the help of ChatGPT.

In the economist’s view, this demonstrates the scale of the changes taking place in the intellectual labor market. AI is gradually taking over functions that previously required a qualified specialist; however, the consequences of this process for the economy cannot be reduced solely to the disappearance of jobs.

Productivity growth does not necessarily reduce employment

Sandoyan draws attention to the historical experience of technological development. According to him, for decades the IT sector has repeatedly seen forecasts about approaching market saturation and declining demand for computing power. However, each new stage of technological development, on the contrary, led to an expansion of their use and created demand for even more powerful computers.

Therefore, the economist believes, increasing labor productivity through AI will not necessarily lead to a reduction in the overall volume of work. He cites the development of software as an example: it multiplied labor productivity many times over, but did not lead to the disappearance of the need for specialists.

Sandoyan links this to the effect of expanding demand: when technological development makes certain services more accessible, they begin to be consumed in much greater volumes. As a result, the need for specialists who provide these services also grows.

He gives medicine as an example. The expansion of AI capabilities in diagnostics and patient care may make medical services more accessible and increase the number of people who can receive continuous medical support. In such a case, automating certain functions of a physician will not necessarily mean a proportional reduction in the need for doctors.

AI and a new model of income distribution

At the same time, large-scale automation of intellectual and physical labor inevitably raises the question of how the value created by the economy will be distributed. Sandoyan notes that mechanisms such as universal basic income and deeper modernization of the system for forming state budgets are already being discussed. In conditions where a significant share of production and analytical functions can be automated, the economic system will have to adapt to the changing role of labor in income generation.

Thus, the key question becomes not only which professions AI will be able to perform, but also how the results of productivity growth will be distributed among economic actors and the population.

During the roundtable, the issue of a potential limitation on the large-scale spread of AI was also raised — a possible shortage of energy resources. The mass introduction of robotic systems and the increase in computing power will require significant growth in electricity generation, participants in the discussion noted. Necessary raw materials and rare earth materials for technological equipment may also become a limiting factor; however, the economist identifies the energy factor as the most significant.

According to Sandoyan, even now the development of AI is simultaneously stimulating the search for new energy sources and improving the efficiency of the existing energy infrastructure. In Sandoyan’s view, the expansion of renewable energy use and the development of new technologies will accompany the further digitalization of the economy.

Thus, the impact of artificial intelligence on the economy will be determined not only by the speed of automation of certain types of activity. The outcome will also be influenced by growing demand for new services, redistribution of income, changes in the structure of employment, and the availability of resources necessary for further technological development.