The so-called artificial general intelligence, ‘the holy grail’ of AI-related technology, will be able to bring explosive growth. However, it is impossible to predict how fast will be the path from the as-is of artificial intelligence to the target status.
The reduction of major tech companies’ indices, which happened on August 5, was one of the key causes of the serious crash in the global stock markets. The stock markets of Asian countries (Japan, South Korea and Taiwan) and regions stood out. For example, the Korean KOSPI stock market index lost 8.8 per cent breaking the anti-record of the crisis 2008 autumn season. And, despite the stock markets bounced back on August 6, investors are still expecting new decline waves.
The American NASDAQ stock exchange can efficiently contribute to the next wave, being the platform for trading stocks of major tech companies: Intel, Microsoft, NVIDIA, Meta, Google, Amazon and others. Already today, after poor reports, investors are unloading the stocks of these companies facing the harsh reality. Which is: large-scale big tech investments in AI technologies have not increased profits. And no one knows when they will.
This uncertainty becomes even worse with the expected economic recession in the US. Investing in trendy technologies is easy when markets are stable, but with ‘black swans’ flying almost everywhere, from the South China Sea, the Middle East and even as far as the Baltics, investors’ risk appetite has become way lower. And, considering that the Big Tech was the key driver for the American growth and then that of the largest regional stock markets, the current crash looks quite natural.
Parallels between the current sky-rocketing demand for AI from investors and ‘the dotcom boom’ of the noughties are there for a reason. Both at that time and today, expectations do not fit the reality. It is clear that, sooner or later, the new technology will bring real increase in labour efficiency. The problem is that the difference between ‘sooner’ and ‘later’ has a specific money metric. Seeing a promising technology, investors are afraid of missing the train, which could take them to sky-rocketing profits. While companies, which were expected to generate these profits, are so far getting losses from hefty capital investments required for the development of new technologies.
For example, the capital expenditures of just four companies, Amazon, Alphabet, Meta and Microsoft, amounted to over USD 106 billion since the beginning of 2024. The greater part of this money was used to buy land plots and build data centres for computing capacities required by artificial intelligence. An interesting paradox has emerged: AI technologies do not yet bring great profits, but the fear to lag behind competitors makes largest companies invest ever more in the technology with questionable returns, which reduces companies’ profits and dividends paid.
AI investments are still considered to be venture-backed. Today, generative AI is mostly in demand in the gaming industry (visual content, journalism, education, etc.), legal studies and the B2C segment (various voice assistants, chatbots and so on). At the same time, modern AI technologies do not help scale up business productivity. Slicker and more convenient chatbots, reduction of costs of legal firms, newsrooms and educational platforms bring 10 to 15 per cent (sometimes 20 per cent) of savings. This gives solid support for businesses, but this is still not the disruptive performance growth, which could meet massive expectations from AI.
A significant economic effect of AI application could be reached in the industrial sector, in theory. But the industrial automation is quite mature already and the AI enhancement will not bring much growth there. At least, for now.
Technologies are growing fast. The so-called artificial general intelligence, ‘the holy grail’ of AI-related technology, will be able to bring explosive growth. However, it is impossible to predict how fast this path from the as-is of artificial intelligence to the target status will be, like it was impossible to say if the Higgs boson would be found at all. For Peter Higgs, who predicted the existence of this particle in the 1960s, it was difficult to imagine that his theory will be experimentally proved only in 2012 with the help of the Large Hadron Collider. Hardly can investors and companies banking on AI wait for so long.
They are not ready to wait not just for decades, but even for a few years. For instance, the interest in Apple’s stocks reduced after Bloomberg’s message that the company may postpone the launch of the first self-driving car until 2028. Also, it is likely the autonomy level of these cars will be revisited. Tech giants’ shareholders were already dreaming of roads full of self-driving vehicles (Autonomy Level 4 without human intervention). But the reality grounded their expectations: today they speak of Autonomy Level 2 the Tesla way (partial process automation when the driver still needs to keep an eye on the traffic).
Exactly for this reason, this promising, yet not giving obvious economic benefits technology, is developing in Russia, in particular, thanks to the efforts of the government and the quasi-public sector. For example, Russia’s 2030 AI Development Strategy attaches a significant role in the AI development to the state, especially when it comes to infrastructure construction and talent training. In this sense, the participation of the state greatly reduces the impact of ‘disappointed investors’ on the stock market. While the competition in this segment will get more pragmatic and focused on specific results.