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Generative AI is not only another technical hype cycle that is committed, according to the Federal Reserve, but a player for human productivity. However, the big restriction is the road to get there, “naturally slow” and “with risks”.
In A The latest work published by the Fed Board of GovernorResearchers suggest that the hype by generative AI is probably not a bladder in the long run and that the technology will be a serious macroeconomic force that is a revolutionary effect on labor productivity that resembles electricity and microscope.
The idea that generative AI becomes make the workforce more productive Is not a groundbreak. It was praised by company managers and many AI bulls since Openai’s generative KI model -Chatgt triggered the AI madness.
However, what is important is that the most powerful business institution in the country has just expressed the remarkable trust in the potential of technology. Albeit with a hook.
AI could be the next microscope
The paper divides technological innovations into three categories. First, they have innovations such as the light bulb, which initially increased productivity dramatically by not restricting workers to daylight. However, as soon as the technology was widespread, the light bulb set up productivity in the workplace.
“In contrast, two types of technologies are a longer impact on productivity growth,” the researchers write and the AI has characteristics of both.
The first are “general technologies” such as the electrical dynamo or the computer. The electrical dynamo was the first practical electrical generator and, even after a widespread introduction, continued to provide accelerated productivity growth because it triggered related innovations and continued to improve.
The researchers say that generative AI already shows signs that it fits into the bill. You have special LLMs for certain domains such as Openais Legalgpt that are helpful in legal matters, and “copilotes” such as Microsoft’s Copilot product, which is intended to increase the productivity of the office by integrating generative AI into corporate work streams. Fed researchers believe that even more knock innovations will come, and this wave is led by digital local companies.
And it is obvious that nuclear technology is quickly innovative and this will probably continue to do so if companies develop technology with the aim of achieving artificial general intelligence. In the meantime, as can be seen in the newspaper, the quick growth of the technology has already awarded us further innovations such as Agentic AI and Landmark AI models such as deepseeks R1.
The second type of technology is referred to as “inventions of invention methods”. The best known examples are the microscope or the printing press. Although a microscope has now become a common instrument, it continues to increase the productivity of humans by enabling research and development projects.
Generative AI was helpful in Simulations to understand the nature of the universePresent In new drug discoveriesand more. And the paper finds that from 2023 there was a huge spike, from companies that cite AI in research and development contexts and in corporate results, and show that the integration of AI has already started in corporate singovations.
There is always a catch
Unfortunately, this trust comes with a restriction. AI will be a blessing for economic and productivity growth, but it is unlikely that it will happen overnight.
The Fed’s paper says that the greatest challenge at generative AI is not the technician itself at the moment: it makes people and companies actually use them. While the researchers do more, most companies have not yet brought them into their daily business outside of technology and scientific areas with the exception of the financial sector. And industry surveys show that the introduction of AI in large companies is far higher than small.
While the generative AI will probably strengthen how productive we are overall, the effects will be slow. This is because it takes time, money and other supporting technologies such as user interfaces, robotics and AI agents to really make AI in the entire economy useful. The authors compare it with previous major technical changes as progress in the calculation that have accumulated for decades before causing a productivity boom.
The schedule for this boom is still unknown. Goldman Sachs Economists believe that the effects of AI on labor productivity and GDP growth in the United States will be shown in 2027 and will accelerate to a climax in the 2030s.
Another risk to which the Fed indicates is associated with the building infrastructure for the expected demand. A widespread introduction of generative AI means a significant need for investments in data centers and electricity generation. But investing too quickly can have “catastrophic consequences” if The demand does not grow as expectedSimilar to the overexpansion of the railway in the 19th century, the FED warns economic depression towards the end of the century.
Despite the restrictions, the Fed is confident that the generative AI is transformative for productivity. However, whether this transformation continues to accelerate and as large as the electrical dynamo or the microscope depends on the extent and speed of the introduction of the technology.
