The Federal Reserve has weighed in on the hype surrounding generative AI, stating that it’s not just another tech cycle that will inevitably fizzle out. Instead, the institution’s researchers believe that generative AI has the potential to be a game-changer for human productivity, akin to the revolutionary effects of electricity and the microscope.
Breaking Down the Hype
While the idea that generative AI will boost productivity isn’t new, the Fed’s paper highlights what’s significant about the technology’s potential. The researchers divide technological innovations into three categories:
- General-purpose technologies, like the electric dynamo or computer, which deliver accelerating productivity growth even after widespread adoption.
- Inventions of methods of invention, like the microscope or printing press, which continue to raise productivity by enabling research and development projects.
- Specialized technologies, like the light bulb, which initially increase productivity but eventually stop providing additional value.
Generative AI falls into the first two categories, with its rapid growth and innovation indicating that it will have a lasting impact on productivity growth.
AI: The Next Microscope
The Fed’s researchers point out that generative AI is already showing signs of becoming a general-purpose technology. Specialized LLMs, like OpenAI’s LegalGPT, are being developed to assist in specific domains, and “copilots” like Microsoft’s Copilot product are being integrated into corporate workstreams to increase productivity. The researchers believe that this trend will continue, with digital native companies leading the way in developing the technology. The core technology is rapidly innovating, with the potential to lead to further innovations like agentic AI and landmark AI models like Deepseek’s R1.
The Microscope Effect
The second type of technology, inventions of methods of invention, has the potential to have a profound impact on productivity. The microscope, for example, has enabled groundbreaking research and discoveries, and generative AI is already being used in simulations to understand the nature of the universe, novel drug discoveries, and more. The paper notes that there has been a significant spike in companies citing AI in research and development contexts and corporate earnings calls, indicating that AI’s integration with corporate innovation has already begun.
The Catch
However, the Fed’s confidence comes with a caveat. The biggest challenge with generative AI right now is getting people and businesses to actually use it. While researchers are starting to adopt it more, most companies outside of tech and the scientific fields haven’t worked it into their daily operations yet, with the exception of the finance industry. Industry surveys show that AI adoption is far higher within large firms than small ones. The timeline for AI’s impact on productivity and GDP growth is still unknown, but Goldman Sachs economists predict that it will start to show in 2027 and accelerate to a peak in the 2030s.
Infrastructure Risks
The Fed also points out that building infrastructure for anticipated demand is a significant risk. A widespread adoption of generative AI would require significant investment in data centers and electricity generation, but investing too quickly can have disastrous consequences when demand doesn’t grow as expected. This risk is reminiscent of railroad overexpansion in the 1800s, which led to an economic depression towards the end of the century. The Fed warns that investing too quickly can have “disastrous consequences” when demand doesn’t grow as expected.
A Conclusion
Despite the caveats, the Fed is confident that generative AI will be transformative for productivity. However, whether that transformation continues to accelerate perpetually and have as big of an effect as the electric dynamo or the microscope will depend on the extent and speed of the technology’s adoption. The future of generative AI is uncertain, but one thing is clear: it has the potential to be a game-changer for human productivity. As the technology continues to evolve and improve, it will be exciting to see how it shapes the future of work and the economy.
