Jonathan W. Welburn and Vegard M. Nygaard
The future of AI, depending on whom you ask, is everything and anything. It is the key to never-ending economic growth. It is the cause of catastrophic unemployment. It is the driver of lifesaving medical advances. It is the source of grave risks to national security.
The truth is that no one knows the full implications of AI. But what researchers like us are starting to see in the data is that it isn't the speed of AI development that will shape the near-term future. It is the speed of its adoption. And AI use across various sectors shows that adoption is uneven and slower than the Silicon Valley and Wall Street hype suggests.
In August, a research paper on AI investments from the Massachusetts Institute of Technology spooked the markets for tech stocks. Headlines underscored just one of the researchers' findings: 95 percent of firms were seeing no return on their hefty AI investments. The more telling data got at why. Few companies have successfully integrated AI into their core business functions, despite the rollout of increasingly powerful models.
Few companies have successfully integrated AI into their core business functions, despite the rollout of increasingly powerful models.
At RAND, our research on the macroeconomic implications of AI also found that adoption of generative AI into business practices is slow going. By looking at recent census surveys of businesses, we found the level of AI use also varies widely by sector. For large sectors like transportation and warehousing, AI adoption hovered just above 2 percent. For finance and insurance, it was roughly 10 percent. Even in information technology—perhaps the most likely spot for generative AI to leave its mark—only 25 percent of businesses were using generative AI to produce goods and services.
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