Experts may be skeptical about corporate AI hype to varying degrees, but they share the view that machine learning models will have a significant effect on society.

The Forecasting Research Institute (FRI) has published a report [PDF] titled “The Longitudinal Expert AI Panel” that attempts to distill the forecasts of knowledgeable folk – mainly men – in industry, academia, and policy about the capabilities, adoption, and impact of AI in the years ahead.

The research project, led by Ezra Karger, an economist with the Federal Reserve Bank of Chicago, suggests that few AI experts believe “superintelligence” as outlined by the likes of Anthropic CEO Dario Amodei will arrive anytime soon. 

But the 339 respondents participating in the project – AI and ML scientists, economists, technical staff at frontier AI companies, and policy experts from NGOs – believe that AI will spur significant social changes by 2040.

“The median expert foresees that by 2030 AI will be responsible for 7 percent of US electricity usage, assist in 18 percent of work hours in the US, and provide daily companionship for 15 percent of adults – roughly 7x, 4x, and 2.5x current levels, respectively,” the report says.

A year ago, between 1 and 5 percent of all US work hours were assisted by generative AI, according to an economic paper, “The Rapid Adoption of Generative AI.“

FRI’s report also finds about 20 percent of ride-hailing trips will involve autonomous vehicles by the start of the next decade, panelists predict; among the general public, the expectation is that only 12 percent of ride-hailing trips will involve robocars by 2030.

Those surveyed see no end to the spending: annual global private investment is projected to reach $260 billion, up from $130 billion in 2024. The experts appear to be none too concerned about the popping of what looks a lot like an AI investment bubble.

Whether any of the frontier model leaders like Anthropic and OpenAI will have found a way by 2030 to profit from more expansive adoption of AI isn’t addressed. Companies selling the picks and shovels for the AI gold rush – AWS, Google, Microsoft, and Nvidia – can at least expect avid usage of their cloud infrastructure. And these cloud hyperscalers may just end up investing more and more into Anthropic and OpenAI until they own them entirely.

Opinions diverged more substantially in terms of predictions about AI usage in drug discovery. The top 25 percent of experts estimated that the majority of revenue from newly approved US drugs by 2040 will be attributable to AI discoveries. The bottom quartile expects less than 10 percent to come from AI.

There’s a similar divide in whether AI will independently solve or assist in solving a Millennium Prize Problem by 2040. About a quarter of experts surveyed expect that AI will be up to the math challenge (>81 percent chance, they predict), while another quarter of experts believe that AI doesn’t have the right stuff (<30 percent chance, they predict).

The median expert also sees AI advancing more slowly than makers of frontier AI models, which foresee human- or superhuman-level intelligence in the 2026-2029 period. The average expert gives the rosy vendor view about a 23 percent chance of being realized, while putting the chance of AI progress stopping around current levels at 28 percent. 

It’s perhaps worth noting that 78 percent of respondents identified as male, 15 percent are affiliated with effective altruism [PDF], and 18 percent are affiliated with top AI labs. The survey does not address any of the ethical issues related to the training, deployment, and commercialization of AI technology. 

Median panelists say there’s only about a 20 to 25 percent chance that the AI train will be slowed by lack of AI literacy, societal unease, lack of use cases, and costs. Data quality, regulations, and cultural resistance are seen as more likely (30 to 35 percent) barriers to adoption. Integration and unreliability are expected to be the most significant obstacles (40 percent). 

The various experts also had differing views about AI’s impact on employment. The median expert forecast 2 percent growth in white-collar jobs between January 2025 and December 2030. But seeing as the historical trend predicted 6.8 percent white-collar job growth, this represents a lower rate of job growth. More than 75 percent of the experts predict slower white-collar job growth than current trends, and 25 percent of experts anticipate 4 percent white-collar job loss by 2030.

Gustavo de Souza, an economist with the Federal Reserve Bank of Chicago, on Monday presented research showing that in Brazil, “AI significantly increased employment in production-related occupations, such as manufacturing, maintenance, and agriculture, while it reduced employment in administrative jobs,” as he explained in a summary post.

AI, de Souza found, allows less skilled workers to perform tasks that previously required more experience. While office workers can expect some of their tasks to be automated away, he asserts that the overall impact is a net improvement in wages and greater wage equality.

“This shift reduces the barriers to entry in high-AI-exposed occupations, increases the hiring of lower-skilled workers, and erodes the wage premium for high-skilled individuals,” he wrote.

Those whose labor can be replaced with AI will likely be hurt, while those whose labor is complemented by AI will likely benefit. 

Overall, he argues, AI has had a positive impact in Brazil and he expects the effect could be even broader in the US. That said, he also calls for policies and programs to help workers transition from occupations made redundant by AI. ®