Economists have time-tested models for projecting economic growth. But they’ve seen nothing like AI, which is a wild card complicating traditional economic playbooks.
Some facts are clear: AI will make humans more productive and increase economic activity, with spillover effects on spending and employment.
But there are many unknowns about AI. Economists can’t isolate AI’s impact on human labor as automation kicks in. Nailing down long-term factory job losses to AI is not possible.
AI also complicates capital expenditure projections. Heavy money is going into data centers and power plants, but how much this will translate into productivity gains — and thus whether demand for AI services will remain high — remains unclear.
Economists are weighing the likelihood of a slowdown in the US and global economy against the productivity gains AI is expected to bring. The Peterson Institute for International Economics, for instance, predicts that global gross domestic product (GDP) will slow in 2026, with AI offsetting some of the decline.
The Conference Board, a nonprofit economic think tank based in New York, estimates that the US GDP will grow around 1.9% annually from 2025 to 2039, down from 2.4% growth from 2000 to 2024. AI will lift some of that decline, said Erik Lundh, senior global economist for The Conference Board Economy, Strategy & Finance Center.
To arrive at this projection, TCB factored AI’s uncertain crosscurrents — such as AI productivity gains — into its models along with established variables, such as long-term trends in total-factor productivity, labor, and capital.
But the projection “does not adequately capture the potential of a sea change… like artificial intelligence,” Lundh said.
Computerworld sat down with Lundh to understand AI’s big-picture impact, how it is being quantified, and how such metrics help business and policy planners. This interview has been condensed and lightly edited for clarity.
The Conference Board projections show US GDP growing at an average rate of 1.9% from 2025 to 2039, slower than the 2.4% growth from 2000 to 2024. Does AI meaningfully offset some of that slowdown? “Yes. The US GDP projection of 1.9% from 2025–2039 … reflects that there’s going to be less bang on the capital and labor side. Productivity associated with technological developments — including AI — does offset more of the slowdown.
“We’re seeing an increase in terms of productivity enhancements over the next decade and a half. While it doesn’t capture AI directly… there is all kinds of upside potential to the productivity numbers because of AI.
“The same is true of the global economy. Emerging markets are going to be growing faster than advanced economies are — and they have been — but again, there is an expectation that AI will play a role in terms of augmenting the kinds of productivity that we see over the coming years.”
As AI becomes a bigger part of the economy, will it change the way we measure growth? And as we go forward, will AI’s impact on GDP keep increasing? “It helps to make a distinction in terms of AI’s contribution. On one hand, we’re seeing a lot of stories about data centers being built, electricity demand rising, and power plants being dusted off or newly planned to support AI. When you build a data center or a power plant, you create real economic activity — the planning, the materials, the labor that goes into erecting these things. That shows up as capital contribution to growth because it’s physical investment.
“But beyond that, you also get productivity enhancements afterward. It’s similar to infrastructure buildout. If you build a new port or airport, you spend money up front, but then it becomes cheaper to ship goods or move workers, and that long-term efficiency shows up on the productivity side.
“AI will likely have similar spillover effects once the infrastructure is in place. How large those effects will be is unclear, which is the core challenge… estimating the relationship between AI and productivity.”
How exactly could AI change productivity and investment patterns across the economy? “There are basically two ways this can go. You can get more output for the same input. If you used to put in 100 and get 120, maybe now you get 140. That’s an expansion in total factor productivity. Or you can get the same output with fewer inputs.
“It’s unclear how much of either will happen across industries or in the labor market. Will companies lean into AI, cut their workforce, and maintain revenue? Or will they keep their workforce, use AI to supplement them, and increase total output per worker?
“R&D spending is also a question mark. AI can allow researchers to do more, faster, and with fewer resources. But that could either mean less R&D spending is needed, or it could inspire even more investment because the return on R&D becomes higher. We don’t yet know which direction it will go.”
The US is spending much more on AI than the rest of the world. Does that make your US productivity projections different from other economies? “Yes, the productivity numbers we’re seeing in the US modeling work are elevated, both compared to what we had previously projected and compared to some historical periods. But we’re also seeing upticks in other parts of the world. China, for example, shows increased productivity projections as well, and that reflects its serious investments in AI capabilities.
China is in the process of developing its next five-year plan — the 15th — and a lot of attention is going into building a more advanced manufacturing environment and next-generation technologies like artificial intelligence. Of course, it’s a moving target: access to high-end chips, the development of domestic alternatives, and broader geopolitical dynamics all play a role.
But China has a large technical talent base and significant government funding aimed at making AI a key part of its growth environment over the next decade.
The US and China are ahead in the AI curve. For developing economies, how does AI change their growth paths? “One of the advantages many of them — like Vietnam, Bangladesh, Kenya, or parts of sub-Saharan Africa — have historically relied on is a labor-arbitrage system, where it simply costs less to produce goods because labor is cheaper. That’s how countries such as China, Taiwan, and Singapore worked their way up global value chains over time.
“But with AI, that can become disruptive. If AI and automation remove the human element from labor-intensive manufacturing, that cost advantage erodes. It makes it harder for developing countries to use cheap labor as a stepping stone toward industrialization.
“At the same time, businesses and consumers in these economies… can still use AI tools to become more efficient. That’s the tailwind.
“So there are both headwinds and tailwinds for emerging markets that may not have the resources or technical know-how to build out AI domestically but will still feel its effects as the technology spreads.”
VCs say they don’t want to fund yet another coding tool or AI search engine. They want AI that transforms the physical world, like robotics, safety tech, or manufacturing tools. That’s where they see trillion-dollar impact. How do you view that? “It’s interesting, and I agree to an extent. But the US is a services-oriented economy, so even if AI eventually reshapes the physical world, the more immediate impacts will be in services. That’s the largest share of our economy. And you don’t need a robot to see disruption. See AI call centers, chatbots, automated accounting, paralegal tools. These can replace tasks that used to require people, and do it for a fraction of the cost.
There may eventually be a pivot back toward manufacturing as physical AI develops, and some in the political world would like that. But in the near term, AI’s biggest effects will likely show up in the services sector long before they show up on an assembly line in Georgia.
As AI accelerates, what uncertainties or unknowns stand out to you when you think about the future of economic analysis? “This is an emerging story. The technology is changing month to month. I’m using it professionally, and it’s making me more efficient.
“I don’t know what this looks like in five or ten years, or whether the economist profession will face the same fate as others, with a reduced need for bean counters like me. It’s a wild future. I can’t predict it with any certainty.”
