When will ai affect us Productivity growth?

By now, it’s pretty clear that generative AI can do lots of important business tasks. It can write code, summarize research, design marketing campaigns, and automate customer service. 

Take the case of Walmart. The retail giant has partnered with OpenAI and Google to make its products easier to discover and buy, while building its own AI shopping assistant, Sparky. At its recent earnings call, CEO John Furner said half of its app users have already tried the smiley face helper. Customers who use Sparky spend more per order on average. That’s a notable real-world data point for all the remaining AI skeptics out there, although the company acknowledges it is still in the early days of figuring out how AI will affect its business long-term.

Some economists are really encouraged by what they see taking place. In a recent Financial Times op-ed, Stanford’s Erik Brynjolfsson argues that the broader data may already be hinting at an important inflection point in the emerging age of AI. His confidence rests on a variety of observations: rapid advances in AI capability, a growing body of micro studies showing double-digit gains in specific tasks, evidence of employment shifts in AI-exposed occupations, and reports from “power users” and executives who say workflows are beginning to change. 

From the piece:

My own updated analysis suggests a US productivity increase of roughly 2.7 per cent for 2025. This is a near doubling from the sluggish 1.4 per cent annual average that characterised the past decade. This shift aligns with the productivity “J-curve” that my colleagues and I have explored in earlier research. General-purpose technologies, from the steam engine to the computer, do not deliver immediate gains. Instead, they require a period of massive, often unmeasured investment in intangible capital — reorganising business processes, retraining the workforce and developing new business models. During this phase, measured productivity is suppressed as resources are diverted to investments. The updated 2025 US data suggests we are now transitioning out of this investment phase into a harvest phase where those earlier efforts begin to manifest as measurable output.

But even if we’re still in the beginning of the beginning of an AI-driven economic revolution, is it still so early that we’re likely not yet seeing a broad impact on labor productivity and economic growth?

There’s certainly reason for caution. As economist Martha Gimbel at Yale’s Budget Lab notes, productivity data are notoriously noisy. When GDP keeps rising while job growth slows, as has been happening lately in the US economy, it can look like workers are suddenly producing more. But there could be other explanations, as Gimbel explains. During the pandemic, millions of lower-wage service workers lost jobs, which mechanically raised average output per worker even though no one became more efficient. More recently, immigration policy changes have reduced labor-force growth. If workers leaving the labor force tend to be in lower-productivity roles, measured productivity can rise without any AI breakthrough. One or two quarters are hardly enough to prove a lasting shift.

The recent NBER Working Paper “Firm Data on AI” might help square the circle here. It finds that 70 percent of firms report using AI, yet 90 percent say it has had no measurable impact on productivity or employment so far, and senior executives themselves use it only about 1.5 hours per week, although “this frequency has increased sharply since the start of 2025.” So for now, adoption appears widespread but still rather shallow.

What’s more, in the survey of nearly 6,000 senior executives across four advanced economies, adoption is concentrated in larger, more productive firms, whose leaders expect AI to raise productivity by 1.4 percent over the next three years. That pattern seems consistent with the idea that early “harvest” effects—again, where firms begin to see measurable gains after investing in AI and reorganizing workflows—may be jaggedly emerging at the frontier, even as economy-wide transformation remains incomplete.

Again, not the end of the beginning but still the beginning of the beginning. Let the progress continue.

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