NBER Study Suggests Limited AI Chatbot Impact on Earnings, Productivity

A study of artificial intelligence chatbot impact on labor markets in Denmark suggests the economic impact is “minimal.” Indeed, the study authors say “AI chatbots have had no significant impact on earnings or recorded hours in any occupation.” 

The study published by the U.S. National Bureau of Economic Research involved two large-scale adoption surveys conducted in late 2023 and 2024 covering 11 occupations; 25,000 workers and 7,000 workplaces.

Productivity gains were said to be modest, with an average time savings of three percent. But the study notes that AI chatbots have created new job tasks for 8.4 percent of workers, including some who do not use the tools themselves.

Nor has there been any impact on worker earnings. “Workers overwhelmingly report no impact on earnings as of November 2024,” the study says. 

Nor do productivity gains seem to have much impact on earnings. “We estimate that only three to seven percent of workers’ productivity gains are passed through to higher earnings,” say authors Anders Humlum and Emilie Vestergaard.

“Comparing workplaces with high versus low rates of chatbot usage, we find no evidence that firms with greater adoption have experienced differential changes in total employment, wage bills, or retention of

incumbent workers,” the authors say. 

The authors also note that Denmark has institutional characteristics similar to those of the United States, with similar uptake of generative AI; how hiring and firing costs; decentralized wage bargaining and annual wage negotiations. 

The 11 occupations studied included accountants, customer support specialists, financial advisors, HR professionals, IT support specialists, journalists, legal professionals, marketing professionals, office clerks, software developers, and teachers.

The findings should not come as a surprise. The “productivity J-curve" suggests that initial investments in new technologies may temporarily suppress productivity before delivering long-term benefits.

Study	Technology Examined	Lag Time Observed	Key Findings
McKinsey Global Institute 1,5,7	Digital technologies, AI	Years to decades	Benefits emerge after business process redesign and "creative destruction." Historical parallels (e.g., electric power) show lags of decades. Generative AI may shorten lags to months or years.
CEPR Study on French Industrialization 3	General-purpose technologies	5–10 years	Firms delayed adoption due to uncertainty, and early adopters operated technologies inefficiently. Aggregate productivity gains materialized slowly as organizational practices evolved.
Stanford CS Analysis 4,5	IT investments	2–5 years	Executives reported 5-year lags for IT payoffs. Complementary investments and learning curves delayed measurable productivity growth.
Productivity Paradox Research 5	IT, automation	2–5 years	"Productivity J-curve" observed: short-term costs offset gains until workflows adapted. Measurable aggregate gains emerged in the 2000s from 1990s IT investments.
Brynjolfsson et al. (McKinsey) 7	Generative AI	Months to a few years	Shorter lag due to existing digital infrastructure, but still requires process redesign. Early adopters see inefficiencies before optimization.