Hype aside, AI may not be turbo-charging employee productivity just yet

Despite the hype that AI is going to fundamentally reinvent work, it has, as yet, had little to no effect on workflows, according to new research.

A report by economists from the University of Chicago and the University of Copenhagen, Large Language Models, Small Labor Market Effects, found that AI chatbots only saved workers about an hour a week, and in some cases, actually created new tasks.

“AI chatbots have had no significant impact on earnings or recorded hours in any occupation,” wrote researchers Anders Humlum and Emilie Vestergaard. “Our findings challenge narratives of imminent labor market transformation due to Generative AI.”

Offering a different narrative on AI

The study specifically looked at the Danish labor market in 2023 and 2024, gathering data from 25,000 workers and 7,000 workplaces. The researchers chose 11 “exposed” occupations: software developers, IT support, financial advisors, HR, accountants, customer-support, legal, marketing, office clerks, journalists and teachers.

The study found that, by late 2024, AI chatbots were widespread: most firms surveyed were encouraging chatbot use, while 38% had their own in-house models, and 30% of employees said they received training on AI tools. Research also revealed that, even with the wide variety of AI tools on the market today, ChatGPT remains the dominant player.

Notably, the researchers found that AI created new tasks for 8.4% of workers, even some who don’t personally use chatbots. These tasks tend to be more sophisticated, such as designing prompts and analyzing outputs, suggesting AI may restructure jobs.

The overwhelming majority of chatbot users — between 64% and 90% in each occupation — did report that AI saved them time. On average, employees said they recouped about 25 minutes per day.

But calculating AI usage frequency and per-day savings actually only equaled about 2.8% in saved time, or roughly an hour a week, according to the researchers.

Further, they estimated that just 3% – 7% of productivity gains translated into higher wages. That status quo applies at the company level, too: There is not yet evidence of job cuts or hiring tied to chatbots.

“Although the paper hasn’t been peer-reviewed and should be treated as such, it does offer a different narrative than that we hear in other circles,” said Justin St-Maurice, technical counselor at Info-Tech Research Group.

Use goes up dramatically when employer-endorsed

The study also revealed the importance of employer encouragement. When supported and trained by employers, 83% of workers used AI, compared to 47% without encouragement. Similarly, daily adoption was 21% when employers promoted AI use, compared to 8% of those using the tools of their own accord.

“This underscores the importance of firm-led complementary investments in unlocking the productivity potential of new technologies,” Humlum and Vestergaard wrote.

However, they said, it should be noted that even when encouraged, more experienced/older workers were less likely to adopt the technology, reflecting habit inertia (sticking to the established way of doing things).

AI research is more grounded than widespread hype

While the findings seem to contradict bolder claims about AI’s impact, they do align with other, more grounded assessments of AI in the workplace.

“The measured value of generative AI in the workplace so far has been quite mixed,” said Hyoun Park, CEO and chief analyst of Amalgam Insights. For instance, his firm estimates that less than 10% of employees have been able to integrate AI into more than 10% of their work.

Park also pointed out that one of the biggest value propositions for generative AI so far is code creation, yet less than 1% of all US employees are developers, and not every developer can fully integrate genAI into their work.

Similarly, Microsoft has suggested that people may save 14 minutes per day, or 2.9% of their daily working time, using Copilot, noted St-Maurice.

“This is different from other sources suggesting that jobs are under threat, and that job losses have started as a result of the technology,” he said.

AI outputs are remarkable, but need to be customized

One of the challenges in workplace AI adoption is that the value propositions that do exist around data and research summarization are not necessarily applicable to the majority of workers across white collar and blue collar jobs, Park noted.

The reality is that effective AI use requires training and organization-specific configuration, he said. Vendors like to say that employees just need to ask questions and will promptly get answers from AI, but there is still much work to do around designing prompts, accessing data, and contextualizing AI outputs.

“Although the outputs coming from foundation AI models are remarkable compared to what we were able to do two or three years ago, they have not been customized to the vast majority of jobs,” said Park. “Until that happens, AI will not be extremely productive in the workplace.”

Similarly, agentic AI requires ongoing management and maintenance, which can be guided by frameworks such as Model Context Protocol and Agent2Agent. Companies also need to invest in documenting and defining processes to maximize value.

St-Maurice noted that AI may make it easier to complete some tasks, but it also raises the bar in terms of expectations, just as when the personal computer replaced the typewriter, and sped up typing, improved document formatting, and enabled managing files and the use of spreadsheets. Similarly, genAI is not just speeding up existing work, but redefining what “competent output” looks like.

“It changes the nature of work, but doesn’t necessarily make us more productive,” said St-Maurice.

Ultimately, Park emphasized, enterprises should make a conscious effort to identify the higher level and strategic work to be done by AI once mundane and Tier 1 tasks are automated.

“Ideally, companies should look at AI as an opportunity to improve the quality of work rather than to replace employees,” he said.