The emergence of generative artificial intelligence (Al) has attracted significant attention, but there have been few studies of its economic impact. This is, to our knowledge, the first study of the impact of generative Al when deployed at scale in the workplace.
We find that (i) ML affects different occupations than earlier automation waves; (ii) most occupations include at least some SML tasks; (i) few occupations are fully automatable using ML; and (iv) realizing the potential of ML usually requires redesign of job task content.
In collaboration with OpenAl, we assess the impact of Large-Language Models on the labor workforce. 80% of the U.S. workforce could have at least one tenth of their tasks affected by GPTs.
"What results [from the task-based analysis] could be a roadmap for employers to look for automation opportunities. The process can help them identify where to put resources amid the AI transformation."
“There’s a lot more to come as more people adopt these things,” said Erik Brynjolfsson, an economist at Stanford who is optimistic that we may be on the cusp of a productivity takeoff as white collar-workers have their day-to-day abilities augmented by the new tools. He has been running experiments and finding that A.I. does help workers, and has co-founded [Workhelix] that coaches firms on how to best employ the technology.
"We studied how you could use generative AI to help the call center operators do a better job and within three to four months, they were already on average about 14% more productive — more calls per hour," [Brynjolfsson] said. "They also had higher customer satisfaction, they also had less employee turnover. So stockholders, customers, workers all were better off," he added.
On the productivity side, I think 2024 is going to be a year of harvesting a lot of the capabilities. So what I see is almost every CEO is being asked by their board of directors “what is your game plan for generative AI?” Many of them are implementing an approach based on what we call the task-based analysis, where you look at tens of thousands of tasks and rank them based on which ones gen AI can help with the most and then putting in place working production systems for coding for customer service, for writing, for sales support and for other areas. In 2024 many of those cases will deliver the double-digit productivity gains that we saw in research.
MIT professor and economist Erik Brynjolfsson said recently that he’d be disappointed if artificial intelligence didn’t lift the current anemic 1.2% productivity growth rate to 3% or even 4%. This would be a good thing for business and government because it could potentially help with the labor shortage, drive earnings growth and increase tax revenues, which would ostensibly help address current debt levels.
Many jobs in which some tasks can be automated aren’t likely to go away. Instead, AI will augment human labor while humans continue to focus on the things they do better. However, jobs that are mostly or fully automatable may disappear, putting people out of work. In such cases, as a society, we have a duty to take care of the people whose livelihoods are affected, to make sure they have a safety net and an opportunity to reskill and keep contributing. Meanwhile, lowering the cost of delivering certain services is bound to increase the demand for some jobs, just as the invention of the car led to a huge explosion in the number of driving jobs. In this way, AI will create many jobs as well as destroy some.
The best way to begin learning [how to interact with LLMs] is to find a project with an attractive benefit-to-cost ratio and low risks and start trying things. The same approach should be used with more-ambitious efforts to work with generative AI, such as combining an LLM with other technologies. Rapid iteration is the best way to learn and make progress. The faster an organization can move through repeated OODA loops of observing the situation, orienting for action, deciding what to do, and then acting, the more it will learn, and the faster productivity gains and other benefits will appear.
“Rarely do humans or machines alone excel as much as combinations of humans and machines together,” [Erik] Brynjolfsson says.
"We’re not going to run out of things for humans to do anytime soon," Mr. [Erik] Brynjolfsson said. "But the things are different: learning how to ask the right questions, really interacting with people, physical work requiring dexterity."
“[Generative AI is] digitally capturing some of that expertise that [senior employees] were previously using for that one customer, and now other customers are going to benefit from it. Even ones that never talked to that high performer,” said Erik Brynjolfsson, senior fellow at the Stanford Institute for Human-Centered AI and one of the authors of the study.
“AI is not just about automating jobs and replacing people,” says Erik Brynjolfsson, senior fellow at the Stanford Institute for Human-Centered AI. "By far the biggest benefits are having AI work with humans and help them be more productive."
"The new technologies can accelerate innovation by making research and the development of new ideas more efficient, boosting not just the level, but the rate of increase in productivity growth."
"A paper by Erik Brynjolfsson of Stanford University and colleagues examines customer-support agents. Access to an ai tool raises the number of issues resolved each hour by 14% on average."
"In the race to adopt AI, Mr. Brynjolfsson said companies in data-rich markets, like the financial sector, have an advantage over those in industries like construction, which lack the kind of data needed to train algorithms in a way that provides business insights."
“And what [Generative AI] did was it took people with just two months of experience and had them performing at the level of people with six months of experience." - Erik Brynjolfsson
“The other thing that I wish people would do more of is think about what new things could be done now that was never done before. Obviously that’s a much harder question. It is also where most of the value is.” - Erik Brynjolfsson
"Over the next decade, AI won’t replace managers, but managers who use AI will replace those who don’t." - Erik Brynjolfsson and Andy McAfee
Watch the recording from our May 2024 webinar featuring Workhelix Co-Founders Erik Brynjolfsson, Andy McAfee, and James Milin, alongside Bryan Hancock, Partner and Global Leader of McKinsey & Company's Talent work, as they share their expertise on how pioneering companies are successfully integrating GenAI into their operations.
Watch the recording from our April 9th Launch Webinar on how to craft your company's plan for GenAI. Featuring Andrew Ng, Managing General Partner at AI Fund, and Jaya Kumar, Chief Digital and Experiences Officer at BAYADA Home Health Care.
On September 12, 2023, Cohere presented a webinar with Workhelix Co-Founders Erik Brynjolfsson and Andy McAfee about the impact of Generative AI on workforce productivity.
In this webinar held on July 28, 2023, AI pioneer Andrew Ng and leading economics researchers Erik Brynjolfsson, and Andy McAfee of Workhelix demystify the process of leveraging Generative AI for your organization.
“I spend a lot of time filling out spreadsheets, making budgets, I would love to say to a piece of technology, ‘Give me a first draft of this and let me tweak it from there.’ That’s what I think is the real innovation here.” - Andy McAfee
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