Stanford University


What ‘Robot Hubs’ Mean for the Future of US Manufacturing

New research gives us a first look at robot adoption and concentration in US manufacturing

Tim Hatton
Contributing Writer

July 24, 2023
7-minute read

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It’s impossible to fully grasp how robotics is changing manufacturing in the United States without a complete understanding of where those robots are. Now, new research is providing a snapshot.

And here’s why that’s important: Robotics is what’s known as a general-purpose technology—just like computers, the internet, and electricity—that has the potential to make a fundamental difference in how entire economies operate. In short, robots present an opportunity to transform the manufacturing industry to reach new levels of productivity and growth. 

But the first step in maximizing that potential is understanding how the technology is used. “We’re still in the early stages of understanding what’s driving robot adoption,” said Erik Brynjolfsson, director of the Stanford Digital Economy Lab and senior fellow at the Stanford Institute for Human-Centered AI (HAI). “It’s important to have data about where they are and also where they aren’t, and what their other characteristics are.” 

Finding the robot hubs

Brynjolfsson is the co-author of a new paper on robotics adoption, along with researchers J. Frank Li, Cathy Buffington, Nathan Goldschlag, Javier Miranda, and Robert Seamans. In “The Characteristics and Geographic Distribution of Robot Hubs in US Manufacturing Establishments,” the team sourced responses from the US Census Bureau’s Annual Survey of Manufacturers to examine which manufacturers use robotics, where the robots are, and how establishments are using them. (A shorter version of the paper, “Robot Hubs: The Skewed Distribution of Robots in US Manufacturing,” is published in AEA Papers and Proceedings 2023.)

“Before we answer all those other questions about productivity and performance and wages, you need to know where the robots are first,” Brynjolfsson said. “For now, the striking finding was how concentrated the robots are.”

More than any other factor, the researchers found that a business is more likely to employ robotics if other establishments in its region report they also use them. In the paper, these concentrated regions of robotics use are called “robot hubs.”

The team ranked regions by the number of robots used in manufacturing, which revealed that robots are highly concentrated in the top 10% of robot-dense areas—and the bottom 50% of regions had almost none. Survey data showed that the top five states with the highest robot adoption share by establishments were Iowa, Michigan, Kansas, Wisconsin, and Minnesota.

The paper also identifies several trends associated with robot hubs, including the presence of “robot integrators,” which are businesses that assist in acquiring and installing robots. Another correlation was a higher share of union membership. Those patterns on their own, however, don’t fully illuminate why a robot hub develops. 

“The concentration of robot hubs is a function of several different things, such as the type of manufacturing these firms do, the education of the workforce, the size of the establishments, but it’s also sort of an unexplained dark matter, and that seems important as well,” Brynjolfsson explained. “Something about these environments makes it so that companies are more likely to use robots. A big part of future research will be to find out why that is.” 

The advantage of census data

Past attempts to generate insight into robot adoption faced challenges, such as selection bias, inherent to the research process. For example, if researchers mailed out surveys or called manufacturers directly, potential respondents might not have picked up the phone. Or a manufacturer might assume that the survey had nothing to do with them and not mail their response back.

Of course, that assumption would be wrong. To fully and accurately understand the spread of robotics throughout the manufacturing industry, it’s vital to get accurate input from a representative set of establishments. 

“There’s never been any careful data gathering on where robots are in America,” said J. Frank Li, a postdoctoral fellow at the Stanford Digital Economy Lab and one of the study’s authors. “There have been plenty of different kinds of bits and pieces that people gathered, but now for the first time, we worked with the US Census to gather some really detailed data on where robots actually are.” 

In addition to counting people, the US Census Bureau conducts regular studies into trends and demographics throughout the economy. The Annual Survey of Manufacturers (ASM) was one of these—a set of questions designed to understand the current state of the manufacturing industry across several dimensions. 

Since responding to the ASM is a legal requirement, responses don’t suffer from the same selection bias as non-mandatory surveys do. This enabled the team to gain unprecedented insight into the use of robots, confident that responses accurately reflected the nature of the entire manufacturing industry. The researchers developed their questions in 2017, which were included in the surveys for 2018–2020. The findings in the paper are based on 2018 data.

Brynjolfsson noted that he was impressed by the bureau’s process in developing the survey. “When a survey is required by law, you don’t want it to be cluttered up with anything time-wasting, so they did over a year of testing,” he said. “That process was an eye-opener for me, and I think it led to a survey that’s far and away the most representative of the industry, thanks to the Census. Otherwise, the data would have been way too scattered.” 

“If we want not just productivity, but widely shared productivity, we need to have robots in places where right now they’re not as common.”

Erik Brynjolfsson

Erik Brynjolfsson

Director, Stanford Digital Economy Lab

Laying the foundation 

The researchers’ findings weren’t limited to solely identifying robot hubs, though. Data from the ASM also included information on the size and age of surveyed establishments and their workforces.

From this data, the researchers found that higher robotics use correlated with higher capital expenditures, particularly in information technology. The research suggests that companies willing to pay the price for robots are also more likely to spend more on other innovations and improvements, leading to enhanced automation and digitalization.

That kind of investment creates a spillover effect throughout surrounding local economies, just like the manufacturing output of the robots does. If the use and integration of robots creates better economic outcomes, then a stark divide between robot hubs and everywhere else could challenge overall growth.

Brynjolfsson raises this possible divide as a legitimate concern. “Having robots so concentrated could lead to a separation, where some manufacturing becomes much more high-tech and robust, and other parts get left behind—so it’s valuable to understand what drives the adoption and, ultimately, the diffusion of robots,” he said. “If we want not just productivity, but widely shared productivity, we need to have robots in places where right now they’re not as common.”

Understanding why companies are adopting robots in certain areas and not others will help guide future development throughout the manufacturing industry. Researchers, data agencies, policymakers, and industry stakeholders can all leverage the paper’s insights to work toward a more balanced and inclusive deployment of robotics. 

The research team realizes that their work is just the beginning of a long line of research into understanding the impact of robotics in manufacturing. The authors propose several avenues that future researchers could pursue—one looks into the relationship between robot hubs and international trade, while another explores the link between robot adoption and other investments. “Our hope is that the patterns in the data that we document in our paper spark further research in this area that is of use to scholars, practitioners, and policymakers,” the researchers wrote.

Future researchers can also better understand the advantages and obstacles of robotics in manufacturing by examining the influence of robots on productivity and wages in manufacturing establishments. A more collaborative environment will make it easier to enable economic growth and tech advancement in the manufacturing sector—and beyond.

“Our examination of the cross-sectional data indicates that robot adoption is positively associated with the share of production workers but negatively associated with earnings per worker,” said Li. “However, what we can say about causality and the mechanism behind our findings is still limited without longitudinal data and exogenous shocks. I expect that as new waves of survey data become accessible, there will be an increase in research exploring the impact of robots on the US manufacturing sector.”

Any opinions and conclusions expressed herein are those of the authors and do not represent the views of the U.S. Census Bureau. Disclosure review numbers CBDRB-FY22-ESMD011-003, CBDRB-FY23-ESMD011-003, CBDRB-FY22-192, and CBDRB-FY23-ESMD011-004 (DMS# 7508509). We are grateful to the Hewlett Foundation, Kauffman Foundation, National Science Foundation, Stanford Digital Economy Lab and Tides Foundation for generous funding. We thank Jim Bessen, participants at the 2023 AEA Annual Meeting, and Emin Dinlersoz for valuable comments and feedback. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

The authors are grateful to the Hewlett Foundation, Kauffman Foundation, Markle Foundation, National Science Foundation, Stanford Digital Economy Lab, and Tides Foundation for generous funding.


A new collaboration with Project Liberty’s Institute

June 8, 2023

Stanford Digital Economy Lab joins Project Liberty’s Institute to study digital platforms, society, and the economy

We’re proud to announce that Stanford Digital Economy Lab is joining Project Liberty’s Institute to expand our pathbreaking research into how AI and other digital technologies affect society and the economy. The collaboration will inspire new, impactful projects designed to spark global conversation about the current and future state of the digital economy.

Erik Brynjolfsson talks

Year in Review

Taking a Look Back:
10 Lab Highlights from 2022

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Of course, we did so much more than 10 things during the past year, but to capture all the highlights here—including the Lab’s groundbreaking research—would send you into a forever scroll. So we’ve whittled the list down to the top 10 things we did during the past year that helped advance the collective understanding of the digital economy.

To keep up with the Lab and our work, follow us on Twitter and LinkedIn and sign up for email updates about future events.

1 / Essay

Erik Brynjolfsson warns of falling into ‘The Turing Trap’

In his far-reaching essay, Erik Brynjolfsson warns of the dangers of focusing AI development on systems that surpass human capabilities rather than systems that augment humans.

In Janurary, Lab Director Erik Brynjolfsson released “The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence,” in which he warns that “an excessive focus on developing and deploying human-like artificial intelligence can lead us into a trap.” The essay was later published in the spring issue of Daedalus, “AI & Society” (see #3 on our list) and served as the basis for our spring workshop.

The Turing Trap: A conversation with Erik Brynjolfsson on the promise and peril of human-like AI
Brookings Institution

Economists Pin More Blame on Tech for Rising Inequality
The New York Times

AI Shouldn’t Compete With Workers—It Should Supercharge Them

How to Solve AI’s Inequality Problem
MIT Technology Review

2 / Collaboration

A redesigned, more rigorous jobs report

The Lab collaborated with the ADP Research Institute to launch the reimagined ADP National Employment Report and ADP Pay Insights Report.
Chef in kitchen
The ADP National Employment Report and ADP Pay Insights Report are based on anonymized and aggregated payroll data from more than 25 million US employees across 500,000 companies. 

In May of 2022, the ADP Research Institute paused its monthly ADP® National Employment Report in order to refine its methodology and design. Part of that evolution was teaming up with our data scientists to add new perspective and rigor to the report. The newly designed report, which launched in August, uses fine-grained, high-frequency data on jobs and wages to deliver a richer and more useful analysis of the labor market.

ADP National Employment Report 

ADP Pay Insights Report

A Key Barometer of the US Job Market Returns With Some Improvements

3 / Publications

A comprehensive collection of views about AI and society

The spring issue of Daedalus featured several contributions by leaders and advisors from the Lab and Stanford HAI.
Eric Schmidt and James Manyika discuss the spring issue of Daedalus at our spring workshop.

In the spring issue of Daedalus—from the Academy of Arts and Sciences—experts explored various angles of artificial intelligence, including its effects on labor and the economy, its role in law and governance, and what it says about us as humans. The issue, which was edited by James Manyika, featured several contributors from the Lab and Stanford HAI community.

Featured essays
Searching for Computer Vision North Stars
Fei-Fei Li (Affiliated Faculty) and Ranjay Krishna

Automation, Augmentation, Value Creation & the Distribution of Income & Wealth
Michael Spence (Advisory Group)

Automation, AI & Work
Laura D’Andrea Tyson (Digital Fellow) and John Zysman

Socializing Data
Diane Coyle (Advisory Group)

AI, Great Power Competition & National Security
Eric Schmidt (Advisory Group)

The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence
0 Erik Brynjolfsson (Lab Director)

4 / Report

Exploring the future of work in California

What’s the current state of the California labor market—and what might it look like in the next 100 years? Our researchers delved deep into these questions as part of the California 100 initiative.
Delivery courier on bike
The Future of Work in California project examined 27 occupations from nine different regions across the state.

As part of the California 100 initiative, researchers at the Lab and SIEPR examined where the Golden State has been, where it’s at, and where it’s headed when it comes to possible scenarios and policy alternatives for the future. The large-scale report, The Future of Work in California, examines several facets of the California labor market, including its polarized workforce and the erosion of its middle class.

Future of Work in California website

Stanford Digital Economy Lab and SIEPR to evaluate the future of work in California

California 100 website

5 / Fall conference

Building the New Economy: Data as Capital

Our fall conference reminded us that as humans continue to develop new technologies, we also must reimagine how society is organized so that data serves all communities.
Stanford visiting scholar Sandy Pentland delivers the keynote address at our fall conference.

As humans continue to develop brilliant new applications of emerging technologies, such as web3, we need to reimagine how our society is organized so that data serves all communities. The speakers and panelists who participated in “Building the New Economy: Data as Capital,” a special Stanford Digital Economy Lab event as part of Stanford Digital Assets Week, explored the feasibility and implications of human-centered web3.

Recap of Building the New Economy: Data as Capital

Playlist: Building the New Economy: Data as Capital

6 / Spring workshop

Avoiding the Turing Trap

Our first-ever in-person event brought together researchers and experts to explore the dangers of incentivizing automation more than augmentation.
Nela Richardson, chief economist of ADP, delivers the keynote at our spring workshop.
Nela Richardson, chief economist of ADP, delivers the keynote at our spring workshop.

What will the workplace look like in 20 years with the rise of artificial intelligence and other digital technologies? Our daylong workshop, Avoiding the Turing Trap, featured interactive panel discussions and presentations by Lab-affiliated researchers showcasing their recent work. Erik Brynjolfsson opened the event by framing the opportunities and challenges of human-like AI. Nela Richardson, chief economist at ADP, closed the day with her keynote address, “AI’s People Problem.”

Recap: Avoiding the Turing Trap

7 / Fall workshop

Decentralized Society: Digitization, Democracy, and Civil Discourse

The one-day event examined the challenges of web2 technologies and explored how web3 technologies might solve them.

In October, the Lab brought together leaders from industry, civil society, and academia to discuss the promise and peril of decentralized digital architecture for our political and economic systems. In the workshop, Decentralized Society: Digitization, Democracy, and Civil Discourse, panelists explored key questions such as new governance strategies, privacy paradigms, business models, and content moderation systems.

Recap: Decentralized Society | Digitization, Democracy, and Civil Discourse

8 / Research

Who’s helping you get your next job?

A new study suggests that your weak connections on LinkedIn could help you land a new job.
Man with tablet
The report, A Causal Test of the Strength of Weak Ties, suggests that your weaker connections on LinkedIn may help you get new job prospects more than your strong ones.

While networking on digital platforms can lead to new job opportunities, a study published earlier this year, A Causal Test of the Strength of Weak Ties, suggests that the specific types of connections job-seekers make online matter in terms of their ability to secure new positions. The project, which was conducted by Erik Brynjolfsson (Stanford), Sinan Aral (MIT), Iavor Bojinov (Harvard), and two LinkedIn employees and recent Stanford and MIT Ph.D. graduates Karthik Rajkumar and Guillaume Saint-Jacques, involved more than 20 million LinkedIn members, who made 2 billion new ties and created 600,000 new jobs over a five-year period.

A Causal Test of the Strength of Weak Ties

Looking For a Job? Some LinkedIn Connections Matter More Than Others
Harvard Business Review

9 / Seminar Series

From robots in China to fake news to the future of the metaverse

The Lab weclomed researchers and experts to share their insights about topics and issues that matter to them—and to the future of the digital economy.
Marshall Van Alstyne, professor at Boston University and a Stanford digital fellow, joined us in April to talk about platforms and the fake news problem.

Throughout the year, the Lab welcomed researchers and experts from all over the world to share their work and insights to a larger, broader audience. You can watch (or re-watch) every one of our Seminar Series talks from the past year on our website and on our YouTube channel.

Recap: Our 2022 Seminar Series

10 / Competition

Emerging Technology Policy Writing Competition

The inaugural competition called upon Stanford students to come up with policy solutions that leverage emerging technologies that could enhance the future of work.
The Emerging Technology Policy Writing Compeition awarded a total of $10,000 in prizes to students with the most innovative policy solutions.

The Lab, in collaboration with Stanford HAI and SIEPR, put out a call for student submissions during the summer for innovative policy analysis and solutions that leverage emerging technologies to create jobs. The Emerging Technology Policy Writing Competition awarded a total of $10,000 in prizes to three winning entries. The first place prize went to to Aniket Baksy and Avi Gupta for their policy suggestion, “Expanding AI Adoption is an Opportunity for Job Creation.”

View winners and competition details

And this also happened…

We welcomed several new faces this year to the Lab, including our first-ever visiting scholar, Sandy Pentland. Among those who also joined us in 2022 include Ruyu Chen, Gabriel Unger, Megan Deason, Andrew Wang, Anthony Weng, David Autor, Angela Chen, Christina Langer, and Ruhani Walia. Visit the team section of our site to view everyone who contributes to the Lab.

In June, Lab affiliated faculty member Susan Athey joined the Department of Justice as chief economist of the antitrust division.

Our research teams published or co-published several papers and journal articles, including the working paper, “How Many Americans Work Remotely?” View all of our research and publications.

We launched The DigDig, our bi-monthly digest of stories—some obscure—making headlines in the digital economy. Sign up to receive The DigDig in your inbox..

An attendee asks a question of the panel


Building the New Economy: Data as Capital
A Stanford Digital Assets Week event

Stanford Digital Economy Lab
Fall 2022 Conference

Stanford University
November 17, 2022

Photography by Christine Baker

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Web3 presents new digital means of production and an opportunity to rebalance the relationships between all stakeholders of the economy. As humans continue to develop brilliant new applications of emerging technologies, we need to reimagine the ways our society is organized so that data serves all communities.

The speakers and panelists who participated in “Building the New Economy: Data as Capital,” a special Stanford Digital Economy Lab event as part of Stanford Digital Assets Week, examined the feasibility and implications of human-centered web3, including:

  • — the role of collective citizen organizations in managing the way data is controlled
  • — more resilient and inclusive systems that spread financial and health benefits more widely
  • — the possibilities we unlock when systems are interoperable so that knowledge, trade, and interaction can flow across company and national boundaries.

The agenda featured three panel discussions and a keynote by Stanford Digital Economy Lab fellow Sandy Pentland. Keep scrolling to view videos of the panels and the keynote address.


Building the New Economy: What We Need and How to Get There

Sandy Pentland, MIT; Stanford Digital Economy Lab
Sandy Pentland delivers his keynote address at Building the New Economy: Data as Capital.

Sandy Pentland (MIT, Stanford Digital Economy Lab) opened the day by examining the current state of web3 and providing a brief overview of what companies and policymakers must do to help it grow so that the technology benefits everyone in society. Video also includes a welcome by Christie Ko and an introduction by Erik Brynjolfsson. (Keynote begins at 13:55).

Panel Discussion

The Human Perspective: New Types of Engagement

Lucy Bernholz, Digital Civil Society Lab
Delicia Hand, Consumer Reports
Melissa Valentine, Stanford University
Sheila Warren, Crypto Council for Innovation
Sheila Warren, Delicia Hand, and Lucy Bernholz
Sheila Warren, Delicia Hand, and Lucy Bernholz participate in the first panel discussion of the day.

As digital businesses replace traditional physical businesses and civic systems, we must grapple with the implications of the amount of data, and resulting power, held by a small number of actors. As in the past, citizen organizations may be central in helping balance economic and social power (much like trade unions and cooperative banking institutions formed as a response to the forces of industrialization and consumer banking). This panel discussion explored how community organizations can wield data cooperatives, shared data, and distributed tokenized funding mechanisms to form a system based on collective rights and accountability.

Panel Discussion

Resilient Systems: Making Society Work Better

Jennifer King, Stanford University
Brie Linkenhoker, Worldview Studio
Joshua Tan, Metagovernance Project; Digital Civil Society Lab
Brie Linkenhoker, Joshua Tan, and Jennifer King discuss how web3 and other new technologies can make society work better.

New distributed, technology-enabled organizations may offer a path toward more resilient, transparent, inclusive, agile, and proactive systems, and a better future, particularly in places where existing institutions are either weak or underserved. In this panel discussion, we explore how new architectures could provide significant upgrades to — or enable wholly new — systems of currency and finance, taxation, and privacy.

Panel Discussion

Data and AI: A New Ecology

Dazza Greenwood, MIT Media Lab
Jeff Hancock, Stanford Social Media Lab
Sean McDonald, Stanford Digital Civil Society Lab
Sandy Pentland, MIT; Stanford Digital Economy Lab
Jeff Hancock, Dazza Greenwood, Sean McDonald, and Sandy Pentland talk about building a more beneficial data infrastructure.

To support a world with billions of data owners, producers, and consumers, governed by digital data and AI, we need to build infrastructure that enables interoperability across company and national boundaries. This infrastructure will determine the future of finance and money, civic engagement, and factors that contribute to human flourishing. This panel discussion explores the opportunities and challenges of designing ecosystems of trusted data and AI that provide safe, secure, and human-centered services for everyone.


Closing Remarks

Erik Brynjolfsson, Stanford Digital Economy Lab
Erik Brynjolfsson shares final thoughts of the day.

Stanford Digital Economy Lab Director Erik Brynjolfsson closed the day with a few words about the future of data and decentralization.

and moderators

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