As nations engage in a race for global advantage in innovation, ITIF champions a new policy paradigm that ensures businesses and national economies can compete successfully by spurring public and private investment in foundational areas such as research, skills, and 21st century infrastructure. Our research on productivity issues analyzes past, present, and future trends in productivity, and advances policies to drive robust productivity growth, including through tech-based automation.
The Enterprise Automation Imperative—Why Modern Societies Will Need All the Productivity They Can Get
Contrary to common belief, enterprise automation is not a cause for alarm, but instead a societal imperative. Modern nations will need all the productivity they can get to address today’s ever-more-resource-constrained challenges.
More Publications and Events
October 20, 2022|Op-Eds & Commentary
Korea Needs More Robots To Be Globally Competitive
For many years Korea had the honor of leading the world in industrial robot adoption. But that lead is now in doubt, as other nations, especially China, but also Japan and the United States, saw much faster increases in robot adoption in 2021, according to the International Federation of Robotics.
September 30, 2022|Blogs
Oops: The Predicted 47 Percent of Job Loss From AI Didn’t Happen
It’s been nine years since Oxford professors Frey and Osborne’s dystopian forecast came out, so it’s worth looking at what happened to U.S. jobs with the increase of new technologies.
September 21, 2022|Events
How Can Policymakers Encourage More Robo-Lawyers?
Watch the Center for Data Innovation's panel discussion about the potential for AI-enabled robo-lawyers to provide legal services, the challenges in providing these services today, and steps policymakers can take to allow the development of tech-enabled legal services.
July 25, 2022|Blogs
Fact of the Week: The Midwest and Great Plains are America’s Regional Leaders in Industrial Robot Usage
Industrial robot concentration is especially high in Michigan, where 39.5 percent of manufacturing employees had exposure to them in 2019.
July 5, 2022|Reports & Briefings
No One Talks About Too Much Automation Anymore
“Defending Digital” Series, No. 7: Remember all those breathless warnings that artificial intelligence would soon eliminate a wide range of “routine” jobs? So far, pretty much the opposite has occurred. Given today’s widespread worker shortages, corrosive inflation, and vast societal challenges, America clearly needs all the automation it can get.
July 5, 2022|Blogs
Fact of the Week: Each Hour Worked Contributes Over $16 More to GDP in the United States Than It Does in Canada
While U.S. labor is currently more productive than Canadian labor, it is losing ground both in terms of pure productivity and price competitiveness.
June 21, 2022|Blogs
Fact of the Week: The Digital Economy Accounted for 9.6 Percent of GDP in 2019
The digital economy accounted for 9.6 percent of US GDP in 2019, or $2.05 trillion.
June 13, 2022|Blogs
If Congress Wants to Help American Workers, It Should Not Require Two-Person Train Crews
As technology such as Positive Train Control systems has improved, and further advances in autonomous systems look promising, freight rail companies would like the flexibility of operating trains with less than two operators, not so they can raise profits, but so they can reduce prices to better compete with the trucking sector.
March 28, 2022|Op-Eds & Commentary, Blogs
Fact of the Week: Teleworking Options Are Expected to Remain Available After COVID-19 for 70 Percent of Workforces Employed in Knowledge-Intensive Services
Managers found that company productivity improved under a companywide teleworking policy, with the strongest ratings on productivity improvement made from managers of firms in “hybrid” models, where workers share time between the home and office.
March 14, 2022|Op-Eds & Commentary, Blogs
Fact of the Week: Large Firms Implementing Artificial Intelligence Enjoyed Additional Productivity Growth Within Just Three Years
Time-lag implementation in the regression also showed a delay of three years between the point of AI adoption and return on productivity growth, indicating an investment delay for AI that could also explain previous literature gaps.