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You need a plan for
Generative AI. We’ve got it.
Workhelix brings together cutting-edge research and comprehensive data to assess your company’s Generative AI opportunity. Our software creates an interactive, dynamic roadmap tailored to your organization.
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“Over the next decade, AI won’t replace managers, but managers who use AI will replace those who don’t.”
“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
MIT Principal Research Scientist and Co-Founder of Workhelix
Bloomberg
“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."
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Erik Brynjolfsson
Stanford Professor and Co-Founder of Workhelix
NPR
“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
Stanford Professor and Co-Founder of Workhelix
New York Times
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
Co-Founders of Workhelix
Harvard Business Review
Our product answers your key questions about Generative AI:
Our software constantly scans 450M+ publicly available data points across 3,000+ jobs and 70,000 work activities. We bring all this information to bear when analyzing your company’s unique circumstance.
Which of our jobs will be most transformed?
How big of a productivity boost can Generative AI bring our organization?
Where should we start?
What do we need to watch out for?
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Workhelix enables your organization to navigate the Generative AI opportunity landscape with data and rigor, rather than relying on gut and instinct.
Our Research
Our team has produced some of the most cited works in Information and Economics.
In collaboration with OpenAI, 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.
We find that (i) ML affects different occupations than earlier automation waves; (ii) most occupations include at least some SML tasks; (iii) few occupations are fully automatable using ML; and (iv) realizing the potential of ML usually requires redesign of job task content.
The emergence of generative artificial intelligence (AI) 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 AI when deployed at scale in the workplace.
A New York Times Bestseller. A “fascinating” (Thomas L. Friedman, New York Times) look at how digital technology is transforming our work and our lives.
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Founding Team
Customer obsessed to the core. Building for 1.25 billion information workers and 41 thousand firms globally.
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Erik is the Director of the Stanford Digital Economy Lab, a Professor at the Stanford Institute for Human-Centered AI, and a Research Associate at the National Bureau of Economic Research. Brynjolfsson is among the most cited researchers in information and economics and his work has been recognized with Ten Best Paper awards and five patents.
Andy is the Co-Director of the MIT Initiative on the Digital Economy and also the Principal Research Scientist at the MIT Sloan School of Management. Throughout his career at MIT and Harvard, he has studied how digital technologies are changing the business world. He has advised many companies, governments, and international organizations.
James brings experience and DNA from top technology firms including Google and Amazon. He previously co-founded a venture-funded AI platform business in the Bay Area and was a founding member of the AWS Private Equity sales team. He has spearheaded digital transformations and cloud migrations for hundreds of mid-market and enterprise customers.
Daniel is the co-author of the transformative “GPTs are GPTs” paper with OpenAI. He is an Assistant Professor at the Wharton School at the University of Pennsylvania. His research focuses on the economic impact of digital technologies on markets, companies, and the Future of Work. Daniel received his Ph.D. from MIT and is a research fellow at MIT and Stanford.
Our Investors
Book a Demo
Book a demo to kick off your firm’s assessment using Workhelix’s Generative AI Exposure Dashboard.