Why Big Tech wants more economists

The Economics Show

Tech companies are increasingly hiring economists and funding research to study AI's economic impact, raising critical questions about conflicts of interest and data

Key takeaways

• Ara Kharazian reports that public-facing economist roles at AI companies are in highest demand ever due to unprecedented interest in AI's macroeconomic effects.
• Ramp's analysis of corporate spending and workforce data shows a 10% headcount increase over two years following intense AI adoption, though causal mechanisms remain complex.

Main topics

• AI economics hiring trends
• proprietary corporate data vs academic research

Notable quotes

"I think you could distill the job of an economist at a company... how do I make Ramp Look Smart? I'd say that is an exercise in branding as much as it is an exercise in PR."

Conclusion

The episode underscores the critical need for independent scrutiny and methodological transparency

Transcript preview

Speaker 3 (0:00) First, AI companies came for the engineers. Now, they're coming for the economists. Beyond hiring teams of economists, the big AI labs are increasingly trying to fund and collaborate with researchers. OpenAI has an economic research team and has launched an economic research exchange to collaborate with outside academics. Anthropic is doing something similar. All great news for economists keen to dig into the exclusive data that AI labs hold, but it does raise a question. Should we worry that to find out what AI is actually doing to our economy and society, we have to ask an AI company? Speaker 3 (0:48) This is The Economics Show with Samaya Keynes. And this week, I want to explore the trend of economists working with or for AI companies, including the potential for conflicts of interest. AI could dramatically reshape our economies and societies. It is incredibly important to ask and answer the right questions about this transition. First, let's hear from Ara Karazian. He is the lead economist at Ramp. a New York-based financial software company that tracks corporate spending. He's got the Substack where he shares insights based on the data that his company collects. For example, the Ramp AI Index shows which AI models US businesses are buying. In August, Anthropic's lead over OpenAI increased. And because we always kick off the show by asking a question for which the answer is on a scale of 1 to 10, I asked Ara... Where he sees demand for economists among AI companies right now? Speaker 1 (1:49) I'm going to answer in a very economics way where there was really very little demand from AI companies. It's out of 10. It is the highest it's been. I myself have never noticed higher demand for this sort of public facing role side, at least of it for, you know, economists at AI startups and companies. We're definitely in a hot moment right now for the job market. Speaker 3 (2:07) Okay, well, why is demand for economists so hot right now? Speaker 1 (2:11) I mean, you can imagine that AI is a very new and nation technology. Everyone wants to know how it's going to affect the economy. It's not showing up in productivity statistics. So you want to get as close to the data and the users as possible to understand first who's using it at all, and then how are those firms using it. And so you can imagine there's demand for that kind of data, both from governments and from investors and the financial markets, but also from the general public too. But there is also a history here. AI companies are not the first to start their own economics research function. I think it started with the big banks around the time of the financial crisis. You didn't see tech start to do it until a similar rupture in public trust, Cambridge Analytica, when tech companies then became the sort of ire of the general public. And then now you have this sort of new era where AI companies similarly have this sort of public trust issue. trying to argue both in favor of their technology in front of the government and also in front of consumers, where there is very little data otherwise available to understand how this technology is affecting our day to day. Speaker 3 (3:15) I mean, what you're describing sounds like economists are kind of involved in an elaborate PR exercise, right? Partly it's kind of shaping the narrative. They're the ones that have access to the data. The companies have an interest in, you know, rebuilding that trust with whoever. And so, yeah, economists are just part of that. Can we talk about Ramp specifically, which is where you are the chief economist? Why does Ramp have a chief economist? Speaker 1 (3:42) Well, you can think about the questions that we got asked by our own customers. So Ramp is an AI finance platform. So you can think about the data set that I work with by thinking about our core products. So let's just say corporate cards and bill pay and invoicing. So essentially, the whole universe of business spend, everything except for payroll, is what I get to see. And as a researcher, that's such a privilege because it's both a very broad set of businesses. It's a very broad set of the investments that businesses are making. It's also highly granular because you can see the line items on bills and receipts. And so we have found that we can start publishing aggregate and anonymized statistics from our data set about how businesses are investing in a new and nation technology, something like AI or something else, and share that data, ideally with the purpose of helping other businesses, whether they use Ramp or they don't use Ramp, also make better decisions and become more productive. Speaker 3 (4:35) But it will be helpful if they use Ramp, right? I mean, part of the idea is to, you know, get Ramp into the public eye. Speaker 1 (4:41) Well, look, I think it's an extremely competitive market. But if you're a business and you are trusting your money and finances with another software company and you're picking between them, ideally, you want to think that that company is thoughtful about... trends in the market and is smart about how your business works and how other businesses work. And so in many ways, you know, I think you could distill the job of an economist at a company. Certainly the way I see my job is how do I make Ramp Look Smart? I'd say that is an exercise in branding as much as it is an exercise in PR. Speaker 3 (5:15) Speaking of smart, let's talk about some of the efforts you have made to make Ramp Look Smart. So I remember seeing the research that you put out looking at growth in AI companies and jobs? Speaker 1 (5:30) Everyone wants to write the paper about how AI is going to affect the job market. Very few companies, if any, have the perfect data set to answer that question. Ideally, you want a data set that shows, hey, these firms adopted AI, these firms didn't. How did jobs change over time? So we put out a paper at the end of June where we use ramp data on business adoption, combine that with workforce data from Revelio Labs. And we tracked exactly that. And we found that companies that use AI intensely see a 10 % increase in headcount over the two years following adoption. But notably, there is no statistically significant change amongst the companies that use AI with low intensity. But all to say is that there's so little data available to assess how AI is actually going to affect jobs in the economy. or how businesses that are using AI are actually hiring differently, whether they're hiring more or less. The AI companies can't produce that kind of research. You know, they don't necessarily have that appropriate data set that shows, hey, these firms used AI. They don't know the firms that didn't use it or used a different model. In any case, it's hard to trust the information that's going to come out from an economics team at an AI company that might be directly interested in the result that says, hey, AI is great. It's going to create jobs. From our perspective, you know, I don't have an investment in whether the result is good or bad. And we don't have a financial interest one way or the other. Speaker 3 (6:52) I mean, the tempting conclusion to draw from that is that, you know, AI is supporting that employment growth. But it could just be that, you know, the kinds of companies, maybe, you know, small startups that would be particularly fast growing are also the most likely to be using AI. So it's not that the AI is causing the job changes, you're just picking up something else. Speaker 1 (7:12) Well, I think that's a good point. We did control for that. And I still think a little bit of both is happening because it's absolutely true that the companies that are going to use AI in the first place are early adopters of this new technology. They were already growing faster pre-adoption. So the main specification we used in our paper was to compare firms that adopted AI to firms that eventually adopt AI but