Open Source Summit NA 2025 | Frank Nagle, Linux Foundation

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Frank Nagle

Advising Chief Economist

The Linux Foundation

Code, community and the future: 13 takeaways from Open Source Summit NA

Beyond uniting developers under shared ideologies, goals and pain points, Open Source Summit North America ignited conversations at the intersection of code, community and change.TheCUBE goes live with insights at Open Source Summit NA

Research shows open source fuels economic growth, AI innovation

Open source is shown to contribute $9 trillion in global value, according to new research from The Linux Foundation.That number combined an estimate of time saved by not having to develop software covered by open source and the profits reaped by companies using open source in production, according to Frank Nagle (pictured), advising chief economist at The Linux Foundation. Now that AI is a part of the picture, the estimation process is changing.The Linux Foundation’s Frank Nagle talks about the economics of open source.“As we move more into trying to understand the value that open source AI is creating, we have to expand how we’re measuring and what we’re thinking about,” Nagle said

play_circle_outline Exploring Open Source Summit North America 2025: Insights from Paul Nashawaty and Frank Nagle, Chief Economist at the Linux Foundation

play_circle_outline Unlocking $9 Trillion: Quantifying the Economic Value of Open Source Research for Society and Business

play_circle_outline Open source AI introduces new metrics beyond just code value.

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Frank Nagle, Linux Foundation

Frank Nagle

Advising Chief Economist The Linux Foundation

In this Open Source Summit North America 2025 interview, Frank Nagle, Advising Chief Economist at the Linux Foundation and Harvard Business School professor, joins theCUBE Research’s Paul Nashawaty for a deep dive into the economic value and future direction of open source software. Nagle shares how his latest research estimates that open source contributes over $9 trillion in global value – an amount that remains conservative when accounting only for in-production enterprise-use.

The conversation explores how organizations are measuring the ROI of ope... Read more

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Frank Nagle, Linux Foundation

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Paul Nashawaty

>> Hello, and welcome to the Open Source Summit North America 2025. My name is Paul Nashawaty, and I cover the app dev space and all things open source. So this is really a great playground for me to be in, and really exciting times to be here. I'm joined today by Frank Nagle, Advising Chief Economist at the Linux Foundation. Frank, how you doing?

Frank Nagle

>> Good, good. Great to be here with you.

Paul Nashawaty

>> Yeah, it's great to have you here. Why don't you tell the audience a little bit about who you are and what you do?

Frank Nagle

>> Sure, yeah. So as you mentioned, currently I'm the Advising Chief Economist for the Linux Foundation, which means I think a whole lot about how open source and all the different foundations under Linux contribute value to society, and also how we can convince businesses that it's good for them to let their employees contribute to open source.

Paul Nashawaty

>> Yeah, open source is definitely a growing area. Obviously, that look at the show floor here today.

Frank Nagle

>> That's right.

Paul Nashawaty

>> The events with Open Source, it's really, really taken off. So let's jump right into some of this, because I know that there's, obviously, a big push here around the economic impacts, and what that means to open source. I've seen that you've done research around open source, that adds about $9 trillion to the global value that boosts productivity. This is obviously, an area where application monetization, application development fits nicely together. Right?

Frank Nagle

>> Mm-hmm.

Paul Nashawaty

>> So can you expand a little bit about that, and talk a little bit about that research?

Frank Nagle

>> Sure, yeah. So in addition to my position with Linux, I'm also a professor at Harvard Business School, although I'm moving to MIT Sloan in a few weeks. And so, a lot of what we think about is how do we quantify things that are hard to put a price tag on? And so, open source, the price is generally zero. The amount of it that's out there is very hard to measure, because we can copy it and share it for free. And so thinking about a bunch of different ways to analyze that value, we tried to think about what type of price can we put on this. And so we could think about how much effort had to go into this, and if people had to be paid to do that, how much would it cost to recreate these software packages, and the applications with them? And so that's the kind of methods that we use to then... And we paired that with some prior work that we've done with Linux, on how we can measure the amount of open source that's out there. So under the census project that we did with Linux, we look at how much open source is being used by companies in production. So not just, what open source is out there, but what of it's actually being used by companies? And so with those two things together, we're able to come to these numbers around $9 trillion. And actually, that's an underestimate of the true value because we're only looking at the packages that are baked into other applications or other things like that. We're not looking at some of the more standalone open source projects as well, which clearly added a lot of value as well.

Paul Nashawaty

>> Yeah, I mean, obviously, open source is growing in popularity. When we look at, and I know when I talk about my practice, I talk about past, present, and future of applications.

Frank Nagle

>> Sure.

Paul Nashawaty

>> I talk about the heritage environments. And the number one thing I hear from CIOs is, the application modernization is their number one initiative.

Frank Nagle

>> Sure.

Paul Nashawaty

>> AI, of course, we have to have AI in this conversation, because that's a big part of it.

Frank Nagle

>> Of course, yes.

Paul Nashawaty

>> And when we looking at these heritage apps, they need to have the way to extract the data and move the data around.

Frank Nagle

>> Yes.

Paul Nashawaty

>> So when we look at the economics around open source and the impacts, the emerging fields like AI, what metrics or indicators do you help prioritize open source value with AI? How does that work together?

Frank Nagle

>> Yeah, absolutely. So in the work that we did on open source software, we could look at the code, and that was most of what we wanted to know about the value. With open source AI, it's obviously a different bucket, because we also have to think about the data that's being used to train it, the inference that's being done later on in the process, and thinking about the way that we think about what is open. Is it the code? Is it the weights? Is it the data? Is it everything? And so I think, as we move more into trying to understand the value that open source AI is creating, we have to expand how we're measuring and what we're thinking about. So that's some of the work that we're going to be doing at the Linux Foundation, is trying to get more data on data itself, on the models, on how it's being used, and how companies are using it, to be able to then say, "Okay, yes, we can measure just the value of the code itself, but it's really about the impact that it's having on organizations and the way that they do business.

Paul Nashawaty

>> Yeah, I mean, that makes a lot of sense. I get that. I totally understand that. And from a green field opportunity, that makes a lot of sense.

Frank Nagle

>> Sure.

Paul Nashawaty

>> But when you think about bridging the gap between old and new, how does the metrics that you're talking about compare to traditional models?

Frank Nagle

>> Sure. No, that's a reasonable question. And I think the models related to everything with AI are going to change. And this is some of the work we've done on GenAI and how it impacts coders. We've shown that it fundamentally changes the way that they balance their time. So they spend more time coding and less time doing project management and other things like that. And so I think that's going to be one of the bigger shifts that we're going to see, is that it's not just about making people faster, more efficient, and can we make the same thing more cost-effective, but it actually is going to change the way that people work. And as a result, the way that they think about the apps that they're using, and the monetization schemes and everything else, because it's going to change, my day job used to be this, but now it's this, and how do I spend my time? And that's all going to change as well.

Paul Nashawaty

>> Yeah, that makes a lot of sense. I mean, I think that when we look at the metrics and how things are changing, what I'm seeing in my research is that the IT budget is typically the budget that's spending for all projects. Right?

Frank Nagle

>> Sure.

Paul Nashawaty

>> But now, IT has a budget of 25% or more is carved out for just AI projects.

Frank Nagle

>> Oh, wow. Yeah, that sounds about right.

Paul Nashawaty

>> So it's a lot of money being carved out. And that money is being used for strategic investments, right?

Frank Nagle

>> Yes.

Paul Nashawaty

>> But there's also kind of this understanding of, how is the money being used? And for what initiative?

Frank Nagle

>> That's right.

Paul Nashawaty

>> And unfortunately, a lot of organizations, what they're doing is they're just going, okay, well, we need to have some type of AI metric, so they throw money at something. And that's not the right approach.

Frank Nagle

>> No, I agree.

Paul Nashawaty

>> So when we talk about partnerships and the expanding ecosystem, there's a big part of OpenShift through partnerships. There's a big part of the advocacy around, obviously, with here at the show, we see a lot of partnership, a lot of collaboration. This is kind of different depending on the different alliances that you have, especially when you think of government engagement or academia. Right?

Frank Nagle

>> Yep.

Paul Nashawaty

>> Academia's different. How do you balance between the, I don't want to call it the professoric approach, but the academian approach, versus the government approach, versus commercial approaches?

Frank Nagle

>> Sure. Sure, yeah. So a lot of the work that I do falls under this heading of collaborate on the core and compete on the edges. But every industry, what is the core? Where you should be collaborating, because it's going to save you costs, and it's not really the thing that's differentiating for your customers? That's going to be different from industry to industry. And so I think what a lot of the academics thinking about open source are, everything should be open source. And some governments also think that. Although, some now, there's a debate, especially in AI, should we have more open source? Or should we actually restrict open source AI? And I think that's playing out in DC right now, and these kind of discussions of what's good for us as a society? What's good for our companies? And what's good for the world? And that's the balance and the tension that I think is happening right now in the open source AI space, is how do we find that right balance between what's closed, what's open, and who is doing what, and how we're driving innovation?

Paul Nashawaty

>> I like that. Driving innovation is a key part of this. So I want to double click on that. But I do like the fact that, when we talk about compliance and regulation, that has to occur. Right?

Frank Nagle

>> Yes. Yes.

Paul Nashawaty

>> Especially, as we see in AppDev, we see that the expansion, and I should say explosion, of application development that's occurring, it's occurring at all levels now.

Frank Nagle

>> That's right.

Paul Nashawaty

>> It's occurring at the professional developer. It's also occurring at the lines of businesses. So you need to have governance and regulations to compliance.

Frank Nagle

>> That's right.

Paul Nashawaty

>> Right? I mean, for example, when you use tools like AI, AI needs to be, the right guardrails need to be in place. Otherwise, you could do something very bad, and very quickly.

Frank Nagle

>> I think that's right. And I think there's a couple of things to keep in mind there. One is that, when we're thinking about regulation around topics like AI, we have to remember it's a general purpose technology. So we can either protect the technology that's being developed itself, or we can encourage the usage of the technology by others who are developing apps and using it to create new things. And I think that's a tension that's often overlooked and we need to think more about. And then on the safety side of things, I think it's important to remember that lots of people have shown that we can make closed source AI do things that it's not supposed to do. And so I think, yes, we have to absolutely think about safety and build the guardrails around it, but I think we have to have those guardrails that apply to proprietary, as well as open source AI, to make sure that we as a society, and we the people, are deciding what the right trajectory for this groundbreaking, genre-shifting technology actually is.

Paul Nashawaty

>> I like that. I like that, the way you frame that up, because the thing that I think about is, there's the innovation piece. I'm going to come back to that, because I think that's a big part of it. 70% of the market that I serve is the emerging market.

Frank Nagle

>> Okay, sure. Yes.

Paul Nashawaty

>> It's the startups that are coming up. And when we think about all the ways to modernize, and think about how we're moving forward with different solutions, and having those guardrails, and governance, and compliance in place, that all really matters. How do we look at enabling open source to really help startups get their, I don't know, foot in the door? How do they get going with their open source initiatives?

Frank Nagle

>> That's a great question. I think that so many startups I've talked to, they use open source. And that's great, and it helps them get to the next level faster, cheaper, quicker. But they feel like they don't have the resources to give back to open source. So I was talking to a four-person AI agent company in Germany, and they say, "We want to get back to open source, we just don't have the time. We only have four people and we've got to build the product." And so I think the important thing for them to remember, and for lots of startups to remember, is that by contributing, you're becoming part of the community, and you're going to help potentially shift that open source project in a direction that's beneficial for you. And so with a small amount of investment, you can get more productive value out of using it. And some of the research that I've done in the past shows that companies that give back to open source, in any domain, can get as much as two times the amount of productivity out of using open source, as those who just use it, but don't actually contribute back to it. So I think from a numbers percentage perspective, it makes a lot of sense to give back as well.

Paul Nashawaty

>> I agree with that. I think that you're right. I think it's, one of the other big challenges that I talk to CIOs about with these modernization initiatives, it's skill gap issues.

Frank Nagle

>> Yes. Sure.

Paul Nashawaty

>> And resource issues, right?

Frank Nagle

>> Yep.

Paul Nashawaty

>> So they're using tools like AI. But the thing is, using and leveraging open source allows for that acceleration of the application, acceleration of what they're trying to drive forward.

Frank Nagle

>> That's right.

Paul Nashawaty

>> And part of that acceleration is also about testing and making sure it works, right?

Frank Nagle

>> Yes, a hundred percent.

Paul Nashawaty

>> A lot of organizations, what you have to kind of understand is you have to slow down and go faster, almost, right?

Frank Nagle

>> Yes.

Paul Nashawaty

>> And that's kind of a weird concept, because you have these sprint reviews, and you're trying to get things out the door every two weeks, or whatever it may be.

Frank Nagle

>> That's right.

Paul Nashawaty

>> But we find in our own research, that 24% of organizations want to release code on an hourly basis, yet only 8% could do so.

Frank Nagle

>> Wow, okay.

Paul Nashawaty

>> And so they need to utilize those open source technologies and the stacks in order to move faster.

Frank Nagle

>> That's right. And I think one of the places that I've seen in talking to developers, that really helps speed things up, is in the unit testing. And the testing and the bringing it to mart, those types of things, so that you, in the old days, pre-AI, you had to write all those tests and do everything yourself. But now, that's an area where, A, it's okay if the code that the AI is writing isn't perfect, because we're still not in the world where everything is perfect coming out of AI. But, so the human is doing the part that's most important for the human to do. And the machines are doing the part that is important, but is more readily done by the machines. And so I think that's where we're going to see a speeding up of processes. So if we can automate testing, automate some of the things that put it into operations, then we'll be racing with the machines, rather than racing against the machines.

Paul Nashawaty

>> Yeah, I agree. I think that there's a lot that needs to be taken into consideration with that. And it is about balance between the business KPIs and the release of what you're doing. I do think that we've become a society of almost instant gratification too, where a release of something would take, I don't know, 18 months in the past, now it takes like 18 minutes now, which is crazy. But if we think about, so I want to talk about ROI a little bit here.

Frank Nagle

>> Sure.

Paul Nashawaty

>> So let's talk about the monetary returns. When you think about open source and the impacts, we talked a little bit up front about that. I think that's a good way to end a session here, is talk about the ROI and open source.

Frank Nagle

>> Yeah, I think it's, ROI is a very important... I'm a professor at a business school, we talk about ROI all the time. I think it's a little bit harder to measure sometimes, especially on the contribution side of open source. On the usage side, okay, we're now using this open source software for free. We used to pay whatever for whatever the proprietary version was. That's easy. That's why everybody's using it. But contributing back to it is much harder to measure. And I think myself, and others, in talking to folks here at the conference, they're developing new metrics and new KPIs to show by contributing back, we were able to save the company X amount of dollars, or whatever it is. And those, I think, are the metrics that people are developing right now, that are going give even more fuel to the arguments, that we should not only be using it, but contributing back to open source as well.

Paul Nashawaty

>> Yeah, I agree. I agree. Frank, we could talk about this all day. This is all outstanding. Thank you for coming on the show with me today.

Frank Nagle

>> Excellent. Yeah, of course.

Paul Nashawaty

>> This has been good. I know you're busy. I won't keep you much longer, but this has been really great to have you on.

Frank Nagle

>> Great.

Paul Nashawaty

>> Thank you very much.

Frank Nagle

>> Thanks so much.

Paul Nashawaty

>> And I am Paul Nashawaty, and I'm coming to you live from the show floor at Open Source Summit in North America 2025. And thank you to the audience for watching theCUBE, the leading source for tech news.