Edtech Insiders
Edtech Insiders
Jeff Maggioncalda on the Coursera Effect and How AI is Driving Global Learning and Workforce Development
Jeff Maggioncalda served as the CEO of Coursera from June 2017 to January 2025, leading the company through remarkable growth to over 160 million learners and 7,000+ institutions, delivering high-quality learning content from top universities and industry leaders. Under his leadership, Coursera expanded its reach, navigated the pandemic, embraced AI-driven learning, and became a publicly traded company.
Since recording, Coursera announced that Jeff has retired from the role, and Greg Hart will succeed him as the CEO.
💡 5 Things You’ll Learn in This Episode
- How Coursera is evolving its AI-powered content to serve not just developers but also everyday professionals using AI in their jobs.
- The role of generative AI in transforming the accessibility and personalization of online learning.
- Insights into Coursera’s latest AI-driven initiatives, including personalized tutors and automated content creation.
- The changing landscape of workforce upskilling and how Coursera is adapting to meet employer demands.
- Jeff Maggioncalda’s vision for the future of online education and the integration of AI in learning.
✨ Episode Highlights
[00:00:37] Coursera’s evolving role in edtech.
[00:04:21] How Coursera expanded to over 1,000 AI-related courses and the shift toward workplace AI adoption.
[00:10:45] The role of generative AI in democratizing education and personalizing learning at scale.
[00:15:22] The challenge of balancing AI innovation with academic rigor and credibility.
[00:22:30] How AI-driven career certificates are helping professionals transition into new roles.
[00:29:50] Predictions on the future of AI in education—Jeff’s perspective on what’s coming next.
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This season of Edtech Insiders is once again brought to you by Tuck Advisors, the M&A firm for EdTech companies. Run by serial entrepreneurs with over 25 years of experience founding, investing in, and selling companies, Tuck believes you deserve M&A advisors who work as hard as you do.
[00:00:00] Jeff Maggioncalda: What's happened since then to your point is the impact and the relevance of AI has gotten much, much bigger to Coursera because of generative AI. One thing on the content side is that the courses are no longer only for the people building AI. They are now courses for people using AI because now with generative AI, suddenly it becomes a cognitive tool that virtually everybody in every job role is going to need to learn how to use.
So we've really ramped up. The amount of content we have over a thousand courses on AI now, and not just for the builders, but for the users as well,
[00:00:37] Alex Sarlin: welcome to ed tech insiders, the top podcast, covering the education technology industry. I'm funding rounds to impact AI development across early childhood, K 12, higher ed and work. You'll find it all here at ed tech insiders. Remember
[00:00:54] Ben Kornell: to subscribe to the pod, check out our newsletter and also our event calendar and to go deeper.
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Jeff Maggiancalda joined Coursera as CEO in June 2017, and since then, helped the company grow to over 162 million learners and 7, 000 institutions, served by high quality learning content. From 350 of the world's top universities and industry educators. He previously served for 18 years as the founding CEO at Financial Engines Incorporated.
A company co founded by economist and Nobel Prize winner, William Sharpe. Financial engines grew rapidly under Jeff's leadership, providing high quality online investment advice that has helped millions of people save and prepare for retirement. Jeff has also worked as a consultant at McKinsey Company and Cornerstone Research and serves as a director of SVB Financial Group.
He holds an MBA from the Stanford Graduate School of Business, go Cardinal, and a bachelor's degree in economics and English from Stanford University, also go Cardinal. In his free time, Jeff is a lifelong learner and proud dad and enjoys studying music theory and spending time with his wife and three kids.
Enjoy our interview with Jeff Maggiancalda. Hello everyone. We are so excited to have Jeff Maggiancalda here at EdTech Insiders. You may know him as the Coursera CEO. I know him as a great dinner guest when we had the Google conference. And then also Alex has worked with Jeff and Coursera. So it's so great to finally have you on the pod.
Thanks so much for joining us. Thanks so much for having me. I'm really excited to be here. Before we start with the questions, can you just tell us a little bit about your journey to Coursera? How did you get started and what led you to Coursera?
[00:03:01] Jeff Maggioncalda: Well, I mean, this is sort of a really good luck serendipity story.
I had been at financial engines, which is a FinTech company since 1996. I had just graduated from the business school at Stanford. Turns out there are a couple of professors at Stanford that wanted to start a company using basically algorithms and Monte Carlo simulation to help people with their 401k plans.
And they asked me to write the business plan and raise the first round. And so. I started in 96 as the first employee of Financial Engines. I stayed there for 18 years. You know, we went public 13 years in and it was a long effort with lots of iterations, but then took some time off starting in the beginning of 2015, traveling with my wife and One of the things I did on my time off is I went to Barcelona because I'd never been there and there was the NIPS conference, the Neural Information Processing Society.
And I was like, I was interested in AI. And so I thought, well, this will be kind of fun, like go to Barcelona, learn about AI. And my youngest daughter was living in Malaga, Spain. And I said, come on up and let's let's have fun in Barcelona. So we did. And the keynote speaker at the NIPS conference was this guy named Andrew Ng, who I'd never knew.
I never met him, but I knew he was a Stanford professor and he was writing up on the. Whiteboard that AI is the new electricity and all this stuff. And I was like, this is really, this is going to be a big deal. And this was in, I don't know, 2015, 2016. So, you know, that goes away. I'm like, okay. I left Barcelona and my wife and I did other stuff.
And then I got a call from a recruiter who I had used at Financial Engines to hire my head of product. And he's like, Hey, there's an opportunity that might be interesting to you. It's called Coursera. And my daughters and my wife were big Coursera fans. I definitely knew about Coursera. I've always wanted to be a teacher and I thought this could be amazing.
And my wife was very supportive. And I'm like, wait, that's the Andrew Ings company. And then stepping one step further, one of the lead investors in the series a was Scott Sandel and NEA. And they were one of the lead investors in the early series B round of financial engine. So I had met Scott in 1997.
And, you know, 23 years later, I had the chance to take on this job as a CEO role. And I've been here for about seven and a half years.
[00:05:19] Ben Kornell: It's such a big world and yet it's so, so small in these circles. Incredible.
[00:05:25] Jeff Maggioncalda: And you know, AI and Stanford are both sort of core to the Coursera story. I'd love to hear you talk a little bit about, you know, AI was basically some of the reason that that Coursera existed in the first courses, obviously Andrew and Daphne are AI professors.
And now as we enter this new era of AI, I think Coursera has taken it to a whole other level, both with AI as content and AI as. feature sets. So I'm sure you talk about this all the time. I'd love to hear how is Coursera doing AI. Yeah. Well, yeah, clearly this is a big deal. I think a lot of people don't realize that a major reason that Coursera is here as a company.
Is because two Stanford professors, Andrew and Daphne Kohler, who teach computer science put up in particular, certain kinds of courses that were in very, very high demand and were unique at the time. And Andrew's primary course was a Stanford machine learning. And at the time in 2012, 2011. Machine learning was brand new, and that course and a few other data science courses kind of put Coursera on the map.
So we were created by data scientists. There were some very unique, valuable courses. They were for the builders. You know, people who took these courses were master's degree, PhD level people who wanted to learn. Machine learning, this kind of new technique, what's happened since then, to your point is the impact and the relevance of AI has gotten much, much bigger to Coursera because of generative AI.
One thing on the content side is that the courses are no longer only for the people building AI. They are now courses for people using AI because now with generative AI, suddenly it becomes a cognitive tool that virtually everybody in every job role. Is going to need to learn how to use. So we've really ramped up the amount of content.
We have over a thousand courses on AI now, and not just for the builders, but for the users as well. And then to your point, in terms of features, there's a ton that we're doing in terms of features. We jumped hard and fast with translations. And so we translated over 5, 000 courses into 25 languages. We started with text.
Now we're doing audio. Now we're doing video. So. Everything will be completely translated and the best instructors in the world will be able to speak the languages in their own voices to any language, major language speaker in the world. We have this coach, which is like a tutor that helps learners to millions of people.
We've had that up for over a year now. We have something called course builder for the authors to help you build courses and mix and match courses using AI. They automatically generates assessments. We have a bunch of grading features and feedback features where people can get much faster, more personalized, more relevant feedback.
And then we have a whole set of features on what we call academic integrity, which are anti cheating features, so that it makes it much more difficult to cheat because AI is quite good at sort of watching what you're doing, how you're speaking, how you're typing. And so we have a way of Basically using AI to help detect and deter student misconduct.
And so there's a wide, wide range of things we're doing with AI.
[00:08:29] Ben Kornell: Just to your point around the popularity of AI courses, we were talking about Google's AI essentials course on Coursera with over 900, 000 enrollments, just in that single course alone. One that's just mind blowing. And it does feel like.
We've now entered the future that Andrew and Daphne predicted would occur, but can you tell us a little bit about where are those learners coming from around the world? What are the backgrounds and how is that student population evolving?
[00:09:02] Jeff Maggioncalda: Yeah. So clearly Google AI Essentials is a very big course in terms of enrollment popularity.
And, you know, people are kind of going through and institutions are going through their own adoption curves. I think for me, when I first used ChatGPT in early December of 2022, like, My mind was blown and I thought this is going to be a really big deal. So we jumped on it pretty fast as a company, but the adoption curve for individuals and institutions is a bit slower.
People are looking still at these early introductory courses like, you know, AI essentials and Google also has a new course called prompting essentials on how to use AI. So. People are really just getting started. But when we look at the kinds of learners who are taking these AI courses, and generative AI courses are now the most popular courses on Coursera.
We're seeing more than six enrollments per minute around the world. It's interesting when you look at it by age group. So the most represented group are millennials. 56 percent of the enrollments in generative AI are millennials, followed by Gen Xers, who are 24%. Gen Z is only 15% boomers or 5%. What I think is interesting though, is that if you compare it versus the representation on Coursera, the largest group in terms of representation, sort of over indexing is Gen X.
So there's only 16% of all course enrollments are Gen Xers on Coursera. But 24% of generative AI enrollments are Gen Xers. Versus Gen Z where their overall 18 percent Gen AI is only 15%. So Gen Xers seem to be the ones who disproportionately are taking these courses. By gender, what we see is a troubling gender disparity where it's 5941 males to women on overall course enrollments globally, but 6832.
So there's a disproportionate likelihood that men are taking Gen of AI courses. And then when you look at countries, 38 percent are from India, more than the U S and only 21 percent overall. So the learners of India are clearly going big on Gen of AI. We also have over representation in Colombia, in Bangladesh, in Brazil.
And other countries. So emerging economies are really jumping. At least learners in emerging economies are really jumping on gender. I wanted to double click on an earlier answer. Just is a little bit of an insider question from my experience at Coursera. I remember that, you know, The peer review system was the source of the most complaints from learners.
They love the videos, they love the instructors, they love the platform, but they would wait for a long time for peer reviews. They would complain about the quality of the peer reviews. And you mentioned how you're using AI for feedback. Can you just expand a little bit, because I think this could be a humongous change in the overall learning quality of Coursera's courses.
I think peer reviews is a great example of the ways that this technology can solve valuable problems. I mean, and that's what I would advise for CEOs and any leaders in businesses is, it's one thing to look at the capabilities of the technology, and it's important to understand that sort of frontier feasibility.
But the key thing is to say, what are the biggest problems that your customers are facing or the biggest problems in your business model? And then ask yourself, because those are pretty well known for anyone who's been paying attention as a leader, like, you know what your customers want, you know what you want to fix with your business.
How might this new technology address some of those pain points? So when generative AI first came out and I was playing with chat GPT, immediately. Because we knew that the peer reviews were slow and often the feedback was poor. We're like, wait, this might be able to solve that problem, a problem we've wanted to solve for a long time.
Now really quickly, peer reviews in 2012 or whenever they were created, which was before I got to Coursera in 2017, the only way to score written submissions Is with the human brain. I mean, they're just computers couldn't do it when Coursera was founded. And so it was a pretty innovative technique, which is to say, hey, how about we create these peer reviews where the author of a course can ask for a written submission.
They will also provide a scoring rubric and then. Other learners will grade each other's submissions. So you have all these learner human brains, you know, grading according to a rubric and giving feedback to other learners. So that, like, that was the only way to scale personalized feedback of written submissions.
Well, we pretty quickly saw that General AI, especially if you give it the instructions of the submission, and you give it the grading rubric and some examples, It's really good at scoring these submissions. So we've now basically added to every peer review by default, AI gives you the review, and then you can click a button to say, I don't really like this.
I would like a human to give me the feedback, but we've been interviewing the learners, first of all, it's lightening fast, what used to take days now takes seconds. The quality of the feedback is way more consistent and personalized and overwhelmingly, learners are like, I want the AI feedback, it's faster, it's better, it's more helpful, like, it's just way better than the quality that people have been getting.
Yeah. And one out of a thousand peers will give you an incredible, you know, response, but AI gives it every time. It's really exciting to hear
[00:14:16] Ben Kornell: about. Yep. As the business guy here, I'd love to dive in a little bit on the business model evolution, you know, back in the day, there was a sense of, Oh, Coursera is going to disrupt higher ed and disrupt our education system.
And there's been this incredible evolution where Coursera has. with higher education, with companies, with consumers. You have consumer businesses that are served by universities, creating courses. You have the Google example is a great one. Cause Google could be both a customer and a producer of the learning.
So you've got B2B as customer, as well as content. Of course, like all of us in entrepreneurship, one on one are told focus, focus, focus, know your customer, know your market. And now here you have this way in which. Universities, learners, direct to consumer, and B2B are all customers and all content producers.
How do you manage that, and how do you think about that ecosystem?
[00:15:15] Jeff Maggioncalda: Yeah, so marketplaces can be tricky, because it's like, well, who really matters, your suppliers or your customers? And you really do have to balance it off. Any kind of a marketplace has to make sure that there's enough supply and enough demand to make a market, and then that you're going to make a market.
Clearly, there's Two really important constituents. I think your point is a good one. People didn't know in 2012, what MOOCs, these open online courses were going to do to higher education. And it's still evolving, but to your point, to a large degree, Coursera has become something of a collaboration platform because you've got branded universities, Duke, Yale, Stanford, Princeton.
And on the business side, Google, Microsoft, IBM, Meta, they're all publishing courses that before people couldn't get access to. To your point, a lot of the companies that publish courses also hire Coursera to train their employees. Google's a big customer. I mean, basically all the big companies are essentially customers of Coursera because they need to train their employees on lots of things.
But what's also really cool is we have examples like the University of London who has a bachelor's degree in computer science. And part of the curriculum for that online degree, you can get the whole degree online and it's a real bachelor's degree that comes from University of London. But part of the curriculum is a Google I.
T. certificate. So a professional certificate that Google created on I. T. help support. And what they do is as you're going through the University of London curriculum, you are taking courses from Google instructors. And even if you're not in the degree program, you can take that Google certificate and then apply it for credit towards your college degree.
So now you have this world where industry is creating training programs and universities are recognizing academic credit and integrating the industry content. Into their college degree programs, which I just think is super cool. Yeah. For 10 years ago, unimaginable. I've just, the idea of universities accepting credit for courses from corporations, it just would have made no sense.
I think it's a real victory. So speaking of that sort of alternative credentials, transferable, all of this amazing skills work, Coursera does two things that I would love you to highlight. Cause I think they're really interesting in terms of the transition to work. One is the career academies. Really, really interesting.
The another is the corporate benchmarking for skills. I think that's incredibly interesting. As we move into this skill based world, I think both of these are really poignant features. I'd love to hear you talk about them. Yeah. So with respect to skills, you know, one of the first things that I really put an emphasis on when I joined Coursera as you know, you probably remember Alex, I was like, Hey.
It's not just content. The reason people come to Coursera is not like Netflix, where you literally come for the content. You're like, you watch the movie and you laugh and cry. That's it. On Coursera, it's the content. It's delivered in a learning experience. So the way that you interact with that content, the way you do hands on labs, the way that you get feedback.
I mean, that's all part of it. All the technology that delivers the content. But fundamentally, you're there to learn skills. And so we'll talk about that in a moment. And ultimately people want to show employers that they have those skills. So you want to do assessments and get credentials that prove that you have the skills.
And so when I think about Coursera as a learning platform, yeah, content is, is a piece of it, but it's content. Delivered through a learning experience to develop particular skills for a job role that when you assess them and you successfully master those skills, you get a credential from a trusted institution and you can use that to advance your career.
Like that's the full scope where skills really come into this on the benchmarking side is we've had this thing called a skills graph. Alex, I'm sure you remember this for a long time, but with generative AI, we've been able to really rapidly enhance it so that. Every piece of content in every course is tagged with certain skills.
So we have this large skills taxonomy with thousands of different skills. And it's like, Oh, in this course, in this lecture, they teach this skill, this skill and this skill at this mastery level. And then in this course, in this module, they teach this skill and this skill. And then we say, okay, so these courses teach these skills.
And these jobs require these skills. And so then you can say, well, if this is your job, here are the skills you need, and if you need those skills, here's the courses you take. And then we could really help people figure out, you know, to advance your particular career and learn the skills you need to, what content should you be taking?
So Career Academy is really a way of having preset learning programs coming from industry that teach someone with no prior work experience, and you don't need a college degree. What are all the skills you need to become an entry level, you know, project manager, cybersecurity analyst? UX designer, front end web developer.
We have over 70 training programs for entry level jobs, and that's what Career Academy is. You learn the skills for the job, and then you get a certificate from, a professional certificate from the industry provider saying you completed the meta database engineer professional certificate, and so you have these skills.
On the benchmarking, what's really neat is when you have millions of learners all taking these courses, and you're watching all of their assessment performance, you know, are they getting this right? Are they getting this wrong? How are they doing? You can start comparing which learners know stuff the best, like how do learners at a telecom company in France compare in their understanding of, say, machine learning, say software engineers at a telecom company in France, how do their machine learning skills compare to the average machine learning engineer in the U.
S.? Or, so you can do it by region, you can do it by industry, you can do it by job title, and you can do any sort of skills, and you can benchmark, you know, anywhere in the world. You can benchmark someone's skills against someone else, at least as evidenced by their performance in the courses. And within an organization, you can benchmark your employees skills as well.
Absolutely, which is a big part of the whole ROI claim, which is, Hey, put in Coursera, and not only will they like watch videos, they'll learn skills. You'll be able to actually see the skill level they're achieving, and you can benchmark and identify who in your company has skills that are valuable at a certain level of proficiency.
[00:21:32] Ben Kornell: Yeah, as I hear this, too, I'm thinking at it from an assessment lens. So much of the challenge of higher ed and higher ed's evolution are these different credentialing regimes across different bespoke regions in the world and higher ed and high school and states and so on. And by breaking things down to a skill level, you've actually created a universal global And for example, I might get the meta certification, but then use that to get a job.
That's not even at meta just because it's a known benchmark in the space and I've demonstrated skills.
[00:22:09] Jeff Maggioncalda: Yeah, and I think that that was true from that very first course that's that Stanford machine learning course from from Andrew. I think a lot of people were data scientists who like they weren't teaching machine learning in college.
And so a lot of people were like this is gonna be my credential to not only learn the skills, but to say I got the machine learning certificate from Stanford. I got it on Coursera. But that idea that you get a credential because you have a skill and you can use that to advance your career is a really big predicate of
[00:22:37] Ben Kornell: The
[00:22:37] Jeff Maggioncalda: whole Coursera
[00:22:38] Ben Kornell: mission and the predicate also of being a global first company, always thinking about the world's learners and not just specific geos.
It almost flies in the face of conventional ed tech wisdom, which is focused on, you know, one market, you know, get consolidation there and then move to others. Last question, you know, we are seeing trends where the kind of global education space is converging and AI is making through translation through many of these other kind of adaptive content, generative capabilities, the ability to launch a global company, even with a team of five people or 10 people, what advice would you give to CEOs who are navigating this world that is both incredibly dynamic with technology shifts, but also increasingly global?
I
[00:23:26] Jeff Maggioncalda: guess what I would say for the most part is sort of where I started or what we touched on earlier. Especially as a CEO, I think of strategy as a combination of what customer value do you provide? You're like, what problems do you solve for somebody? The second big part of it is what's the opportunity?
Like, what are the economics of solving that? How many customers are there and what are the unit economics of that? And then the third big piece of strategy is what are your, your differential advantages as it relates to AI. And my advice for CEOs is like, look, technology creates disruption. And this is one of the most disruptive technologies that we've ever seen.
Cause it enables us to solve problems that, that weren't solvable before. As an incumbent, I would say like, if you're the CEO of an incumbent company, that's doing pretty well, you better jump on this really fast because there are going to be new entrants. Who don't read your barriers to entry that you had before might not be so relevant in a world of generative AI, where someone could deliver the same value at a much lower cost.
And so be aware that there might be new entrance into your space, whether those are startups or whether those are people in your supply chain, your suppliers might be able to forward integrate into your business and squeeze the economics out of that part of the value chain that you have historically owned.
So I have a whole course on navigating generative AI for CEOs. And I say, like. Look at your ecosystem and really think about who are your current competitors because you're going to start having competitive pressure from other places. Now, on the other side, if you are a startup or you're thinking about entering new markets, think about how this new technology can help you solve a problem that you couldn't solve before that could put you in competition favorably against someone already in the space.
So I just think that it starts with value. The ability to solve problems is much broader than it's ever been. And that means Companies will be springing up to solve customer problems in new ways, more efficiently, more effectively. And if as a CEO, if you are not on top of the problems that you're solving in the most.
Fast and effective way to solve them using this technology. You're going to get beaten by somebody else. Who will
[00:25:35] Ben Kornell: great note to end on. I mean, I feel like you're teaching your Coursera class here to us. So it's great to take notes and also, you know, such a really powerful story in terms of your ability to take the vision and inspiration that Andrew and Daphne had.
Really to the next level and take it globally. So kudos to you. Kudos, the Coursera team, and thanks so much for joining EdTech Insiders. Thank you so much for having me. Great to see you guys.
[00:26:02] Alex Sarlin: Thanks for listening to this episode of EdTech Insiders. If you liked the podcast, remember to rate it and share it with others in the EdTech community. For those who want even more EdTech Insider, subscribe to the free EdTech Insiders newsletter on Substack.
