Big Technology Podcast - LinkedIn's CEO On How AI Changes Your Job — With Ryan Roslansky

Episode Date: September 18, 2024

Ryan Roslansky is the CEO of LinkedIn and host of The Path podcast. He joins Big Technology to discuss how AI will change our jobs and the future of tech products. Tune in to hear Ryan's perspective whether AI replace workers, which tasks are ripe for automation, and how LinkedIn is adapting its products for the AI era. We also discuss the importance of professional content on LinkedIn, the rise of video on the platform, and why podcasts are a key LinkedIn focus area. Hit play for an insightful conversation with the leader of the world's largest professional network. --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. For weekly updates on the show, sign up for the pod newsletter on LinkedIn: https://www.linkedin.com/newsletters/6901970121829801984/ Questions? Feedback? Write to: [e-mail]

The CEO of LinkedIn is here with us to speak about how AI will change our jobs, whether we'll keep them, and where AI belongs in products. That's coming up right after this. Welcome to Big Technology Podcast, a show for cool-headed, nuanced conversation of the tech world and beyond. We're here today with Ryan Roslansky. He's the CEO of LinkedIn. And he's also a fellow podcaster in the LinkedIn Podcast Network, which we're proud to be a part of here at Big Technology.

And you can find his show The Path in your podcast app of choice. Ryan, so great to see you, and welcome to the show. Wow, thanks, Alex, and thanks for that plug there on the path. Appreciate it, man. I didn't expect that. Definitely, look, as a fellow podcaster, I know if I'm appearing on a show, I want to make sure the audience knows right off the bat. And so it's the path.

You can get it in your app of choice. There's some great guests on there, including Saty Nadella and Andy Jesse. By the way, if you have any booking tips for us about how to get those guys on the show, we'd be happy to take them. If you work for Microsoft, it's pretty easy to, you know, get your boss, to you on the podcast. So that's the trick there. You know, I was scrolling through your feet and I looked at it and I was like this jassy interview is a coup given that like Amazon and Microsoft are definitely competitors on cloud. So it's a great interview. We'll get into the podcast network in the second half, which we're proud to be a part of as I mentioned. But first, let's talk a little bit about AI. You mentioned LinkedIn is a Microsoft subsidiary. LinkedIn hasn't been shy about building AI into the product. And also from your position as CEO of LinkedIn, you probably have one of the best views in the business world of how AI is going to change jobs, potentially replace them, change the skills that we have. And I think that's of interest to a lot

of the listeners out there in terms of like, how's our job going to change? Or is it going to change at all? Will we be unemployed? Will we get paid better? We're not going to get into all of that. But I do have some questions for you. And let's start with your job. So there was a story in the New York Times in May 24, so just a few months ago. It says, if AI can do your job. Maybe it also can replace your CEO. So let's just start off with that one. Do you see that happening? I'd love to hear you weigh in on that front. Some days, that would be very nice, actually. I would love that if someone else could do the difficult parts of this job. You know, maybe kind of going back to where you started, very fortunate that LinkedIn is part of Microsoft. I think a lot

of times people don't even realize that. And to a certain extent, that's strategically set up that way by the acquisition that Microsoft did of LinkedIn roughly seven years ago. When Satya bought LinkedIn, the thesis was we can help LinkedIn grow by keeping it as a standalone company inside of the Microsoft umbrella. And to a large extent that thesis has been playing out well when we were acquired seven years ago, we were, you know, less than a billion members and doing roughly $3 billion a year in revenue. Today, we're north of a billion members. There are seven members that are growing, joining LinkedIn every second right now.

And, you know, we're doing north of $16 billion a year in revenue. So it's a nice place for LinkedIn to be inside of this Microsoft ecosystem. But also, you know, because every Friday I attend Satya Ndella staff meeting, which is just a master class on, you know, AI, where AI is going. the future of technology in general. So very fortunate to kind of see what that looks like. And one of the things that I've learned or thought about, you know, navigating LinkedIn where, you know, people are, you know, visiting LinkedIn every day to figure out how to navigate their career and, you know,

what are jobs of the future going to look like, etc., is in a sea of uncertainty to kind of break it down in a way that at least can help people make sense of what's going on. And that framing that I use a lot of is that, you know, everyone's job in the world, your job, Alex, my job, everyone's job. At the end of the day is a set of tasks that need to be done or skills that need to be learned to do those tasks. And if you start to break your job down into, not just the title, but the set of tasks that need to be done on a daily basis, and then you apply the idea that, hey, there are certain tasks where AI can help better automate those tasks. you soon start to realize, you know, what your job can look like in the future. Now, if your job is just a set of tasks that can be automated, you need to start thinking about

a new job. And I think in a lot of cases, you know, there's certain, you know, industries, sometimes, you know, translation or copywriting where it's like, huh, you know, AI is getting pretty good at doing some of those things. So what does that mean for my job moving forward? you know, there's a lot of, you know, jobs where AI is not really going to automate a lot of it, to be honest. And so, you know, those jobs are kind of on the other side of the spectrum. The majority of the jobs, though, are kind of in the middle where a lot of the tasks that you do or a lot of the skills that you have are probably going to change to help you do your job better in the future. And it's not a new thing per se. I mean, you know, one of the great things about LinkedIn is that all the data that we have on LinkedIn allows us to see remarkable insights and data

trends over time. And if you go back to 2015 to now, which is just nine years, the average job on LinkedIn and the skills that are required to do that job, on average, you've changed by 25%. So my job, your job, on average, those skills have changed 25% to do that job. Our guess is that, you know, it'll probably change 70% by 2030, like through AI. But I think that this, you know, change is a good thing. I think that it's going to give a lot of, you know, autonomy to people to do, you know, better work and to do better things. And sometimes people like to talk about, hey, you know, these technology, paradigm shifts, or revolution end up in these really amazing, you know, breakthroughs or innovation or growth. I think that's true.

I think it's also important to realize that when you're in the messy middle of it, it can also be confusing and uncertain and people are going to be, you know, losing jobs and changing jobs frequently. And we hope, or at least I hope, that LinkedIn can act, you know, somewhat as a guide to help people navigate what that change is going to look like by helping you understand what skills you need to learn, what jobs are out there, how potentially, you know, your job may change and what we can do to help, et cetera. So that's where a lot of my focus is today. Right. And, you know, it's interesting because in the headlines, you read the headlines, one company goes out there and they say they're going to automate jobs with AI. And then all of a sudden

it's sort of taken for granted that AI is coming for jobs. And in some cases, the company doesn't actually do it. But in other cases, they do. We had Sebastian Simeonkowski, who's the CEO of Klarna on the show recently. And up until I interviewed him, I was like, there's no way AI is automating any jobs. And he convinced me they've taken AI and used it to automate about 700 customer service jobs within Klarna. But the thing is, you know, that doesn't seem to me to be the case across the board, my guess would be that's that, that is more of the exception and not the rule. And you're the CEO of LinkedIn. You're sitting on top of like some of the most interesting data about how this technology is changing our workforce. So I want to turn it over to you.

Have you seen companies either in, you know, dramatically reducing their workforces or stopping to hire completely? And then you see like a lot of AI and the job titles all of a sudden. Is that something that you've seen within the platform? So the data we see so far, at least that I see real time right now, not seeing the former, not seeing companies reduce their workforce because of AI, definitely seen a ton of job descriptions that now include some form of AI in them. And at least I can speak for myself at LinkedIn. You know, one of the great, you know, we have a large customer service team, for example,

And, you know, with a billion members on LinkedIn, we run a social platform on one hand. Then we run a set of these enterprise businesses. And so customer service at LinkedIn is a pretty diverse set of things, where on one hand, you've got a ton of people on a daily basis, you know, messaging in or emailing in, hey, how do I change my profile photo or how do I change my password or my email address? And then you've got, you know, customers emailing in that are like, hey, we want to ask. add another 1,000 recruiter seats to our, you know, contract. Like, how do we do that?

And what we found, at least at LinkedIn, is we've been able to, you know, through virtual chat assistants, really help to automate a lot of those queries that really are not a good use of a human being's time to answer. So, for example, like, hey, I need to know how to change my password. Like, I don't think a human being needs to walk you through that process when, you know, an AI chat can really help you step by step. Go ahead and do that. So, you know, on the flip side, when someone needs to, you know, add a thousand seats to the recruiter contract or has like a, you know, a billing problem they need to solve, et cetera, where to a large extent success in

solving that problem is not only, you know, good for the problem being solved, but also for the longer term retention of customers to LinkedIn. That's a much better use of a human beans time. So in our case, we have rolled out pretty aggressively chat assistance in customer care. And we've also increased the number of customer service reps at LinkedIn because it turns out that the more that our customer service reps are dealing with those kind of meaty problems, we're seeing better retention of our customers, lower time resolution of those like thicker and more difficult problems and more success. So at least for us, we're seeing, seeing like AI doing a lot of great things and actually a need, you know, for more humans that

are doing some of the things as well. So, you know, my guess is that over time, that's probably a lot of the direction where where a lot of this goes. And I mean, look, I, you know, I probably like you, am sick of hearing like this printing press comparison, but I think that there's something really important about thinking about technological paradigm shifts of the past. And not only what happen with that technology, but what happened with the ecosystems around it. So if you were to go back to the printing press, wow, like here's this new invention. You look at it as an invention itself, it's like, it's pretty cool. Like, you know, the world can change and like you can do something differently now and like,

you know, the older way of doing it is going to change and people are upset. But more importantly, the printing press quickly spawned this huge ecosystem around it. So think about it. You need to have, you know, foundry for movable type. You need to have paper. You have to have ink. And out of that emerges newsletters or newspapers or books,

booksellers that emerge out of that. And ultimately, it's all for the benefit of writers and readers who create new careers on top of it. And that's like, quote unquote, stack, if you think about that stack of things, the tech stack we talked about for the printing press, that translates super directly into a brand new economy. New kinds of jobs, new types of jobs, new types of,

types of companies were created, the Enlightenment, democracy, all these things happen because of this technology and what spawned from it. So in my view, I think that's a lot of what's going to happen over time with AI, which is that you get into this like, you know, messy middle we're in right now and it's tough and confusing. But you think about it. Like you look at what's happening right now around data centers or power or AI councils or responsible AI jobs. All these new things are starting to kind of, you know, pick up around this ecosystem. And my guess is that over time, an entirely new, extraordinary economy is going to be built out of this AI wave.

Okay, Ryan, so outside of Microsoft Office, what personal uses of AI have you found helpful to you? Like, I want to know, like, are you a weekend speak with chat GPT type of person? Are you dumping some of the files that you have into some of these chatbots and saying, hey, I'm trying to lead this company. What am I missing? Or where do you find value from the AI tools as the CEO of LinkedIn? So if you take my job down to a set of tasks, you know, one of the most important tasks that I have is to communicate, to communicate strategy, to communicate, you know, direction of the company, to communicate vision, to communicate one-on-one, etc. And whether I like it or

not, when you're in a job like this, your words carry a lot of weight. So you have to be really thoughtful, you know, what you say, how you say it, when you say it, consistency, et cetera. And I'm going to absolutely cheat on your question because I do find a ton of value. My day, my day lives inside of the Microsoft office ecosystem. So, you know, for example, if I'm writing an email, you know, to my boss, Satya, like, you're, you're darn right. that like I'm gonna push like the co-pilot button just to like hey any advice on this email it's like hey Ryan you know either watch your tone or this sentence doesn't make sense and it's actually super helpful to pull something like that together before sending an email off or another

part of another task in my job is constantly reading you know strategy documents or planning documents etc just a lot going on for you know our company we have 18,000 employees we have five different business lines there's a lot of complexity in it so one of my hacks is inside of you know Microsoft co-pilot is you take a document and it's like hey write me a quick FAQ on this document and it'll take like a large document and like hey Ryan here's like the really important stuff that you have to know about and I found that to be really really valuable so you know at least for me like the tasks of communication or just like insights you know kind of you know condensing information finding the signal from the noise,

I think I've been super, super valuable, at least for how I've been using it on a daily basis. Actually, how about you, Alex? Remember, I'm a podcast host, too, so I can ask you a question back. Like, how do you use that? Definitely. Well, it's interesting that you mentioned

that you're like getting it to check your tone and see if there are examples that you mentioned and also just be like, can you condense this large amount of information down? And you started the question saying the answer, saying communication is the most important. important thing that you do. And I was like, I wonder if Ryan's actually letting the AI write the things that he's communicating. And to me, that's always sort of dangerous because AI will sort of

bring your writing up to maybe the average, maybe a bit above average if you prompt well. And I think you want to be above average if you're the CEO of a company like you are. So it's, it's interesting that like you talk about using AI effectively to hone your communication, to check your communication almost as like this sort of good angel over the shoulder saying hey this is kind of where I would go with this or where I might and that's almost exactly what I use it for as well so I'll dump articles that I'm about to publish in and say what did I miss or what this is one of my favorite examples is I'll take the transcript of podcasts like I'll take the transcript of this podcast afterwards when we're done because you can pull it right out of Riverside and I'll put it in a

in, I'll just say it, I'll put it in Claude. Claude is what I use for this. You know, maybe chat GPT one day. And I'll be like, rate this podcast on a variety of metrics. And it will like look into flow. It will look into difficulty of questions without me like giving the parameters and like go through all the relevant type of questions and be like, all right, this is how are different topics and be like, this is how you did with this.

And it's generally pretty good. And then one other thing I'll do with it is I'll take like the, you know, other interviews that I find interesting, and if I want to, like, write about it, I'll put it into an AI chatbot and be like, I think this was the most interesting part. Why don't you call out some quotes? Right? So I'll never have it do the writing, but it will help me sift through the information and sort of modulate what I'm doing in a, like, very effective way. I love that. By the way, I think on the doing the writing for you, I both agree that is that is dangerous. And quite frankly, the technology is not quite there yet.

in my view, for the most part, no matter what you ask, you know, be it co-pilot or Claude or chat GPT to do, to a large extent it's going to, even with some intense like prompting, it's going to give like a pretty canned answer that you think it would be pretty much a lot of the same tone, I don't know, have a better personality that it would almost kind of pull back for anyone. You know, I think technologically over time, what's going to be fascinating, especially, you know, as we move into, you know, any of this agentic world is that personality layer is going to be a critical component of this, which is if I was ever to let something respond on my behalf, it would need to know so much about me

and have the context and the background and the tone and the context of the people that I'm communicating with, my relationship with them, to be able to do that. So it's not there yet. I think over time, that'll be a really important part of the stack, though, to figure out. It's something we spend a lot of time on because we're, you know, we build AI tools right now for recruiters, a large part of a recruiter's job, and their secret sauce, quite frankly, is when they see a candidate they want to reach out to, their own personalized way to reach out to that candidate. You know, some recruiters, for example, their secret sauce, like you're sending a, you're sending an important, recruiting email to a, you know, amazing, like Gen Z software engineer, like, you include a lot of emojis. Like, that's the unlock. Like, that's how you get people's attention. So, you know, helping recruit, like, helping the AI over time understand, like, what would this specific recruiter

do in this instance to help communicate with this specific candidate? Like, that's a real unlock. And I do think over time, you know, the more we can help people be more effective in those parts of their jobs and own that personality with them, it will unlock and unleash a lot of people's to do more of the human parts of their job. So on the recruiting thing, for example, you know, a recruiter's job is to recruit. You talk to great recruiters. You know what they love to do.

They love that stage in the process where they pick up the phone and they have a conversation, which is a blend of EQ learning more about this person, potentially like understanding that candidate's tone and what they're saying as to whether or not they'd be a good fit

with the group of people that they're going to be working with. And then potentially a lot of selling as well, because this is someone that's potentially in high demand. You don't want to help them to understand that this is the company for them to come and work for. And that unique blend of like EQ understanding, selling is what recruiters love to do. What recruiters don't love to do is to sit there and sift through, you know, profile after profile thousands of times, like find the signal from the noise, you know, write personalized in-mails to them to kind of get their attention. And so, you know, over time, we're trying to take a lot of that back into the product, into the technology that we're building that gives then those recruiters the ability to do the part

of the job that they really love. And on the writing front, one more question for you. And maybe this is something that you've already considered building into the product. But the models are starting to give us larger and larger context windows. I think the Gemini one is two million tokens or some crazy number. And, you know, maybe there is a point where, like, you can. and take all of your writing, put it in the context window, and say, write an email or an article the way that I do.

Is that something that you're thinking about? Let's say for the recruiter that loves the emojis. Like, can we get to a point where you end up having LinkedIn, say, every member is going to have a customized AI trained on their communication style that will then help them be more efficient and communicating in their style to more people? So, um, even, yes and even beyond that. So by the way, that's a very thoughtful approach you just took there, which is that in your head, you're, you're actually understanding how many tokens exist so that you can code into the prompt the right way to ask the question. I like that. My hope is that over time,

though, um, it changes a little bit. So LinkedIn is historically, you know, for the past 20 years we've been around, been the place where you maintain your professional identity online. So when I want to look someone up, when I want to look up Alex, like I go to LinkedIn and I see you know, who you are, who you know, what you know, what you've done, etc. But you can think about over time, LinkedIn also potentially being the place where a lot of that deeper information about you can be stored. So, you know, it's what I like to call. I don't have a better word for it yet, but your personality. You know, like, how does Alex communicate?

What does Alex tone in certain situations? Who are Alex's close contacts? Who does Alex have a closer relationship or a more distant relationship with? You know, does Alex like to respond to things quickly or take time to respond to them? I mean, it's basically like your personality. And then if you can have that, you know, be it when you're writing an in-mail on, LinkedIn or potentially when you're using like any other AI agents on the internet, the ability to, you know, for that tool to hit that personality to grab that context and help it be smart

in that response on your behalf. I think it's a really interesting thing that we've just started scratching the surface on. We need to in the recruiting and the sales use cases because they're core components of who we are and what we do as a company. So, you know, for a recruiter, for example, It's not that every time a recruiter sends an in-mail to a candidate, they're going to have to, you know, input all their stuff and learn it on the fly. But a lot of these recruiters, we've been watching what they're doing for a decade, you know, how they respond, who they respond to, who they don't respond to, et cetera. And that, you know, quote-unquote personality will be built in to how they reply to candidates on LinkedIn,

and we keep building that up. So, I mean, uncharted territory, exciting times. But again, for me, it all goes back to, you know, a recruiter's job is to recruit, a salesperson's job is to sell, like all these other things that you have to do to get to that point. Like, how can we help you be more efficient and effective in doing it? Even on the flip side, by the way. So not that you asked this question, but let me tell you about some other LinkedIn products. You know, if you're a job seeker right now on LinkedIn, which, you know, there's many that come to LinkedIn every day looking for a job and searching jobs. and you're staring at a job in front of you,

and you're like, hey, is this job a good fit for me? You know, we've kind of created these AI tools in that flow, which, you know, you push the button and it's like, hey, Ryan, like, turns out this job isn't great for you because it requires these four skills that you don't have, but instead come take a look at this job over here. Or, hey, Ryan, this job is perfect for you.

I think you should apply to it. Great, well, what don't you do now? Well, I need to write a cover letter. Cool, can you help me write a cover letter that, like, showcases the best parts of me and the best part of this job to give me like a template to start from. So, you know, we keep trying to build these like, you know, flows in the process to just help, you know, minimize the friction in any of these processes to help someone

get to their end goal. Okay. And now I have a question for you about that because I hear efficiency and, man, I'm pumped, but I'm also a little bit nervous because the other side of efficiency for the sender is volume for the algorithm, for the receiver. and you can get into a world where if it's so easy, like, like, think about the job process, part of this is proof of work. Like, you write the cover letter A to introduce yourself, but also to show that you're serious

enough that you've written this letter that explains why you're the right candidate. And that's why they should take a look at the resume. And if they make people write cover letters, then they'll only get the more serious candidates. Now you can have an LLM just write us in a cover letter for you and it's just as good as almost everybody else is out there. So how do you get around this potential threat of just having a world of AI slop, for lack of a better term, you know, both in the feeds on LinkedIn and on the inboxes, where people are trying to find the information and that proof of work is actually important, right? Like if you have to spend time writing a LinkedIn post, you know, it better be good. Whereas like if you can like prompt it, maybe it won't be.

So how do you think about that? So a lot of ways. And I mean, it's a great question. Look, just to be, like, you know, transparent and, like, up front about how real this issue is. I think it was a couple weeks ago, you know, someone wrote an awesome, you know, bot on LinkedIn to, like, go and apply for, like, thousands of jobs, you know, as a bot, like, doing this. And I think that, you know, the bot got actually a couple, like, interview requests back. And, you know, it was just, it was really important in eye-opening for us to understand, hey, this is something we have to be very thoughtful about. you know, this approach and make sure we have the safeguards in place.

So your example is a real thing in the world. So there's a couple of ways that we approach it. So number one, we've been investing really heavily on LinkedIn in what we call verified identity. And historically, you know, your LinkedIn, like your LinkedIn profile, we didn't really have too much of a fake profile problem on LinkedIn because the barrier to create a LinkedIn profile is high. You know, you have to, you know, you have to create a resume along with your profile, basically. So, you know, a LinkedIn profile alone was just a pretty

good sign of authenticity. But over time, we've even tried to push that a step further, given that, you know, through automation, you could theoretically find ways to do this stuff. Not to say we don't have a huge, you know, security team on the other side of this, but we introduced what's called verified identity, which is basically either through, you know, your work email address if you are, you know, like active directory, if you're at a, you know, a company using any of the office products, or through your driver's license, or through your passport, you can actually verify who you are. When you verify who you are, like a little check goes on to your profile, which is like, hey, this is really Alex. You know, we verified that this is actually Alice.

So that's a great start for our product internally because, you know, when you're applying for jobs, when you are creating feed posts, when you are making connections, you know, real people, real verified people, like, are less likely to, you know, create havoc inside of the system and it gives us much more flexibility in what those accounts have access to do versus non-verified accounts. you know, there are more restrictions on what they're able to do across the product. So, you know, a real verified account that's, you know, applying to a lot of jobs is most likely a real thing. A non-verified account that was just created, you know, five minutes ago applying to a thousand jobs, you know, we'll stop that earlier on in the process. So one starts with just the identity of understanding who this person is in general and then what they're able to do on the platform. Number two, you know, is to be very thoughtful in the middle of the matching processes that we have on LinkedIn about how we're connecting things. And our whole job is to connect things across LinkedIn, to correct a recruiter to a job seeker or someone sharing their podcast on LinkedIn to someone who wants to listen to the podcast or a potential buyer with a marketer, et cetera. And our ability inside of that algorithm to be thoughtful about, hey, you know, here's someone with, you know, on their profile without the skills that are applying to a ton of jobs, you know, we, you know, those will end up much lower down the queue for a recruiter because a recruiter is like, hey, please send me like the highest quality thing.

So, you know, what the recruiter ends up seeing, we want to make sure that those are the highest quality, highest matching things, not saying we won't show everything. way that we present that to them, which makes their job more effective and efficient to show them the things that matter most. There's a lot of things that we do where there are, you know, different types of, you know, for lack of better term, like watermarks that come across in a lot of new, you know, AI tools where videos created, et cetera, we can actually say, hey, this was an AI created thing. And we're, you know, like other platforms, we're testing a lot of that as well. But it's a problem that we have to ensure that we can address, I think it's less of a problem for LinkedIn because of the authenticity that exists in the profile and the verified identity is kind of one of our

main ways to solve it. But through matching is the real other way that we have to just continue to get more sophisticated on it in general. Let's say we push much further into this generative AI wave. I remember at the beginning, Benedict Evans, a tech analyst, he's been on the show, talked about how the way that you have to think about software being developed with AI or AI software is not like how does this end up being added to Excel, but how could that replace Excel, right? For instance, like, do you want to be working in spreadsheets or do you want to just upload all your data and just sort of query it with natural language? Now, we have not gotten anywhere close to that yet. And it's only been, what, two years since chat GPT or coming

up on the two-year anniversary. But I'm curious if you think about that from a perspective of the CEO of LinkedIn, right? Is there a place where, for instance, instead of like combing through profiles, you are a natural language being like, can I find the right person for this job or what job suits me, given these parameters? Is that something that that you think about? Is there like a revolutionary interface change that you might have to make to fend off potential competition who could get there first. So probably, so yeah, I mean, I think it was, I don't know, maybe it was like 10 years or so ago. I had the opportunity to attend a talk with Clay Christensen, who, among other things, wrote The Innovators Dilemma,

you know, where he studied, you know, how was it that these companies at the top of their game, like end up falling off a cliff, you know, Kodak or Blockbuster, et cetera. and I had the opportunity to ask him a question at the end because it was always kind of plaguing me because I'd read that book many times and I was like, hey, like you've studied all these companies when they were being disrupted, did they know they were being disrupted?

And his answer was fascinating to me. He was like, they all knew it. But they were all so stuck in their comfortable ways of doing things that they'd always done that they weren't able to break out of it. So I think a lot about that. I think a lot about your question. So my hope is, yes, that the way that you interact today with LinkedIn will not be the

way that you interact with LinkedIn, you know, three to five years from now, that we will be on the bleeding edge of hopefully disrupting ourselves and the existing way that the product works, leveraging the technology that will exist to create better ways of helping people get their jobs to be done completed in the product. And I think probably a ton of people who are in great positions at companies that have been longstanding are hopefully thinking the same way right now because AI will allow completely new ways to interact. And if you're not in the bleeding edge of what that should look like inside of your own product, I think that you're at risk of being disrupted. So it's probably the most important thing that I spend the majority of my time

thinking through. And we're, you know, I think, I think we're already, you know, the part, one of the best parts of being part of Microsoft is, look, two years ago when, you know, chat GPT came out. Like that, that was the, like, time when we got access to a lot of this, you know, well ahead of a lot of other companies. And no exaggeration, we have probably run at least 250 different, like, AI feature experiments through our products over the last two years. a ton of them have failed, but some of them are really catching on and helping people be more productive on what they're trying to do on LinkedIn. So just that mentality of embracing it, pushing the boundary, looking forward, testing a bunch of stuff. That's kind of where we are

in our mindset right now. And, you know, my hope is that many more people will be using LinkedIn to, you know, navigate their career and find a job three years from now. And it probably looks nothing like it does today. Right. Okay, Ryan, I got two and a half minutes left and two questions for you. So let's see if we can fit them in. First question, I'm just going to ask them both and you can tackle them as you see fit. Podcasts are now super important, I think, on LinkedIn. It's one of the only places where you can listen to podcasts, watch podcasts, and then also like have an interaction with the podcast's hosts and other listeners. And we do that very seriously with big technology as part of LinkedIn podcast network.

So I'm curious if you could, in your own words, talk about the importance of podcasts to LinkedIn. And then another rising format is video. And there's a new video tab on LinkedIn. So I'm curious what makes a good LinkedIn video as opposed to, let's say, a TikTok video. How are they different? So maybe for both of these, let me start.

I mean, like the the thesis that we have around content on LinkedIn may end up taking the form in the, like, you know, the format of the consumption patterns of other networks, but our approach starts from a completely different place. So, again, remember, you know, we exist as a company to help create economic opportunity for every member of the global workforce. that's our vision. Like what's a really important part of being a successful and productive professional? Staying informed. So when we think about our products around creating content, sharing content, our feed, we start from the premise of how do we help professionals stay informed on a daily basis? So what's going on in their industry, what's going on, you know, around their function, what's going on in their network. That's like the framing that we take on all of this. Turns out that the, you know, a lot of the way, a lot of the best information

that helps someone be successful in their job is in a podcast format, which is why, you know, we're so grateful to work with folks like you and a lot of others to bring this insightful knowledge. I mean, when you and I sit down for a talk like this, like, you know, it's different than like, you know, 140 characters. It's like, this is a in-depth conversation. It's It's professional in nature. So we really want to invest in helping people both distribute that on LinkedIn, but also have the healthy, vibrant, productive conversation around it through the platform as well. So that's why we were making that investment in podcasts.

It's a meeting that makes sense. On video, I will say we're like, rightfully so a little bit late to this game here. And let me tell you what I mean by that, which is we have not invested historically. in a lot of video on LinkedIn. Short-form video is obviously one of the most, you know, you know, engaging and, you know, watched formats or mediums on the Internet. My view is that, you know, up until maybe a year and a half,

two years ago, the majority of short-form content, it didn't fit inside of that ethos of, you know, helping the professional become more productive and successful. You know, it was more entertainment, which is fine, which is all great, but it wasn't really fitting with LinkedIn. So we didn't make a large investment in it. Then I'll say, you know, maybe a year and a half, two years ago, all of a sudden, a lot of these amazing professional creators start popping up on TikTok and on Instagram,

doing awesome career content, technology news, all these great things. And it's like, oh, we have to help those folks tell their story on LinkedIn as well. So we made a huge investment right now in video. And it's great. I mean, one of the big movements we've seen is, you know, a lot of CEOs, CFOs, like, you know, an earnings call happens. and they pick up their phone and turn to LinkedIn to actually give the inside scoop about what just happened. Like Daniel, Daniel Eck from Spotify just kills it on LinkedIn.

Like, he loves to just like, you know, use it as the medium in a productive way to tell the story about what's happening at their company. So we're seeing a lot of great progress happening there. It's just early days. You know, video on LinkedIn, I think it's, you know, 1.5X, the engagement of any other medium right now. So we're seeing good momentum there. Advertisers obviously want to be around video.

So, but for us, the key is keeping it, you know, professional, keeping it trustworthy, you know, holding a high bar on what happens on LinkedIn. So that's the thing that we're navigating now, but seeing a lot of good results around it. So you're saying more podcast videos, more informative stuff, and I should maybe shelve my plan to turn my LinkedIn video feed into my NBA trick shot feed. Yeah, I think there are better places for that, Alex. But a lot of the other stuff you do is perfect for LinkedIn. All right. awesome so shoot over the house maybe i put that on youtube everything else can you do that that'd be awesome if it took me if i basically retired from podcasting and spent the whole day with the basketball

maybe once in in a year or so Ryan so great to speak with you so great to see you i encourage everybody to subscribe to the path which you can find in your podcast app of choice ryan rislanski thanks much for being here thanks alex all right everybody thanks for listening and we'll see you next time on big technology podcast