AI transcript
0:00:06 Today on the podcast, we’re joined by A16Z partners, Olivia Moore and Justine Moore to
0:00:11 get the latest consumer AI 100, their biannual ranking of the most used AI native products
0:00:13 across web and mobile.
0:00:18 They discuss how real users are adopting, what’s fading, and where the next wave of opportunities
0:00:19 might be.
0:00:20 Let’s get into it.
0:00:24 Hi, I’m Justine.
0:00:25 And I’m Olivia.
0:00:27 And welcome back to the A16Z podcast.
0:00:32 Today, we’re going to be discussing the consumer AI top 100 list.
0:00:37 So, Olivia, let’s start because you are compiling the list and you’ve been doing this for a
0:00:37 while.
0:00:40 What is this list and kind of what’s the purpose of it?
0:00:42 So, this is our fifth time doing this list.
0:00:43 We do it every six months.
0:00:48 We started at basically the dawn of the consumer gen AI era.
0:00:52 And the purpose is just to get a sense of what real consumers are actually using in AI.
0:00:57 As a sample set, we take every website and every mobile app in the entire world.
0:01:00 And we sort them in descending order of usage.
0:01:02 So, for websites, this is monthly visits globally.
0:01:05 For mobile apps, this is monthly active users.
0:01:08 We use similar web and sensor towers, these two data sources.
0:01:13 And then we grab the top 50 from each of those sources that are AI native companies.
0:01:17 So, you’ll notice that this captures usage, not revenue.
0:01:19 So, it’s not paid usage only.
0:01:24 It’s all usage, even people who are using the products for free, which to me gives an even
0:01:29 better and, I think, kind of more real sense of what is capturing consumer imagination in AI.
0:01:30 Totally, yeah.
0:01:38 I feel like a common question we often get as folks who are consumer investors in AI is, what are people doing on AI?
0:01:40 Yes, well, what should I be doing?
0:01:41 That, too, yeah.
0:01:46 And so, I feel like these lists are a really helpful way for folks to get a sense of what are some of the use cases,
0:01:51 what are some of the properties that are getting really big, getting a lot of users that you might not know about.
0:01:55 And for a lot of people, sort of an inspiration list of what they want to try out.
0:02:01 Let’s talk about the new companies on the list, because that’s always exciting of, like, who cracks into the top 50 for web
0:02:04 and the top 50 for mobile who weren’t in the list before.
0:02:04 Yeah.
0:02:06 How would you describe the new companies?
0:02:07 Were there any major changes?
0:02:08 Yeah.
0:02:11 The web list, I think, is the best way to track changes over time.
0:02:18 The mobile list is a little bit less stable, just because the app stores are constantly updating their policies on what’s allowed.
0:02:24 For our first couple mobile lists, it was just a wave of companies that were direct copycats of ChatGPT.
0:02:25 I remember that.
0:02:30 Yeah, and all the companies were, like, ChatGTP or Chat and Ask AI.
0:02:31 ChatGBT was a big one.
0:02:32 Exactly.
0:02:32 Yes.
0:02:34 And so those were dominating the mobile list.
0:02:39 So this time, we had a lot of new companies on mobile, as iOS ecosystem has cracked down on that.
0:02:42 But on the web list, we still did have 11 new names.
0:02:50 Sounds like a lot out of 50, but it’s actually a big reduction from, I think it was 17 new names six months ago.
0:02:50 Wow.
0:02:55 Which, to me, reflects the fact that the ecosystem is starting to stabilize a little bit more.
0:03:03 There were still a couple of really exciting trends that popped out on this list that I would expect might continue and yield more new names.
0:03:08 Vibe Coding was one of them, which I think kind of burst into the forefront at the end of last year.
0:03:15 So we saw it a little bit on our prior list in March, but it really kind of came into the forefront now.
0:03:19 So we have Bolt on our Brink list, just below the Top 50 Cutoff.
0:03:19 Awesome.
0:03:23 And then we have both Lovable and Replit on the web list.
0:03:33 In the past, a lot of the names on the list have been kind of in one of two categories, which is like general chat and companionship or creative tools, which I love.
0:03:35 I spent a bunch of time in both of those categories.
0:03:44 But it sounds like we’re starting to see things like vibe coding that are sort of outside of those two, what were really the killer use cases of consumer AI for a long time.
0:03:47 We definitely are more in productivity as well, which we’ll talk about.
0:03:50 I will say companionship continues to just dominate.
0:03:52 We actually did have three new companionship names.
0:03:59 So Juicy Chat, Joy, and Our Dream all made the list, alongside a bunch of others that have made the list before.
0:04:08 So Character was the biggest name, Janitor, Spicy Chat, Polybuzz, Crush On, ADOT, and Candy AI were all on this list and in the past.
0:04:15 So that’s a pretty notable section of the list that I think is dominated by companionship names, which is pretty interesting.
0:04:15 For sure.
0:04:19 And there’s also a lot of big companies that have products on the list, folks like Google.
0:04:23 Maybe you can talk a little bit about that because I think that’s been a surprise.
0:04:25 Yeah, Google had a big six months.
0:04:30 And I would say especially their models and even their consumer-facing products had a really big six months.
0:04:38 The way they structured their domains in the past made it hard for us to include Google products on the list since we needed to be able to independently rank their traffic.
0:04:44 So now we finally were able to for the first time, and four unique Google properties made the web list.
0:04:46 So Gemini was number two.
0:04:47 It was right behind ChatGPT.
0:04:54 It has just about 10% of ChatGPT’s traffic on web, but it’s much closer on mobile.
0:04:58 It’s like half of ChatGPT’s traffic on the mobile app, which is interesting.
0:05:01 It’s mostly Android users, which I think you would expect.
0:05:05 The other big debut for Google was a little more surprising to me.
0:05:10 It’s actually AI Studio, which is Google’s developer-facing sandbox.
0:05:14 So that’s where engineers go when they want to build things and test out Google models.
0:05:17 So that hit in the top 10 as well.
0:05:21 And then right below the top 10 was Notebook LM at number 13.
0:05:33 And I take your wow as a little bit of a surprise, which was a surprise to me, too, and I think a bit of a narrative violation that they went viral almost a year ago in September of 2024.
0:05:45 But they’ve actually kept up their traffic every month of flat or increasing traffic, with the exception of this last month of summer, when I think a lot of the academic usage caused it to decline, but just barely.
0:05:51 And then one of your favorites also made the list, which was Google Labs, down at number 39.
0:05:58 This is kind of the consumer-facing sandbox for Google models, whereas AI Studio is the developer-facing sandbox.
0:06:06 Google Labs includes VO3, the amazing new video model that you yourself have probably driven a big portion of the usage for.
0:06:07 I’ve spent a lot of money on VO3.
0:06:08 Yeah, exactly.
0:06:10 And driven many visits, for sure.
0:06:16 And actually, Google Labs includes a bunch of other products, like Doppel, which is their kind of outfit try-on product.
0:06:16 Yes.
0:06:18 It includes Portrait, which is coaching.
0:06:19 WISC, right?
0:06:20 WISC.
0:06:23 The image generation kind of sandbox, which is very cool and fun to play with.
0:06:24 Exactly.
0:06:27 Project Mariner, which is their agentic kind of browser sandbox.
0:06:38 But my hunch is it’s largely VO3, because traffic to that, to the Google Labs, spiked 15% in the month that VO3 was released, which is really exciting.
0:06:41 Let’s talk about the Chinese AI companies.
0:06:48 So, both new startups coming out of China, also big Chinese companies releasing models or consumer-facing properties.
0:06:52 How are these ranking on the list, and what do you think has driven their growth?
0:06:57 I mean, you could argue that Chinese companies show up in two or even three pretty interesting ways on the list.
0:07:03 I would say the first one are companies or AI products that are built for China and used in China.
0:07:05 And you might say, why?
0:07:21 And it’s because a lot of non-Chinese AI products, like ChatGBT and Claude, are banned in China because they have to follow specific regulations and policies and data capture rules that they’re not wanting to or able to do if they’re going to operate in China.
0:07:25 So, China doesn’t have a lot of those products that we have, but they have their own.
0:07:32 So, a couple companies that made the list are Quark, which is Alibaba’s AI assistant on both web and mobile.
0:07:37 Daobao, which is ByteDance’s AI assistant, also on both web and mobile.
0:07:41 And then Kimi, which is another general AI assistant from Moonshot AI.
0:07:46 Each of those ranks, actually, all of them in the top 20 on web.
0:07:53 And the majority usage in China, which I think reflects the fact that, like, China is the biggest country in the world by population.
0:07:57 So, even if they’re only used one place, they’re getting a lot of usage.
0:08:02 And they don’t have as much competition from the American general chat assistants that can’t be in the country.
0:08:04 Yes, like the chat GBTs of the world.
0:08:12 The second category of Chinese companies we’re seeing are startups that are developed in or around China, but are built for the rest of the world.
0:08:15 And you can’t actually even use them in China in many cases.
0:08:20 So, these are products like DeepSeek or the video models like Hilo and Kling.
0:08:20 Yes.
0:08:22 Or products like SeaArt for images.
0:08:22 Yeah.
0:08:28 I would say the concentration of these is especially strong in image and video, which is a space that you know well.
0:08:38 Yeah, I think image and video, we’ve seen a lot of great video models from China, particularly when it comes to animating from a single frame from an image.
0:08:46 ByteDance has also been doing a lot more around things like SeaDance, which is a really great video model they released that actually outscores VO3 on some of the arenas.
0:08:54 One of the really interesting things that I know we can’t disentangle in this data, but I think a lot of Chinese companies have taken the strategy in the U.S.
0:08:58 of distributing their models through U.S. properties.
0:09:07 So, there’s companies like CREA or Hedra that host various models and have subscriptions where you can access a bunch of the Chinese models at once.
0:09:16 Whether it’s the closed ones like Kling or Minimax or some of the open source ones like Wan or Quen, which a lot of people are using and really liking.
0:09:32 Some of them will also have their own consumer-facing properties, others will distribute through either the application layer, or honestly through folks like Fall and Replicate, more of the developer-facing platforms, where you can do one-off runs or you can have an API to use them in your application.
0:09:38 That is probably yet another way that Chinese companies are showing up in the list, in a way, as you said, that’s not measurable right now.
0:09:38 Right.
0:09:46 But the last trend that we were seeing with Chinese companies was products that are developed in China and used both in China and abroad.
0:09:47 So, Manus is a great example.
0:09:51 They just announced a 90 million annualized run rate.
0:09:55 And if you look at their traffic, it’s number one Brazil, number two U.S., and number three China.
0:09:56 Brazil surprises me.
0:09:58 Yes, a lot of AI traffic comes from Brazil.
0:10:00 More free traffic than paid traffic.
0:10:01 I was going to say, yes.
0:10:02 But a lot of traffic.
0:10:07 So, we’re seeing both kind of like this domestic AI ecosystem in China start to mature.
0:10:07 Yeah.
0:10:10 I think for the very first time on this version of the list.
0:10:10 Right.
0:10:16 And then we’re seeing the same thing we’ve seen on other versions of the list, which is Chinese companies exporting their AI products abroad.
0:10:29 And then to talk about another big trend, which you touched on earlier, vibe coding, we’re probably all seeing the tweets from various vibe coding companies that are like, we went zero to 100 million or even more in ARR in a really short period of time.
0:10:35 They have millions of users, kind of faster growth than I think we’ve seen in many other categories in a very long time.
0:10:39 I’m curious, how did you see that kind of reflected on the list?
0:10:40 And how did that change since the last edition?
0:10:49 Yeah. So, six months ago, it was just Bolt on the list. Now, Bolt actually is on the brink list. And Lovable and Replit both made it onto the main list.
0:10:55 To me, I was particularly interested to look at not just traffic for these, but also revenue and retention.
0:11:06 So, Lovable recently announced $100 million in ARR. But it’s always easy to say, especially for consumer properties, like, yeah, a lot of people are maybe signing up for a trial, but they’re canceling.
0:11:08 They’re not going to stay on. Retention is low.
0:11:15 We actually also, for the vibe coding products, looked at revenue retention across another data provider, Consumer Edge.
0:11:24 So, that looks at a cohort of everyone who signs up in month zero, how much are they paying and what percent are still paying in month one, month two, month three.
0:11:37 And we put some of this in the report, but what we found for many of the leading vibe coding platforms is they actually see 100% or above revenue retention in the first three months and then maybe flatten out a bit below 100%.
0:11:41 Which, as a point of comparison, is very strong for what we see.
0:11:51 I mean, it’s very rare to see any sort of, especially consumer, prosumer, might suggest that there’s some enterprise usage happening there with prototyping and stuff within companies.
0:12:04 Enterprise usage or even just solo vibe coders, people building projects who do get a low-cost plan to try it out and then find themselves actually publishing and using something and buying more credits and upgrading to the next plan, which is exciting.
0:12:13 It’s interesting, though, on that point, for both Lovable and Replit, we can independently see traffic to the sites where you vibe code things.
0:12:15 So, that’s where you or I would go.
0:12:18 Oh, because they’re hosted on Lovable.app.
0:12:27 Yeah, so you can see traffic for everything people are making with Lovable and Replit, and then separately, traffic to Lovable and Replit, which are the people making things.
0:12:34 And in both cases, the people making things traffic is much higher than the traffic to the things that they are making.
0:12:34 Yes.
0:12:36 Which suggests one of two things.
0:12:42 One, it could be that people who are making serious, high-traffic websites are buying domains for them.
0:12:48 A custom domain, so they no longer pop up under the Lovable or the Replit domain in this data.
0:12:49 So, their traffic would not get included.
0:12:50 Yeah.
0:12:57 Or it could be the case that people are building almost personal software, software for themselves with these vibe coding platforms.
0:12:57 Yeah.
0:13:04 So, they might publish them and not get a lot of hits, but they’re extremely valuable to the individual user or maybe the user’s family and friends.
0:13:08 And I’m curious, have we seen anything yet in vibe coding coming to mobile?
0:13:10 Like, are there any?
0:13:10 Not yet.
0:13:10 Interesting.
0:13:16 There’s a couple companies, startups that we’ve seen, but none of them ranked high enough to get a spot on this list this time.
0:13:19 Yeah, it will be super interesting to see the next edition of the list.
0:13:19 Maybe for the next edition, for sure.
0:13:21 Like, if any of those start popping up in the top 50.
0:13:26 It’s hard to displace the companionship and the AI girlfriend ones, for sure.
0:13:26 Yes.
0:13:28 But maybe a vibe coding one can do it.
0:13:28 Yes.
0:13:32 No, it’s actually a good point because we did, on the point of displacement, for the first time,
0:13:35 we ranked what I’m calling our AI all-stars.
0:13:36 Cool.
0:13:38 So, this is across five lists.
0:13:41 What are the companies that have made the list every single time?
0:13:42 Amazing.
0:13:44 Which is hard to do because this dates back two years now.
0:13:47 So, there’s 14 of these companies.
0:13:56 So, we have ChatGPT, not a surprise, Perplexity, and Poe all made the list in what I call kind of general LLM assistance.
0:14:00 Then we have Character AI in Companionship.
0:14:00 Yeah.
0:14:01 They’ve made it on both web and mobile.
0:14:09 We’ve got Mid Journey, Photo Room, Leonardo Cutout Pro, Veed, and Eleven Labs in Creative Tools.
0:14:16 We have Quillbot and Gamma in Productivity, and then we have Hugging Face and Civit AI in Model Hosting.
0:14:19 And so, those have made the web list for every single one?
0:14:21 Web list for every single, got it.
0:14:23 Every, all five of the versions we’ve done of this now.
0:14:23 Amazing.
0:14:29 It was funny looking back at the very first list because I think we had this question of,
0:14:36 is it only going to be companies that invest tens of millions of dollars into proprietary models that are able to hold consumer attention?
0:14:37 Yeah.
0:14:45 But now, when we look at these 11 all-stars, more than half of them are actually hosting or using other people’s models or are model aggregators.
0:14:46 Right.
0:14:54 And so, I think that speaks to the fact that in consumer AI, the UI and the product experience matters just as much as the model,
0:14:59 especially when so many amazing models are now API-available or open source.
0:15:05 If you think of some of those properties, too, some of them have built really deep and interesting workflows around creating content,
0:15:07 even if they don’t have their own model.
0:15:07 Yeah.
0:15:13 Some of them are also starting to see what I would say are sort of the first kind of non-data network effects in AI,
0:15:23 especially things like Hugging Face and Civic AI, where, you know, you have these communities where people are hosting tons of models or LORAs or data sets.
0:15:24 They’re commenting on them.
0:15:25 They’re ranking them.
0:15:28 They’re spitting up many apps that you can only access on that website.
0:15:28 Yeah.
0:15:36 So, it’s pretty cool to see both of those kind of make the list over and over again and show that you can maybe have network effects in AI.
0:15:36 Yeah.
0:15:42 I think you could argue, too, 11 Labs is the same, where people can publish their voices on 11 for other people to use.
0:15:50 The voice libraries, I hear that all the time from people, that one of the reasons they love using 11 is there’s thousands and thousands of voices you can choose from,
0:15:53 and that’s because so many folks have uploaded voices to the voice library.
0:15:57 You could even argue the same is true for a ChatGPT or MidJourney.
0:15:58 Yep.
0:16:05 Where the more user data they get, the better models they can train, which then makes the product better and attracts more users, and it’s a whole virtuous cycle.
0:16:05 Yeah.
0:16:13 I think that is the natural assumed network effect for AI, which is kind of more users, more data, more feedback, better models.
0:16:23 But I know a lot of folks are wondering, like, where are the network effects beyond that, which is why I was particularly interested in, like, the hugging faces, civic AIs of the world, things like the 11 voice library.
0:16:30 Yeah. We’re even starting to see, in some cases, Gamma is a good example of this on the list. 11 is another good example. Same with PhotoRoom.
0:16:43 These consumer AI properties are almost graduating to enterprise usage with things like team plans, templating, you know, design libraries, and then it becomes something that can spread organically through a team and that a whole organization can benefit from.
0:16:52 And the more you invest into building out, say, your templated slide deck on Gamma, the harder it is to kind of churn and move over to another platform, so.
0:17:04 Yeah, I think that’s one thing that a lot of people didn’t expect with a lot of these, especially creative tools or productivity tools that I try to tell founders all the time, is, like, there’s so many AI enthusiasts now.
0:17:07 Some are tourists, but some have real use cases.
0:17:19 And often with companies like 11, we will see one individual signs up, they try it out, they see if they like it or not, and then that individual actually becomes, like, their own self-serve enterprise sale.
0:17:30 Like, they bring it into their company, they make the case for it, and then it’s so easy for, and then they go to the business and they’re like, hey, we actually have 10 or 15 or 20 users on individual plans.
0:17:47 Like, we should have some sort of enterprise-level contract here, which makes it a lot easier for these AI companies to grow than the traditional top-down sales that enterprise software had to do, where you had to go in and get approval from 10 different people and then convince the employees to use the product.
0:17:55 versus this bottoms-up adoption that we’re seeing with a lot of these freemium AI products that start in consumer feels very cool and unique.
0:18:05 Yeah, and that in turn supports more consumer growth because then someone on a team will adopt it because their other team member had it, and then they’ll bring it home and use it for a project and spread to their friends and their kids.
0:18:12 And, yeah, I expect we’ll continue to see more prosumer enterprise representation on this consumer AI list.
0:18:15 So this, as you’ve mentioned, is the fifth edition of the list.
0:18:25 I’m curious, reflecting back on all of the past editions, what are your biggest takeaways, and do you have any hot takes or predictions for what we’re going to see in the next few lists?
0:18:38 Yeah, I would say looking at the list now and then looking back, I really can appreciate now that the first list or two was total chaos in the sense of half the list was new every time, if not more.
0:18:40 And the traffic was fluctuating so wildly.
0:18:41 Yes.
0:18:47 And there’s often, you know, like a two-week to one-month delay between when the data happens and when we get it through the data sources.
0:18:54 And so founders would be contacting us angry, like, hey, I’m actually ahead of this other property now.
0:19:02 I should be number two instead of number five, just because the data sources had a little bit of a lag and things were so volatile back then.
0:19:03 Things were changing so rapidly.
0:19:13 I would say that, as you said, companionship and general LLM assistance, like ChatGPT and then creative tools were kind of the three categories that were working two years ago.
0:19:20 And anything else that popped up on the list in many cases was pretty random and would spike one month and be gone the next month.
0:19:24 I would say we’ve had a lot of stabilization since then.
0:19:29 By the third edition of the list, we started seeing things that weren’t just image and text.
0:19:33 We started seeing video, we started seeing music, which was really exciting.
0:19:42 The fourth and fifth editions of the list, we still have some breakouts, but we’re also starting to see the list kind of normalized, I would say.
0:19:47 Right, you said 11 new on the web for this time versus 17 last time.
0:19:47 Yes, exactly.
0:19:49 So even list over list.
0:19:51 And there’s fewer newcomers.
0:19:54 There’s a clear list of all-stars.
0:20:02 And the newcomers that we are seeing are kind of clustered around many of the same themes, like vibe coding and companionship, on this edition of the list.
0:20:05 I’m kind of bought into this all-stars concept now.
0:20:07 Like, we should maybe make jerseys for it or something.
0:20:07 I know.
0:20:08 And I’m very—
0:20:09 I’m proud of them.
0:20:11 I hope that they are proud of themselves.
0:20:11 Yes.
0:20:13 And I hope that they are rooting for themselves to remain on the list.
0:20:15 We should send them, like, trophies or something.
0:20:15 We should.
0:20:16 We absolutely should.
0:20:22 I would say when I’m looking for the next five lists, there’s a couple things that I have top of mind.
0:20:22 Yeah.
0:20:29 Our partner, Anish, wrote an article about how AI products are kind of verticalizing, even within these general products.
0:20:35 Like, you’ll go use Gemini for one thing and Claude for one thing and ChatGPT for another thing, perplexity for another thing.
0:20:37 I would expect that to continue.
0:20:43 We’re not seeing that this is necessarily a race that ChatGPT is running away with, especially on mobile.
0:20:45 People have lots of different use cases.
0:20:45 Right.
0:20:46 Grok.
0:20:47 We didn’t talk about Grok yet.
0:20:47 Yeah.
0:20:52 But they had a big debut on both the web and the mobile list this time around, which was super exciting.
0:20:54 And they popped up near the end of the period.
0:20:55 Exactly.
0:21:03 In terms of when Grok for the companions and the image and video, I imagine, is what drove a lot of the growth in the Grok app.
0:21:03 Exactly.
0:21:04 Yeah.
0:21:07 And Grok debuted, actually, in the top five at number four on the web list.
0:21:08 Wow.
0:21:09 On the web list.
0:21:11 Yeah, which is pretty surprising and exciting for them.
0:21:11 That’s incredible.
0:21:18 We also saw meta AI start to make a little bit of a dent this time around, not on the mobile list, but on the web list as well.
0:21:18 They have a web.
0:21:19 I should look into this.
0:21:20 Yeah, exactly.
0:21:27 So we’re still seeing, I think, things heat up, even in this space where you might guess that ChatGPT has kind of run away with it.
0:21:28 For sure.
0:21:37 I would say the other thing I’m expecting to see in the next two lists in particular, on the other end of the spectrum from creative tools where hallucinations are the feature.
0:21:38 Yeah.
0:21:43 There’s, like, productivity prosumer tools where hallucinations are a real problem.
0:21:43 Right.
0:21:48 So these are things that can make spreadsheets, slide decks for you, build financial models, answer emails.
0:21:59 We’re finally seeing both model reliability and kind of workflow and UI get to a point where these products are exploding in revenue, and I think they’re going to explode in usage as well.
0:22:00 For sure.
0:22:04 So I’m excited to see more in the prosumer product category on the next version of the list.
0:22:05 Manus made it this time.
0:22:06 Yeah.
0:22:09 Perplexity Comet as its own domain, I would expect might make it.
0:22:14 GenSpark is another one that I might expect to see on future versions of the list.
0:22:31 I think one really interesting thing that people sometimes don’t realize about more of these professional-ish use cases, you know, financial modeling, like you mentioned, or coming up with a presentation or, you know, doing a formal pitch or doc or whatever, is all of the evolution that we’re seeing on the foundation model side.
0:22:39 Like, you know, Grok 4, the new version of Claude, GPT-5, like, those aren’t just sort of in their bubble on the side, and then the app layer is separate.
0:22:43 A lot of these applications are powered by all of those models.
0:22:50 So as those models get better at things like math and logic and reasoning, they have less issues with hallucinations.
0:22:59 Like, that naturally supercharges all of these products that are in the kind of productivity, prosumer, accuracy is important space.
0:23:12 And I imagine we’ll reach a point where it tips them over from, like, oh, this was cool, but it was inaccurate too much of the time, so I can’t really use it, to, like, oh, this is now good enough that, like, it can do a lot of stuff for me, and I am willing to use it.
0:23:14 Yeah, I think that’s a great example.
0:23:25 Even things like GPT-5 release, being very good at consumer health questions, we might expect to see a wave of new and more reliable consumer health products on web or mobile on the next version of the list.
0:23:30 Yeah, I was thinking about what categories we didn’t see a lot of that we might expect to see in the future.
0:23:31 More ed tech, I think.
0:23:35 For sure, ed tech, because ed tech is another one where it’s important to not have a ton of hallucinations.
0:23:42 Personal finance is one where we haven’t seen a lot on either web or mobile, that I expect to see a bunch more on mobile, since it’s such a big category there.
0:23:43 Social?
0:23:43 Yep.
0:23:48 I think there’s been a lot of people wondering, when are we going to see the first big AI-native social platform?
0:23:48 Yes.
0:23:59 Which some could argue is now Facebook, which has largely been taken over by Boomer AI images, but I personally think there’s going to be at least one, probably multiple separate ones.
0:24:03 And honestly, Grok is sort of kind of making a case there in being a social platform.
0:24:18 I think health is a great example, a great category, or some of these more structured coaching, therapy, wellness types of things that I think a lot of people use Chat2PT for today, but probably deserve to exist in separate products that will hopefully make the list in the future.
0:24:25 Yeah, I agree. My biggest takeaway, actually, from every version of the list is that, as with everything else in consumer, there’s so much randomness.
0:24:31 And if we were able to perfectly predict the next great consumer product, there’d be hundreds of people out there building it.
0:24:41 So just like vibe coding nine months ago was a completely unexpected category to pop up on the list, I’m sure there will be one or two more in the next few editions, which is really exciting to think about.
0:24:44 Amazing. So we got to stay tuned for the sixth edition, it sounds like.
0:24:48 Click through to check out the full version of the list, which is out now.
0:24:53 We’d also love to hear in the comments what your favorite product or company is that made the list this time.
0:25:00 Or if you have any products you use all the time that you were shocked to find did not make the list, we’d particularly love to hear about those.
0:25:03 And we’ll see you in six months for the next one.
0:25:08 Thanks for listening to the A16Z podcast.
0:25:14 If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com slash A16Z.
0:25:16 We’ve got more great conversations coming your way.
0:25:18 See you next time.
0:25:32 As a reminder, the content here is for informational purposes only, should not be taken as legal business, tax or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund.
0:25:38 Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast.
0:25:45 For more details, including a link to our investments, please see A16Z.com forward slash disclosures.
0:00:11 get the latest consumer AI 100, their biannual ranking of the most used AI native products
0:00:13 across web and mobile.
0:00:18 They discuss how real users are adopting, what’s fading, and where the next wave of opportunities
0:00:19 might be.
0:00:20 Let’s get into it.
0:00:24 Hi, I’m Justine.
0:00:25 And I’m Olivia.
0:00:27 And welcome back to the A16Z podcast.
0:00:32 Today, we’re going to be discussing the consumer AI top 100 list.
0:00:37 So, Olivia, let’s start because you are compiling the list and you’ve been doing this for a
0:00:37 while.
0:00:40 What is this list and kind of what’s the purpose of it?
0:00:42 So, this is our fifth time doing this list.
0:00:43 We do it every six months.
0:00:48 We started at basically the dawn of the consumer gen AI era.
0:00:52 And the purpose is just to get a sense of what real consumers are actually using in AI.
0:00:57 As a sample set, we take every website and every mobile app in the entire world.
0:01:00 And we sort them in descending order of usage.
0:01:02 So, for websites, this is monthly visits globally.
0:01:05 For mobile apps, this is monthly active users.
0:01:08 We use similar web and sensor towers, these two data sources.
0:01:13 And then we grab the top 50 from each of those sources that are AI native companies.
0:01:17 So, you’ll notice that this captures usage, not revenue.
0:01:19 So, it’s not paid usage only.
0:01:24 It’s all usage, even people who are using the products for free, which to me gives an even
0:01:29 better and, I think, kind of more real sense of what is capturing consumer imagination in AI.
0:01:30 Totally, yeah.
0:01:38 I feel like a common question we often get as folks who are consumer investors in AI is, what are people doing on AI?
0:01:40 Yes, well, what should I be doing?
0:01:41 That, too, yeah.
0:01:46 And so, I feel like these lists are a really helpful way for folks to get a sense of what are some of the use cases,
0:01:51 what are some of the properties that are getting really big, getting a lot of users that you might not know about.
0:01:55 And for a lot of people, sort of an inspiration list of what they want to try out.
0:02:01 Let’s talk about the new companies on the list, because that’s always exciting of, like, who cracks into the top 50 for web
0:02:04 and the top 50 for mobile who weren’t in the list before.
0:02:04 Yeah.
0:02:06 How would you describe the new companies?
0:02:07 Were there any major changes?
0:02:08 Yeah.
0:02:11 The web list, I think, is the best way to track changes over time.
0:02:18 The mobile list is a little bit less stable, just because the app stores are constantly updating their policies on what’s allowed.
0:02:24 For our first couple mobile lists, it was just a wave of companies that were direct copycats of ChatGPT.
0:02:25 I remember that.
0:02:30 Yeah, and all the companies were, like, ChatGTP or Chat and Ask AI.
0:02:31 ChatGBT was a big one.
0:02:32 Exactly.
0:02:32 Yes.
0:02:34 And so those were dominating the mobile list.
0:02:39 So this time, we had a lot of new companies on mobile, as iOS ecosystem has cracked down on that.
0:02:42 But on the web list, we still did have 11 new names.
0:02:50 Sounds like a lot out of 50, but it’s actually a big reduction from, I think it was 17 new names six months ago.
0:02:50 Wow.
0:02:55 Which, to me, reflects the fact that the ecosystem is starting to stabilize a little bit more.
0:03:03 There were still a couple of really exciting trends that popped out on this list that I would expect might continue and yield more new names.
0:03:08 Vibe Coding was one of them, which I think kind of burst into the forefront at the end of last year.
0:03:15 So we saw it a little bit on our prior list in March, but it really kind of came into the forefront now.
0:03:19 So we have Bolt on our Brink list, just below the Top 50 Cutoff.
0:03:19 Awesome.
0:03:23 And then we have both Lovable and Replit on the web list.
0:03:33 In the past, a lot of the names on the list have been kind of in one of two categories, which is like general chat and companionship or creative tools, which I love.
0:03:35 I spent a bunch of time in both of those categories.
0:03:44 But it sounds like we’re starting to see things like vibe coding that are sort of outside of those two, what were really the killer use cases of consumer AI for a long time.
0:03:47 We definitely are more in productivity as well, which we’ll talk about.
0:03:50 I will say companionship continues to just dominate.
0:03:52 We actually did have three new companionship names.
0:03:59 So Juicy Chat, Joy, and Our Dream all made the list, alongside a bunch of others that have made the list before.
0:04:08 So Character was the biggest name, Janitor, Spicy Chat, Polybuzz, Crush On, ADOT, and Candy AI were all on this list and in the past.
0:04:15 So that’s a pretty notable section of the list that I think is dominated by companionship names, which is pretty interesting.
0:04:15 For sure.
0:04:19 And there’s also a lot of big companies that have products on the list, folks like Google.
0:04:23 Maybe you can talk a little bit about that because I think that’s been a surprise.
0:04:25 Yeah, Google had a big six months.
0:04:30 And I would say especially their models and even their consumer-facing products had a really big six months.
0:04:38 The way they structured their domains in the past made it hard for us to include Google products on the list since we needed to be able to independently rank their traffic.
0:04:44 So now we finally were able to for the first time, and four unique Google properties made the web list.
0:04:46 So Gemini was number two.
0:04:47 It was right behind ChatGPT.
0:04:54 It has just about 10% of ChatGPT’s traffic on web, but it’s much closer on mobile.
0:04:58 It’s like half of ChatGPT’s traffic on the mobile app, which is interesting.
0:05:01 It’s mostly Android users, which I think you would expect.
0:05:05 The other big debut for Google was a little more surprising to me.
0:05:10 It’s actually AI Studio, which is Google’s developer-facing sandbox.
0:05:14 So that’s where engineers go when they want to build things and test out Google models.
0:05:17 So that hit in the top 10 as well.
0:05:21 And then right below the top 10 was Notebook LM at number 13.
0:05:33 And I take your wow as a little bit of a surprise, which was a surprise to me, too, and I think a bit of a narrative violation that they went viral almost a year ago in September of 2024.
0:05:45 But they’ve actually kept up their traffic every month of flat or increasing traffic, with the exception of this last month of summer, when I think a lot of the academic usage caused it to decline, but just barely.
0:05:51 And then one of your favorites also made the list, which was Google Labs, down at number 39.
0:05:58 This is kind of the consumer-facing sandbox for Google models, whereas AI Studio is the developer-facing sandbox.
0:06:06 Google Labs includes VO3, the amazing new video model that you yourself have probably driven a big portion of the usage for.
0:06:07 I’ve spent a lot of money on VO3.
0:06:08 Yeah, exactly.
0:06:10 And driven many visits, for sure.
0:06:16 And actually, Google Labs includes a bunch of other products, like Doppel, which is their kind of outfit try-on product.
0:06:16 Yes.
0:06:18 It includes Portrait, which is coaching.
0:06:19 WISC, right?
0:06:20 WISC.
0:06:23 The image generation kind of sandbox, which is very cool and fun to play with.
0:06:24 Exactly.
0:06:27 Project Mariner, which is their agentic kind of browser sandbox.
0:06:38 But my hunch is it’s largely VO3, because traffic to that, to the Google Labs, spiked 15% in the month that VO3 was released, which is really exciting.
0:06:41 Let’s talk about the Chinese AI companies.
0:06:48 So, both new startups coming out of China, also big Chinese companies releasing models or consumer-facing properties.
0:06:52 How are these ranking on the list, and what do you think has driven their growth?
0:06:57 I mean, you could argue that Chinese companies show up in two or even three pretty interesting ways on the list.
0:07:03 I would say the first one are companies or AI products that are built for China and used in China.
0:07:05 And you might say, why?
0:07:21 And it’s because a lot of non-Chinese AI products, like ChatGBT and Claude, are banned in China because they have to follow specific regulations and policies and data capture rules that they’re not wanting to or able to do if they’re going to operate in China.
0:07:25 So, China doesn’t have a lot of those products that we have, but they have their own.
0:07:32 So, a couple companies that made the list are Quark, which is Alibaba’s AI assistant on both web and mobile.
0:07:37 Daobao, which is ByteDance’s AI assistant, also on both web and mobile.
0:07:41 And then Kimi, which is another general AI assistant from Moonshot AI.
0:07:46 Each of those ranks, actually, all of them in the top 20 on web.
0:07:53 And the majority usage in China, which I think reflects the fact that, like, China is the biggest country in the world by population.
0:07:57 So, even if they’re only used one place, they’re getting a lot of usage.
0:08:02 And they don’t have as much competition from the American general chat assistants that can’t be in the country.
0:08:04 Yes, like the chat GBTs of the world.
0:08:12 The second category of Chinese companies we’re seeing are startups that are developed in or around China, but are built for the rest of the world.
0:08:15 And you can’t actually even use them in China in many cases.
0:08:20 So, these are products like DeepSeek or the video models like Hilo and Kling.
0:08:20 Yes.
0:08:22 Or products like SeaArt for images.
0:08:22 Yeah.
0:08:28 I would say the concentration of these is especially strong in image and video, which is a space that you know well.
0:08:38 Yeah, I think image and video, we’ve seen a lot of great video models from China, particularly when it comes to animating from a single frame from an image.
0:08:46 ByteDance has also been doing a lot more around things like SeaDance, which is a really great video model they released that actually outscores VO3 on some of the arenas.
0:08:54 One of the really interesting things that I know we can’t disentangle in this data, but I think a lot of Chinese companies have taken the strategy in the U.S.
0:08:58 of distributing their models through U.S. properties.
0:09:07 So, there’s companies like CREA or Hedra that host various models and have subscriptions where you can access a bunch of the Chinese models at once.
0:09:16 Whether it’s the closed ones like Kling or Minimax or some of the open source ones like Wan or Quen, which a lot of people are using and really liking.
0:09:32 Some of them will also have their own consumer-facing properties, others will distribute through either the application layer, or honestly through folks like Fall and Replicate, more of the developer-facing platforms, where you can do one-off runs or you can have an API to use them in your application.
0:09:38 That is probably yet another way that Chinese companies are showing up in the list, in a way, as you said, that’s not measurable right now.
0:09:38 Right.
0:09:46 But the last trend that we were seeing with Chinese companies was products that are developed in China and used both in China and abroad.
0:09:47 So, Manus is a great example.
0:09:51 They just announced a 90 million annualized run rate.
0:09:55 And if you look at their traffic, it’s number one Brazil, number two U.S., and number three China.
0:09:56 Brazil surprises me.
0:09:58 Yes, a lot of AI traffic comes from Brazil.
0:10:00 More free traffic than paid traffic.
0:10:01 I was going to say, yes.
0:10:02 But a lot of traffic.
0:10:07 So, we’re seeing both kind of like this domestic AI ecosystem in China start to mature.
0:10:07 Yeah.
0:10:10 I think for the very first time on this version of the list.
0:10:10 Right.
0:10:16 And then we’re seeing the same thing we’ve seen on other versions of the list, which is Chinese companies exporting their AI products abroad.
0:10:29 And then to talk about another big trend, which you touched on earlier, vibe coding, we’re probably all seeing the tweets from various vibe coding companies that are like, we went zero to 100 million or even more in ARR in a really short period of time.
0:10:35 They have millions of users, kind of faster growth than I think we’ve seen in many other categories in a very long time.
0:10:39 I’m curious, how did you see that kind of reflected on the list?
0:10:40 And how did that change since the last edition?
0:10:49 Yeah. So, six months ago, it was just Bolt on the list. Now, Bolt actually is on the brink list. And Lovable and Replit both made it onto the main list.
0:10:55 To me, I was particularly interested to look at not just traffic for these, but also revenue and retention.
0:11:06 So, Lovable recently announced $100 million in ARR. But it’s always easy to say, especially for consumer properties, like, yeah, a lot of people are maybe signing up for a trial, but they’re canceling.
0:11:08 They’re not going to stay on. Retention is low.
0:11:15 We actually also, for the vibe coding products, looked at revenue retention across another data provider, Consumer Edge.
0:11:24 So, that looks at a cohort of everyone who signs up in month zero, how much are they paying and what percent are still paying in month one, month two, month three.
0:11:37 And we put some of this in the report, but what we found for many of the leading vibe coding platforms is they actually see 100% or above revenue retention in the first three months and then maybe flatten out a bit below 100%.
0:11:41 Which, as a point of comparison, is very strong for what we see.
0:11:51 I mean, it’s very rare to see any sort of, especially consumer, prosumer, might suggest that there’s some enterprise usage happening there with prototyping and stuff within companies.
0:12:04 Enterprise usage or even just solo vibe coders, people building projects who do get a low-cost plan to try it out and then find themselves actually publishing and using something and buying more credits and upgrading to the next plan, which is exciting.
0:12:13 It’s interesting, though, on that point, for both Lovable and Replit, we can independently see traffic to the sites where you vibe code things.
0:12:15 So, that’s where you or I would go.
0:12:18 Oh, because they’re hosted on Lovable.app.
0:12:27 Yeah, so you can see traffic for everything people are making with Lovable and Replit, and then separately, traffic to Lovable and Replit, which are the people making things.
0:12:34 And in both cases, the people making things traffic is much higher than the traffic to the things that they are making.
0:12:34 Yes.
0:12:36 Which suggests one of two things.
0:12:42 One, it could be that people who are making serious, high-traffic websites are buying domains for them.
0:12:48 A custom domain, so they no longer pop up under the Lovable or the Replit domain in this data.
0:12:49 So, their traffic would not get included.
0:12:50 Yeah.
0:12:57 Or it could be the case that people are building almost personal software, software for themselves with these vibe coding platforms.
0:12:57 Yeah.
0:13:04 So, they might publish them and not get a lot of hits, but they’re extremely valuable to the individual user or maybe the user’s family and friends.
0:13:08 And I’m curious, have we seen anything yet in vibe coding coming to mobile?
0:13:10 Like, are there any?
0:13:10 Not yet.
0:13:10 Interesting.
0:13:16 There’s a couple companies, startups that we’ve seen, but none of them ranked high enough to get a spot on this list this time.
0:13:19 Yeah, it will be super interesting to see the next edition of the list.
0:13:19 Maybe for the next edition, for sure.
0:13:21 Like, if any of those start popping up in the top 50.
0:13:26 It’s hard to displace the companionship and the AI girlfriend ones, for sure.
0:13:26 Yes.
0:13:28 But maybe a vibe coding one can do it.
0:13:28 Yes.
0:13:32 No, it’s actually a good point because we did, on the point of displacement, for the first time,
0:13:35 we ranked what I’m calling our AI all-stars.
0:13:36 Cool.
0:13:38 So, this is across five lists.
0:13:41 What are the companies that have made the list every single time?
0:13:42 Amazing.
0:13:44 Which is hard to do because this dates back two years now.
0:13:47 So, there’s 14 of these companies.
0:13:56 So, we have ChatGPT, not a surprise, Perplexity, and Poe all made the list in what I call kind of general LLM assistance.
0:14:00 Then we have Character AI in Companionship.
0:14:00 Yeah.
0:14:01 They’ve made it on both web and mobile.
0:14:09 We’ve got Mid Journey, Photo Room, Leonardo Cutout Pro, Veed, and Eleven Labs in Creative Tools.
0:14:16 We have Quillbot and Gamma in Productivity, and then we have Hugging Face and Civit AI in Model Hosting.
0:14:19 And so, those have made the web list for every single one?
0:14:21 Web list for every single, got it.
0:14:23 Every, all five of the versions we’ve done of this now.
0:14:23 Amazing.
0:14:29 It was funny looking back at the very first list because I think we had this question of,
0:14:36 is it only going to be companies that invest tens of millions of dollars into proprietary models that are able to hold consumer attention?
0:14:37 Yeah.
0:14:45 But now, when we look at these 11 all-stars, more than half of them are actually hosting or using other people’s models or are model aggregators.
0:14:46 Right.
0:14:54 And so, I think that speaks to the fact that in consumer AI, the UI and the product experience matters just as much as the model,
0:14:59 especially when so many amazing models are now API-available or open source.
0:15:05 If you think of some of those properties, too, some of them have built really deep and interesting workflows around creating content,
0:15:07 even if they don’t have their own model.
0:15:07 Yeah.
0:15:13 Some of them are also starting to see what I would say are sort of the first kind of non-data network effects in AI,
0:15:23 especially things like Hugging Face and Civic AI, where, you know, you have these communities where people are hosting tons of models or LORAs or data sets.
0:15:24 They’re commenting on them.
0:15:25 They’re ranking them.
0:15:28 They’re spitting up many apps that you can only access on that website.
0:15:28 Yeah.
0:15:36 So, it’s pretty cool to see both of those kind of make the list over and over again and show that you can maybe have network effects in AI.
0:15:36 Yeah.
0:15:42 I think you could argue, too, 11 Labs is the same, where people can publish their voices on 11 for other people to use.
0:15:50 The voice libraries, I hear that all the time from people, that one of the reasons they love using 11 is there’s thousands and thousands of voices you can choose from,
0:15:53 and that’s because so many folks have uploaded voices to the voice library.
0:15:57 You could even argue the same is true for a ChatGPT or MidJourney.
0:15:58 Yep.
0:16:05 Where the more user data they get, the better models they can train, which then makes the product better and attracts more users, and it’s a whole virtuous cycle.
0:16:05 Yeah.
0:16:13 I think that is the natural assumed network effect for AI, which is kind of more users, more data, more feedback, better models.
0:16:23 But I know a lot of folks are wondering, like, where are the network effects beyond that, which is why I was particularly interested in, like, the hugging faces, civic AIs of the world, things like the 11 voice library.
0:16:30 Yeah. We’re even starting to see, in some cases, Gamma is a good example of this on the list. 11 is another good example. Same with PhotoRoom.
0:16:43 These consumer AI properties are almost graduating to enterprise usage with things like team plans, templating, you know, design libraries, and then it becomes something that can spread organically through a team and that a whole organization can benefit from.
0:16:52 And the more you invest into building out, say, your templated slide deck on Gamma, the harder it is to kind of churn and move over to another platform, so.
0:17:04 Yeah, I think that’s one thing that a lot of people didn’t expect with a lot of these, especially creative tools or productivity tools that I try to tell founders all the time, is, like, there’s so many AI enthusiasts now.
0:17:07 Some are tourists, but some have real use cases.
0:17:19 And often with companies like 11, we will see one individual signs up, they try it out, they see if they like it or not, and then that individual actually becomes, like, their own self-serve enterprise sale.
0:17:30 Like, they bring it into their company, they make the case for it, and then it’s so easy for, and then they go to the business and they’re like, hey, we actually have 10 or 15 or 20 users on individual plans.
0:17:47 Like, we should have some sort of enterprise-level contract here, which makes it a lot easier for these AI companies to grow than the traditional top-down sales that enterprise software had to do, where you had to go in and get approval from 10 different people and then convince the employees to use the product.
0:17:55 versus this bottoms-up adoption that we’re seeing with a lot of these freemium AI products that start in consumer feels very cool and unique.
0:18:05 Yeah, and that in turn supports more consumer growth because then someone on a team will adopt it because their other team member had it, and then they’ll bring it home and use it for a project and spread to their friends and their kids.
0:18:12 And, yeah, I expect we’ll continue to see more prosumer enterprise representation on this consumer AI list.
0:18:15 So this, as you’ve mentioned, is the fifth edition of the list.
0:18:25 I’m curious, reflecting back on all of the past editions, what are your biggest takeaways, and do you have any hot takes or predictions for what we’re going to see in the next few lists?
0:18:38 Yeah, I would say looking at the list now and then looking back, I really can appreciate now that the first list or two was total chaos in the sense of half the list was new every time, if not more.
0:18:40 And the traffic was fluctuating so wildly.
0:18:41 Yes.
0:18:47 And there’s often, you know, like a two-week to one-month delay between when the data happens and when we get it through the data sources.
0:18:54 And so founders would be contacting us angry, like, hey, I’m actually ahead of this other property now.
0:19:02 I should be number two instead of number five, just because the data sources had a little bit of a lag and things were so volatile back then.
0:19:03 Things were changing so rapidly.
0:19:13 I would say that, as you said, companionship and general LLM assistance, like ChatGPT and then creative tools were kind of the three categories that were working two years ago.
0:19:20 And anything else that popped up on the list in many cases was pretty random and would spike one month and be gone the next month.
0:19:24 I would say we’ve had a lot of stabilization since then.
0:19:29 By the third edition of the list, we started seeing things that weren’t just image and text.
0:19:33 We started seeing video, we started seeing music, which was really exciting.
0:19:42 The fourth and fifth editions of the list, we still have some breakouts, but we’re also starting to see the list kind of normalized, I would say.
0:19:47 Right, you said 11 new on the web for this time versus 17 last time.
0:19:47 Yes, exactly.
0:19:49 So even list over list.
0:19:51 And there’s fewer newcomers.
0:19:54 There’s a clear list of all-stars.
0:20:02 And the newcomers that we are seeing are kind of clustered around many of the same themes, like vibe coding and companionship, on this edition of the list.
0:20:05 I’m kind of bought into this all-stars concept now.
0:20:07 Like, we should maybe make jerseys for it or something.
0:20:07 I know.
0:20:08 And I’m very—
0:20:09 I’m proud of them.
0:20:11 I hope that they are proud of themselves.
0:20:11 Yes.
0:20:13 And I hope that they are rooting for themselves to remain on the list.
0:20:15 We should send them, like, trophies or something.
0:20:15 We should.
0:20:16 We absolutely should.
0:20:22 I would say when I’m looking for the next five lists, there’s a couple things that I have top of mind.
0:20:22 Yeah.
0:20:29 Our partner, Anish, wrote an article about how AI products are kind of verticalizing, even within these general products.
0:20:35 Like, you’ll go use Gemini for one thing and Claude for one thing and ChatGPT for another thing, perplexity for another thing.
0:20:37 I would expect that to continue.
0:20:43 We’re not seeing that this is necessarily a race that ChatGPT is running away with, especially on mobile.
0:20:45 People have lots of different use cases.
0:20:45 Right.
0:20:46 Grok.
0:20:47 We didn’t talk about Grok yet.
0:20:47 Yeah.
0:20:52 But they had a big debut on both the web and the mobile list this time around, which was super exciting.
0:20:54 And they popped up near the end of the period.
0:20:55 Exactly.
0:21:03 In terms of when Grok for the companions and the image and video, I imagine, is what drove a lot of the growth in the Grok app.
0:21:03 Exactly.
0:21:04 Yeah.
0:21:07 And Grok debuted, actually, in the top five at number four on the web list.
0:21:08 Wow.
0:21:09 On the web list.
0:21:11 Yeah, which is pretty surprising and exciting for them.
0:21:11 That’s incredible.
0:21:18 We also saw meta AI start to make a little bit of a dent this time around, not on the mobile list, but on the web list as well.
0:21:18 They have a web.
0:21:19 I should look into this.
0:21:20 Yeah, exactly.
0:21:27 So we’re still seeing, I think, things heat up, even in this space where you might guess that ChatGPT has kind of run away with it.
0:21:28 For sure.
0:21:37 I would say the other thing I’m expecting to see in the next two lists in particular, on the other end of the spectrum from creative tools where hallucinations are the feature.
0:21:38 Yeah.
0:21:43 There’s, like, productivity prosumer tools where hallucinations are a real problem.
0:21:43 Right.
0:21:48 So these are things that can make spreadsheets, slide decks for you, build financial models, answer emails.
0:21:59 We’re finally seeing both model reliability and kind of workflow and UI get to a point where these products are exploding in revenue, and I think they’re going to explode in usage as well.
0:22:00 For sure.
0:22:04 So I’m excited to see more in the prosumer product category on the next version of the list.
0:22:05 Manus made it this time.
0:22:06 Yeah.
0:22:09 Perplexity Comet as its own domain, I would expect might make it.
0:22:14 GenSpark is another one that I might expect to see on future versions of the list.
0:22:31 I think one really interesting thing that people sometimes don’t realize about more of these professional-ish use cases, you know, financial modeling, like you mentioned, or coming up with a presentation or, you know, doing a formal pitch or doc or whatever, is all of the evolution that we’re seeing on the foundation model side.
0:22:39 Like, you know, Grok 4, the new version of Claude, GPT-5, like, those aren’t just sort of in their bubble on the side, and then the app layer is separate.
0:22:43 A lot of these applications are powered by all of those models.
0:22:50 So as those models get better at things like math and logic and reasoning, they have less issues with hallucinations.
0:22:59 Like, that naturally supercharges all of these products that are in the kind of productivity, prosumer, accuracy is important space.
0:23:12 And I imagine we’ll reach a point where it tips them over from, like, oh, this was cool, but it was inaccurate too much of the time, so I can’t really use it, to, like, oh, this is now good enough that, like, it can do a lot of stuff for me, and I am willing to use it.
0:23:14 Yeah, I think that’s a great example.
0:23:25 Even things like GPT-5 release, being very good at consumer health questions, we might expect to see a wave of new and more reliable consumer health products on web or mobile on the next version of the list.
0:23:30 Yeah, I was thinking about what categories we didn’t see a lot of that we might expect to see in the future.
0:23:31 More ed tech, I think.
0:23:35 For sure, ed tech, because ed tech is another one where it’s important to not have a ton of hallucinations.
0:23:42 Personal finance is one where we haven’t seen a lot on either web or mobile, that I expect to see a bunch more on mobile, since it’s such a big category there.
0:23:43 Social?
0:23:43 Yep.
0:23:48 I think there’s been a lot of people wondering, when are we going to see the first big AI-native social platform?
0:23:48 Yes.
0:23:59 Which some could argue is now Facebook, which has largely been taken over by Boomer AI images, but I personally think there’s going to be at least one, probably multiple separate ones.
0:24:03 And honestly, Grok is sort of kind of making a case there in being a social platform.
0:24:18 I think health is a great example, a great category, or some of these more structured coaching, therapy, wellness types of things that I think a lot of people use Chat2PT for today, but probably deserve to exist in separate products that will hopefully make the list in the future.
0:24:25 Yeah, I agree. My biggest takeaway, actually, from every version of the list is that, as with everything else in consumer, there’s so much randomness.
0:24:31 And if we were able to perfectly predict the next great consumer product, there’d be hundreds of people out there building it.
0:24:41 So just like vibe coding nine months ago was a completely unexpected category to pop up on the list, I’m sure there will be one or two more in the next few editions, which is really exciting to think about.
0:24:44 Amazing. So we got to stay tuned for the sixth edition, it sounds like.
0:24:48 Click through to check out the full version of the list, which is out now.
0:24:53 We’d also love to hear in the comments what your favorite product or company is that made the list this time.
0:25:00 Or if you have any products you use all the time that you were shocked to find did not make the list, we’d particularly love to hear about those.
0:25:03 And we’ll see you in six months for the next one.
0:25:08 Thanks for listening to the A16Z podcast.
0:25:14 If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com slash A16Z.
0:25:16 We’ve got more great conversations coming your way.
0:25:18 See you next time.
0:25:32 As a reminder, the content here is for informational purposes only, should not be taken as legal business, tax or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund.
0:25:38 Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast.
0:25:45 For more details, including a link to our investments, please see A16Z.com forward slash disclosures.
What are real consumers actually doing with AI today?
In this episode, a16z consumer investors Olivia Moore and Justine Moore break down the fifth edition of our Consumer AI 100, a biannual ranking of the most used AI-native web and mobile products across the globe.
Timecodes:
0:00 Introduction
1:45 New Companies & Trends
3:32 Companionship & Creative Tools
4:20 Big Tech on the List: Google’s Impact
6:24 Chinese AI Companies & Global Trends
10:19 Vibecoding: A New Trend
13:40 AI All-Stars: Consistent Top Performers
15:30 Network Effects & Product Experience
17:20 Enterprise Adoption & Prosumer Growth
19:40 Biggest Takeaways
21:09 Grok’s debut
22:56 Future predictions
25:14 Closing & Audience Engagement
Resources:
Read more about the Top Gen 100: http://a16z.com/100-gen-ai-apps-5/
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Find Justine on X: https://x.com/venturetwins
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.