The New Research Stack: AI, Creators & Confused Algorithms

Check out the full episode below! Enjoy The Exchange? Don't forget to tune in live Friday at 12 pm EST on the Greenbook LinkedIn and Youtube Channel!

The market research industry is being turned upside down. NIQ just went public for over a billion dollars, prediction markets are beating traditional research, and the industry grew 7.6% despite economic chaos.

But here's the kicker: while everyone's obsessing over AI, Gen Z's "algo speak" is evolving faster than algorithms can keep up. Terms like "skibbity" and "riz" are breaking fraud detection systems and confusing market analysis.

With ChatGPT-5 on the horizon and Amazon betting big on creators, the real question isn't about technology – it's about who can adapt fastest in a world where language changes overnight.

Many thanks to our producer, Karley Dartouzos. 

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Transcript

Lenny Murphy: All right, we are live. We are live.

Susan Griffin: Oh my goodness, live in the middle of the hot summer. Cooling off here in Kentucky.

Lenny Murphy: Actually, it cooled down.

Susan Griffin: The big thunderstorms, it's cooled down a bit in the Northeast. Oh, that's right.

Lenny Murphy: Did you swim to work this morning?

Susan Griffin: Well, actually, we swam last night from New York City to Western Massachusetts, where we have a small place. Yeah, definitely. There were backstrokes and breaststrokes involved.

Lenny Murphy: I always wanted, remember back in the 60s when there were cars that were also boats, and they never caught on. But I've always thought, yeah, I want a multi-purpose vehicle, just a flying car that also could go into the water.

Susan Griffin: Our daughter went to college in Boston, and they had the duck boats. Yes, yes. Yeah. Anyway, But I keep saying out, Lenny, do people even know who I am? I'm not Karen, clearly.

Lenny Murphy: I think everybody knows who you are, Susan, but for those who do not, because you are one of the most prominent, influential people in my world. So, Susan, go ahead.

Susan Griffin: Go ahead. Well, I'm Susan Griffin. Been around this world for a long time. And I've got a marketing consultancy called Griffin and Skeggs Collaborative, but I've had past lives in market research. And Lenny every once in a while brings me on the exchange, particularly when Karen has the week off, Karen's on a well-deserved vacation. And so I'm the mere mortal who's come along for the ride today. Oh, well, I don't know about all that because you are vital to what we're going to do.

Lenny Murphy: So guys, a little different approach today where we're going to pop through a couple of news things. But then there's a whole bunch of links that Karley is going to share that are indicative of a, of a story, of a shift. And Susan, as we had discussed, what I really want is to get your perspective, as someone who has led and built sales and marketing organizations in this space, of the impact of these changes. This, this picture, this Connect the Dots is gonna be pretty damn clear, as we go through this and get there. So guys, that's why Susan is here. She's being far too humble. She is the keeper of the wisdom on today's topic. So. Well, thank you.

Susan Griffin: But we got lots to go through.

Lenny Murphy: We do. There was so much. There was.

Susan Griffin: There was a lot that popped in. Go ahead. Yeah. Well, Lenny, one of the things you sort of brought to my attention. I knew it was happening, but the NIQ IPO, 10, no, what was it? 1.05 billion. That was a big thing. And then you also brought to my attention NIT and their raise of 16 million. Their latest raise. Their latest race, right. And what's interesting about that one is they are leaning into the need for the integration of the human and the AI, which I think is a slightly different positioning. But then I don't really know Polymarket that much, but talk about that one, that story. I want to make one point before I get there.

Lenny Murphy: What is interesting about NIT and Nielsen. So Nielsen made some other announcements this week about the launch of their, effectively their marketplace. Right, right. So, they are going for the platform play as a data platform that enables and connects lots of other research. We'll circle back around to that theme in a minute. And NIT, I think, is positioned fundamentally as an operating system for research as well. So, you know, it's leveraging data and technology to enable more efficient processes. So I said, well, again, a trend there. Polymarket, I think, is just something to pay attention to primarily because they, so prediction markets, right? In fact, they make their money as a betting market, but they are prediction markets, wisdom of the crowd, right? And arguably, like in the last election cycle, not just here in the US, but elsewhere, they're highly accurate, right? Their outcomes were highly accurate. So the point is that idea of a very large, very scalable prediction market platform that does lots of things, whether you're betting on a game or, or an election or the success of an ad or a business that's like everything is on the table. Um, and that model is, it continues to gain credibility, which has been around forever. I mean, you, or a brain juicer, right? I mean, prediction markets, wisdom of the crowd has been something, you know, forever. They're scaling that. They're not the only ones. Uh, and now they're, they're buying, uh, they bought QXC, um, to with crypto prediction trading. So they're building financial systems based on the wisdom of the crowd across multiple categories. They integrated with, uh, with X leveraging their data. So as we think about another approach in research that doesn't have anything to do with the traditional model of asking questions, but rather harnessing individual capabilities, pay attention to this. Because there's been other plays. They seem to be the biggest. I mean, they're getting real money.

Susan Griffin: But getting it back to more sort of like short and visibility into the market research industry. Talk to us a little bit about the Insights Association's State of the U.S. Insights and Analytics Report.

Lenny Murphy: Yeah, so we talked about it a little bit last week, the Insights Association, along with SMR and Michigan State and, oh gosh, I forgot one of the data companies. Anyway, we released our annual report based on 2024 data. I think what is really interesting is, well, there's lots of interesting things. They did a great job and there's more perspective than just data. So definitely encourage you to download it. It's worth the money. Some of the trends they were detecting were from 2024. Let's see how that carries into 2025. The trajectory is good growth. The US industry grew by 7.6%, 82.9%. But the driver of the growth, no surprise, technology, data analytics, right? It's the data side of stuff. And that was last year before we hit this tipping point that I think that we have hit, kind of the AI revolution.

Susan Griffin: Right. Well, but what's interesting to me is that in this moment of, you know, uncertainty where brands that sell to consumers are kind of in a state of paralysis around what's going to be the impact of tariffs, and what's going to be the impact of inflation, and what's going to be the impact of employment. In this uncertainty, we're still seeing all of these investments. So there is money, and there are people with a long-term perspective about a future that's worth investing in. So that I find fascinating.

Lenny Murphy: Uncertainty is great for, for research, right? I mean, it drives the demand for insights, you know, to, to get to certainty. So, uh, what's changed is the form and, and factor of how we get to that information fundamentally. But I, I, I was on a call earlier this morning with, uh, the company was like, and they've said what I've been saying. Insights, the demand for insights is only going to increase because the uncertainty is only increasing, or maybe the better I said, the rate of change, right? We can't just assume anything anymore about how things were. So that's great. How do we fine tune our business models as an organization that provides certainty through information? That's the wild ride that we're on.

Susan Griffin: Well, now that's an interesting segue into something that we were talking about in preparation for today. And that is, you know, big tech and the big consulting firms. Because they are succeeding with all the tools that they use in their big engagements. They are succeeding in galvanizing the interest and the the sense of urgency in the C-suite, but I keep thinking about, you know, the rate of change and how it impacts operationalizing these concepts for, you know, I remember mobile is going to change everything, but how, and how do I apply, how did I apply that as a brand back when that was the big, um, disruption. But now with AI, and arguably AI is changing things faster than we could have even imagined. And the C-suite says, yes, because McKinsey told us it's going to change everything. How does that cascade down in a way that the organization can actually operationalize it and utilize it to make that organizational change that's going to drive growth.

Lenny Murphy: So that is, um, yeah, let, let's, let's go there now. So Karley, uh, if you want to take all of those links on, uh, from the big story from the run of the show and just go ahead and pop them in. Um, cause these are just data points. So guys, you're going to get a whole bunch of links. Um, I think. The research industry developed as a way to collect information, right? And think about them, and everything fundamentally that's happened for the last 80 years has been just changes in how we collect information. So from, you know, mail to telephone, to online, to mobile, even social media. And there were some levels of disruption and a kind of democratization. But fundamentally, it was a manufacturing process, right? We built, we stepped into a niche to fill that gap of getting information and then delivering it in a way that folks can make decisions on. I think that the fundamental difference that we have now is twofold to your question. We see all the big tech companies coming in, or I'm sorry, all the big consulting companies, and you're getting all those links that we just had here. It's all going to change, because they are experiencing them, because fundamentally, they're in the same business. They're slightly different. They're in the business of saying, Oh, here's what the information means to you. But underneath that certainly is the data collection component. And they're in the same world now that we all are, that is, we've got the data feeds, those have been established for a long time. What we didn't have was a way to synthesize all of that effectively to drive unlocking new value in that data. That's what AI does. Is an unlock from a productivity perspective that creates more value from information while at the same making the entire process incredibly efficient, which is disruptive to business processes underneath.

Susan Griffin: Particularly when those business processes, you know, despite all of our intentions to change this, have been so siloed. So, you know, the ability to unlock, to leverage AI to unlock all of the insights that can drive growth still face the fact that the devil's in the details. Data is sitting in separate places and there isn't a magic bullet that's going to necessarily allow the power of AI to get to all of those siloed sets of insights. Well, I don't know if I agree with that.

Lenny Murphy: I mean, I think the AI I think you still gotta, you still gotta put it in the gun and aim it. I mean, so, and I think that's what we're seeing in these numbers. So in these links would- Maybe you've got to put it in the syringe and get it in the vein. The medicine's there, right? Right. Whatever, but that's, that's significant. That is what we call pace of change. That's adoption. Right.

Susan Griffin: Right.

Lenny Murphy: If you look at the numbers that came out this week on, uh, in all those links that we came out on,, uh, uh, Microsoft beat expectations and it was Azure revenue, their operating system platform, 75 billion a year. The Gen AI apps doubled their revenue, growing to 1.7 billion for the first half. Open AI hits 12 billion in analyzed revenue. That's double what it was a year ago. Those numbers aren't driven by individuals. Those are enterprise sales. Those are enterprise integrations. So if we use that as a proxy, and I think that a huge piece of that is, for that, we're really on the adoption curve to bring down those silos. That's what's happening there. Obviously, it costs a lot of money. So the big brands are doing that first, because they have the money to spend. And they have a greater imperative. Unlock it. But it's becoming more widely distributed, cheaper, the barriers to entry for smaller businesses and even for individuals are decreasing. So we're, we are well on that way, that path, well on that path. And it ain't stopping. And now we're starting to get the implications of what that means, not just for the, the, go back to our industry. Where do we fit in now that is no longer driven by our own silos that we create, our own defensive moats, we have this data, right? Or we have this particular expertise, or we have this specific technology. Those are- Particularly if it's niche, right?

Susan Griffin: Right. I mean, you could have, I see a lot of companies who have a tool or a methodology and it might be integrating AI. Most of the time, it is in some way, shape, or form. But if it's standalone, and it's not going to plug into those ecosystems of discovery on the part of the buyers, they're going to be hard pressed to actually. And we kind of will get to this. Differentiating your story, particularly if you're a niche player, becomes mission critical because all of the platitudes, better, cheaper, faster, did I say better chap or feaster? I don't know. Easy for you to say. I mean, there are a lot of companies who are emerging that have that semi-niche characteristic who don't know how to differentiate themselves. And if they're not plugging seamlessly into a bigger ecosystem, their path to growth is even more fraught. Right. So if we look at the...

Lenny Murphy: One that jumped out for me is looking at... There were a few other articles here that we posted on the consulting companies. McKinsey sees an AI surge, consulting, 40% of their 2024 business from AI projects, BCG, 20% of 2024 revenues, doubling to 40% by 2026, Accenture, 4.2 billion in generative AI sales. Now here's the thing, they're not creating AI, right? Oh, and my dog says hello, sorry about that.

Susan Griffin: In violent agreement.

Lenny Murphy: Yes, they're blocked out of the office. And they're not happy about it. So what they are selling is consulting. They say, here's all these tools, and here's how you unlock those silos and create value for that.

Susan Griffin: But there is skepticism out there that the big firms are actually the ones who are helping get from concept to reality.

Lenny Murphy: Right. I've had McKinsey in which its clients, you know, there're incredibly smart people. I'm not going to take anything away from them, um, uh, doing that. But as a consultant, I know the joy of consulting is all I have to do is hand you the directions and then I leave. Um, right. So it's not, I don't necessarily have to get into the implementations. Here's what to do. Bye. Thank you. Thank you for checking. And that's kind of the way that it works.

Susan Griffin: So anyway, they're making money. Off of the concept of AI. But it is firms like, you basically drew the line for me, it's firms like Knit, much further down in the visibility arena perhaps, but who are actually delivering tools that they can help companies implement are helping them realize real value. And they are profitable as a result. Because they're part of the connective tissue, right?

Lenny Murphy: It's like a valve on a pipeline. If you make good valves, you're going to make a lot of money, because valves are important to help control the flow. And I don't mean that not. If you're listening, I'm not saying that you're just a valve. But I'm saying these operational components create efficiencies that help streamline the processes, you know, absolutely are vital, especially today. And if you get in early, like they are, then you're, you're foundational. And then you rely on, you know, as long as you keep doing the right stuff, so that you're foundational to the system, then you're, you're great, you're in a great spot. But how many of those are right? The even, even look, just the AI companies, right? There's effectively four big ones right now. Well, we'll call it six actually, but there's not a hundred. It's only six right now. Right. Consolidation of them at some point.

Susan Griffin: So the, but the low barrier to entry actually is now, um, accelerating the small niche players because where there's maybe six big AI companies, think about the number of companies that we have seen being part of the IAX ecosystem in the last two years, the number of net new companies who are somehow leveraging, I mean, if there are only six big AI companies, think about how many AI enabled companies are in the online call space now, right?

Lenny Murphy: And I would say, I had a conversation with the CEO one of those companies said, we want to be a unicorn. And my response was, you cannot be. Exactly. You will not be. What you can do is build a really good, nice business and get over the course of the next two years and then sell to be part of an ecosystem. But you're likely, and sorry guys, please don't shoot the messenger, if you're building that type of business, I think you're probably building it to sell. That's the right thing to do. Because we're not going to see, there's certainly gonna be winners and losers, but the barrier to entry for your features and capabilities is incredibly low now. The barrier to entry is client adoption fastest. That's your best.

Susan Griffin: Right, right, which means your sales and marketing have to be absolutely bulletproof, rock solid, and have to be really intelligent in terms of how to rapidly build that adoption base. That's right.

Lenny Murphy: And that's why we see, so let's go back, Karley, to the product launches for a minute. Yeah. Because these are companies that, so Displayer, their AI-powered research agent, VoxPopMe, VoxPopMe Signals, which is this. Synthetic sample type of model, pure profile, AI-powered message testing. So these are trusted brands that already have good relationships. And they're not just doing this for me, too. They're doing it because they want to build on that trust to continue, because that's their most. Their most is they're already engaged with these relationships, and they're a trusted partner, and they're going to build capabilities to do that so they can continue to be part of that ecosystem, not because they think no one else could do this. Every single one of these things, someone else could do. I actually saw a demo last night of a few other integrations of AI with traditional data analytics platforms that was fairly shocking on how good it is. So Display, you're doing a fantastic job. We love you. You're a partner of Grit. So again, not trying trying to denigrate the value of what everybody is building, just recognizing that the barrier to entry to build something similar by others is very low now.

Susan Griffin: Well, and I do want to, this is an unpaid political announcement here, but Green Book has launched a series of buyer's guides that are thematic. They did two earlier in the year, user research and one on shopper insights. Green Book is about to launch three others on sampling solutions, online qual and brand solutions. And then in October, there are buyer's guides that are going to focus on social media insights, solutions, data analytics and synthesis and non-conscious measurement. Now, why do I mention this? From a point of view of that, we'll call it musical chairs. It's going to happen with all of these emergent companies for whom the mode is not the technology, because so many people can do it. That barrier to entry is not, as you say, Lenny, the features and functions. The barrier to growth is going to be adoption. You've got to be discovered. You've got to be found. Yep. And we've talked about it, or Lenny, you've certainly talked about it on the exchange. The large language models are going for discovery are going to be trained on readily available, open, robust data sources and Greenbook's ongoing evolution of new tools for suppliers is transforming the Green Book value proposition into being a recommendation engine. And so part of that equation for suppliers who are trying to differentiate is to make sure that everything you can say that is going to enhance your ability to be able to capture adoption than the competitors, you need that to be visible. And what Greenbook is doing to transform itself is gonna be part and parcel of how you're going to leverage that. Will there be winners and losers?

Lenny Murphy: But it's about being integrated into the marketplace. There's actually, there's two posts, Karley, I see that you put up. How AI collapses or rebuilds marketplace boats. It's a blog post, but it is incredibly insightful. Definitely check that out. That kind of speaks to your point, Susan, around where are the marketplaces for buyers to engage, whether it's a widget or strategic consulting, right? Synthesizes, combines, and centralizes. That's what it does. So that lends itself directly to the fact that there's different ways around discoverability. The other one is, Carla, it's the very last one, how to get recommended by ChatGPT. That's an interesting article from a marketing standpoint, but to your point, Susan, it also changes in that world. We're not about buying AdWords anymore and where we can, you know, a small company could compete with a big company just because you're throwing enough money at it, or SEO optimization. It is about authority and content, et cetera, et cetera. And in that world, that is a centralization model. Um, it's around, you know, aggregation and curation of authority content. And it just changes the game and how you market the guys that may sound self-serving. Look, I'll just tell you the truth. When all this started from a green book standpoint, we were like, Oh shit, what is going to happen to us? We were scared.

Susan Griffin: And then the penny dropped and we said, Oh, geez.

Lenny Murphy: Right. Wait a minute. Actually, building curated content, you know, in mass. Wow. Didn't know that's what we were doing, but, you know, luckily enough. And my point is, it's not yet. Sure. Talk, talk to us. We'll help you whenever we can. The point is just the way that we market is changing. And, uh, and the way that we engage with, uh, with buyers is changing fundamentally because of technology and this transformative impact of that. I want to be conscious of time. There's a couple things that I think are worth calling out real quick that were just kind of cool. Did you see under the tech developments that Amazon is investing in the Netflix of AI startup Fable, which was just, so just is, it's a platform and you wanted to, I really love Scooby-Doo. I want to make new Scooby-Doo cartoons, right? That I'm going to write the script for, and it's going to animate those Scooby-Doo cartoons, and it's going to share it out on a marketplace, right? Whatever the case may be. I just think that's super cool. If that grows from a creator economy standpoint with media, it's a whole new channel we have to pay attention to. What does that do to research? What does advertising do to advertising? This creator economy is exploding as well. So our channels are becoming more and more fragmented. What does it do to how we tell stories? What if we use that technology like to write a script? For data, right and we're delivering that is as You know an animated show to folks. That's cool stuff, right? It's scary and weird as all this is there's other stuff like that. That's really cool. There was another one notebook LM video overview for Google Play. So it's not just, it can create a fake podcast, which it was. You can actually create really complex presentations of complex data sources now. What does that do to how we deliver information, right?

Susan Griffin: Results, new tools. You know, my, my, my like, wow, that's really interesting from this week was actually around, All of the text analytics, all the conversational AI tools, all the online qual tools claim that they can operate in many, many languages, 90 languages, 55 languages, but there is a language that has emerged and it is called algo speak. And the New York Times had an article about a Harvard-trained linguist named Adam Aleksik, who just wrote a book about, now, what's algo-speak? Well, it turns out algo-speak is what Gen Z has been popularizing amongst themselves in social media that has spawned words in the lexicon like skibbity, and jalulu, and riz. And there's actually a guy guide online for parents to learn the meaning of this. Now, Gen Z is a population that is notoriously hard to get to do online service, but they're doing stuff in social media and they're speaking that language. Now, if I'm in fraud detection and I say I can eliminate gibberish, I can look at completions that have gibberish because I have AI and it can speak all and it can detect, but if they see skibbity. Right. And Riz.

Lenny Murphy: Yeah.

Susan Griffin: And, and actually for our audience, Riz is what Gen Z uses as slang for charisma. So I told Lenny this morning and he told me I couldn't say this, but I think that Lenny is the personification of Riz charisma in the market research industry. He says no, but I think he's just being overly humble. So, man, you got Riz, you ate Riz.

Lenny Murphy: That's another Algo speak. Like Ritz, did you say eat Ritz, like Ritz crackers?

Susan Griffin: Yes, I will deal with that. That's not, that's not, no, that's, that's, that's a scabity. But what I find to be fascinating about this is, are the large language models being trained on Algo speak? You can actually read Adam's book that he just published on Amazon just for fun, but really not for fun. Because the issue is that things are very dynamic. And how consumers express themselves is dynamic. And this population that is currently very, very young is going to age very, And if, and they speak, their slang that they identify, I mean, I'm still struggling with awesome.

Lenny Murphy: I mean, you know.

Susan Griffin: I know, dude. Dude.

Lenny Murphy: Dude.

Susan Griffin: We're dating ourselves. Yeah. But, but I just, I just find this stuff to have implications for AI and implications for research that we may find silly and funny, but actually it's like, oh man. Yeah.

Lenny Murphy: Well, let's, let's bring that back with the, so there are a couple others, uh, the race continues. Yeah. Uh, uh, opening, I suppose, release chat, GPT five today, right? Or whatever they said in August. Um, by the same time, the most recent one, uh, there was a great LinkedIn post that said opening AI needs to immediately recall the new agent mode, that it's not fully baked. And apparently, these things are released from the wild. It moves fast, breaks things, and puts it out there. And as early adopters tend to do, especially with technology, like, oh, well, let's put it through its paces. And they're discovering, oh, it wasn't supposed to be able to do this. But it does. And that's kind of scary. In a particular case, here's examples of the agents taking autonomous action in connected information and accounts that maybe people really didn't want to do, right? Executing sales through a linkage to your bank account and those types of things.

Susan Griffin: So we have to, it's just this weird point. And McKinsey just published a very specific industry vertical specific report on how AI is going to transform finance and banking and credit. Yes. Yes. The devil's in the details and moves fast and breaks things when it comes to my bank account. I don't think so.

Lenny Murphy: Absolutely and let's wrap it up with that right because we're starting on a little bit over but it's been if Karen was here we'd have her get out her horse right to beat the dead horse that I've got, Lenny.

Susan Griffin: I've got horses. Yeah, I've got horses. Anyway, go ahead.

Lenny Murphy: Go ahead. We are not in the traditional cycle anymore of early adoption, et cetera, et cetera. That was two years ago. And there is no going back to this, to a previous world. It is, we must adapt to this world. The signals are incredibly clear. That's what we're trying to do is to, you know, call out separate signals from the noise. And we must adapt. We should have adapted it yesterday, right? If you're not on this path of adaptation internally and strategically from a process standpoint, from a product standpoint, from a positioning standpoint, you know, et cetera, et cetera, there's no waiting. Anymore right that we are just we are in mid transformation and it's not the odd part about this is that we can see the outline slightly ahead but we don't see the outline a year from now because the pace of change is just too fast so all we can do is continue to adapt as we go the next models can be released next week it's gonna do something's really well, it's going to do some weird shit that we're going to go, what, what is that? And it's scary and whatever, and they're going to fix it. And then the next model is going to come out and it's going to do the same thing. And it doesn't matter because the adoption is still going to continue at a pace. And, we must adapt to the uncertainty ourselves, um, uh, in order to be successful in our mission of delivering certainty to clients, because the process is no longer the business, the process. So that's just the process.

Susan Griffin: And towards that end, there are no magic bullets relative to marketing. Again, your service on the basis of features and functions, I mean, we have to be very agile and we have to figure out ways of telling a differentiated story, again, based on trust, based on a variety of things. So yeah, buckle your seat. That's my favorite Betty Davis line of all times from the movie, All About Eve. Buckle your seat belts, boys. It's going to be a bumpy night.

Lenny Murphy: And on that note, what better way to end? And not a Betty Davis quote.

Susan Griffin: Exactly, exactly. Thanks for having me on, Lenny. It's always fun.

Lenny Murphy: Thanks for joining, Susan. And guys, next week, Karen will be back.

Susan Griffin: Aren't you glad?

Lenny Murphy: I miss her. I miss Karen's Riz.

Susan Griffin: Karen's got Riz. Oh, she defines Riz.

Lenny Murphy: Yes, but I love having the opportunity to talk to you and obviously to our listeners. Shout out, Karley, do we have a graphic for the GRIT survey?

Susan Griffin: Oh, yeah.

Lenny Murphy: Pull that up. If not, that's OK. The GRIT survey is live. All of the stuff we're talking about, we've retooled the survey in order to focus on this and try to understand, provide some certainty or at least some direction with new questions, et cetera, et cetera. Look online or in your email inbox. There's tons of links. Please take a few minutes to participate.

Susan Griffin: And for those people who are buyers and suppliers, definitely check out the buyer's guides and keep your eyes open for the next round.

Lenny Murphy: Yep, absolutely. All right. With that, we will say goodbye. Happy Friday. Everybody have a great weekend. We'll talk to you next week. Bye.

Links from the episode:

NIQ IPO Raises More Than $1bn

Knit Raises $16.1M Series A to Redefine Enterprise Research with Human + AI Insights

Polymarket Acquires CFTC-Licensed Exchange and Clearinghouse QCEX for $112 Million

Insights Association Publishes The State of U.S. Insights & Analytics Report

Displayr Unveils AI-Powered Research Agent

Voxpopme Unveils “Voxpopme Signals” to Deliver Proactive, AI-Powered Consumer Insights

Pureprofile unveils AI-powered Message Testing

ISO 20252 Draft Standard Released for Public Comment

Amazon Invests in ‘Netflix of AI’ Start-Up Fable, Which Launches Showrunner

What’s New in NotebookLM: Video Overviews and an Upgraded Studio

OpenAI Prepares to Launch GPT-5 in August

OpenAI Needs to Immediately Recall the New Agent Mode Feature in ChatGPT

When Agents Attack: How AI Collapses and Rebuilds Marketplace Moats

McKinsey Technology Trends Outlook 2025

McKinsey Sees AI Surge Boosting Consulting Amid Industry Slump

BCG Predicts AI to Drive 20% of 2024 Revenues, Doubling to 40% by 2026

Accenture Hits Record $4.2 Billion in Generative AI Sales

Microsoft Beats Expectations, Reveals Azure Revenue for the First Time — $75 Billion a Year

GenAI Apps Doubled Their Revenue, Grew to 1.7B Downloads in First Half of 2025

OpenAI Hits $12 Billion in Annualized Revenue

Meta's Vision for Personal Superintelligence

Raising the Success Rate of AI Deployment Across Industries

The Harvard-Educated Linguist Breaking Down ‘Skibidi’ and ‘Rizz’

The Future of Work Requires a New Kind of Leader, and a New Kind of Thinking

Banking on Gen AI in the Credit Business: The Route to Value Creation

How to Get Recommended by ChatGPT