← The AI Daily Brief: Artificial Intelligence News and Analysis
The AI Daily Brief: Artificial Intelligence News and Analysis
The AI ROI Surprise: Wharton Finds 75% of Enterprises Seeing Positive ROI from AI
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This podcast is sponsored by Google. Hey folks, I'm Amar, Product and Design lead at Google DeepMind. We just launched a revamped vibe coding experience in AI Studio that lets you mix and match AI capabilities to turn your ideas into reality faster than ever. Just describe your app and Gemini will automatically wire up the right models and APIs for you. And if you need a spark hit, I'm feeling lucky and we'll help you get started. Head to AI Studio Build to create your first app today on the AI Daily Brief, 3/4 of enterprises are already seeing a positive ROI from AI investment and before that in the headlines Anthropic projects profitability on 70 billion in revenue by 2028 the AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. Alright friends, quick announcements before we dive in. First of all, thank you to our sponsors Gemini, Superintelligent, Rovo, Robots and Pencils and Blitzy. To get an ad free version of the show, go to patreon.com aidaily brief and to learn more about sponsoring the show or job opportunities or anything else, visit us at aidailybrief AI. While you're there, you can also learn more about our AI ROI Benchmarking Study which is live at roisurvey AI right now. Welcome back to the AI Daily Brief Headlines edition. All the daily AI news you need in around five minutes. A new financial forecast from Anthropic suggests absolutely unrelenting growth for the leading AI labs. According to reporting from the Information, Anthropic expects to generate $70 billion in revenue and have positive cash flows of $17 billion in 2028. Now last month Reuters reported that Anthropic was on pace for 9 billion in ARR by the end of the year. Their report noted a revenue target between 20 and 26 billion had been set for 2026. Digging into line items, Anthropic expects API revenue to reach 3.8 billion this year, more than doubling the 1.8 billion most recently forecast by OpenAI. Claude code itself is now generating a billion dollars in annualized revenue, which is more than double its pace from July. Now. For many, the report is a big validation for Anthropic strategy of pursuing foundation models, the application layer and direct partnerships with enterprise customers all at the same time. Anthropic assigned a number of large partnerships in recent months, including org wide deployments for Deloitte and Cognizant for hundreds of thousands of seats. On another front, the numbers suggest that Anthropic might have a big fundraising round coming soon. Their last fundraising was completed in September and valued the company at 170 billion. Sources suggest the next round would target evaluation between 300 and 400 billion. Now, to the extent we can extrapolate this level of growth to the sector in general, it's certainly a positive sign for AI being a boom rather than a bubble OpenAI reported 13 billion in ARR in October, but Sam Altman recently said the figure is now, well, more than that. He hinted that reaching 100 billion in revenue is a realistic forecast for 2027, shuffling up that timeline substantially. Besides stratospheric growth, Anthropic's numbers also suggest that their business model has a clear path forward towards probability. There's been a huge amount of hand wringing about AI being unprofitable, but Anthropic disclosed they're on pace to reach 50% gross profit margin this year and 77% by 2028. The company is forecasting 2027 is the year they flip into positive free cash flow for the first time. Now, given how tied up the performance of these companies is with the broader stock market, it's worth noting that AI stocks are having a bit of a shaky week as investors pull back on fears of the AI bubble bursting. Back on Tuesday, AI stocks led a 2% fall in the Nasdaq, which frankly had so many different causes, it's very hard to sort out exactly what the catalyst was. You could point to ongoing government shutdown, trade uncertainty or deteriorating conditions in the real economy as driving the movement. At an event on Tuesday, Goldman Sachs CEO David Solomon said, when you have these cycles, things can run for a period of time, but there are things that will change sentiment and will create drawdowns or change the perspective on the growth trajectory, and none of us are smart enough to see them until they actually occur. Morgan Stanley CEO Ted Pick had a similar view, commenting that we should quote, welcome the possibility that there would be drawdowns, 10% to 15% drawdowns that are not driven by some sort of macro cliff effect. Still, many are expecting a macro cliff and a total collapse of AI stocks that mirrors the end of the dot com bubble, despite all the evidence of all the ways that it's different. And while Wednesday saw a stabilization for AI stocks, the balance of risks has clearly shifted. Andrew Schlossberg, the CEO of Invesco, said, there is some point where we will be probably closer to a correction than we are to a 10% or 20% rise up from here. One of the interesting stock moves this week was Pinterest, with investors seemingly running out of patience with AI hype. The stock fell by 21% on Wednesday after guidance came in weaker than expected. Pinterest also warned of softer ad spending linked to tariffs. Yet during the same earnings report, CEO Bill Reddy said, our investments in AI and product innovation are paying off. We've become a leader in visual search and have effectively turned our platform into an AI powered shopping assistant for 600 million consumers. Continuing the theme we saw with big tech earnings last week, investors seem to no longer care about claims that AI adoption is paying off. They want to see real ROI falling to the bottom line now. One reason for the fallen sentiment is that Michael Burry is looking for his next big short. Burry famously made $100 million by shorting housing bonds during the financial crisis and was later depicted by Christian Bale in the film the Big Short. I've spoken before about how I think that movie itself almost single handedly made it so a generation of traders would rather call everything a bubble every single time than actually try to engage with the fundamentals. But here we are. On Monday night, Burry revealed that his hedge fund, Scion Asset Management, is short the AI bubble via a billion dollars in put options on Palantir and Nvidia. That's roughly 80% of the value of his fund concentrated in those bearish bets. The disclosure came two weeks ahead of the deadline, so Burry clearly wanted to spark a narrative. Palantir CEO Alex Karp fanned the discussion in an interview with CNBC on Wednesday morning, saying, when I hear short sellers attacking what I believe is clearly the most important software company in the world, it's super triggering. Every time they short us, we are just tripling down on getting better numbers in part to make them poorer. The two companies he's shorting are the ones making all the money, which is super weird. The idea that chips and ontology is what you want to short is batshit crazy. Jensen Huang also pushed back on Burry's positioning. Speaking with Sky News in the uk, he rejected the idea of an AI bubble, saying, we're a long ways away from that. I really think this is the beginning of the buildout and we're seeing a platform shift from the traditional way of doing computing to artificial intelligence. When something is profitable, the suppliers want to make more of it. That's the reason the AI buildout is accelerating, because AI is now so productive, so profitable and used by so many people. Now, while many are latching on to Burry's trade as a surefire sign the bubble is bursting. Others noted that he isn't always a reliable signal. The Short Bear posted. I respect Burry. However, let's remember it took two to three years from the moment he started shorting until the collapse. It is also worth noting that Burry called for crashes in 2015-2017-2019-2020, 2021 and 2023. As Peter Mallouk pointed out at the beginning of October, The S&P 500 is up 71% and has hit 88 all time highs since Michael Burry said sell back in 2023. It's also worth keeping in mind that Burry isn't shorting the market with a billion dollars of his own money. Investors put their money with Burry's hedge fund specifically because of his reputation for shorting bubbles. The point is, he wouldn't be doing his job if he wasn't shorting the likes of Palantir and Nvidia at some point. Still, markets around AI are getting more interesting. Deutsche bank is considering shorting AI stocks as a way to hedge their exposure to AI data centers. The German bank has extended billions of dollars in loans to data center projects, with one executive stating that they've bet big on the theme. Now, high level conversations are underway on how the bank can hedge. Their exposure options include buying default protection on some of the debt using derivatives called synthetic risk transfers or SRTs. They're also reportedly looking to simply short a basket of stocks associated with AI. Deutsche has primarily lent to hyperscalers like Amazon, Microsoft and Google, but they're increasingly going down the stack and lending to smaller NEO clouds as well. Now, part of what this is reflective of is a changing of the phase for the AI buildout. Until now, AI infrastructure has largely been cash flowed by the hyperscalers, but the size of the buildout increasingly will require debt financing to continue. Speaking with the information this week, BlackRock's global head of tech, Tony Kim, said there is no doubt that with the trillions of dollars of capex required for, AI, companies will need to tap into debt markets to fund this expansion. For his part, Kim believes this is a necessity to move forward. Commenting Tech companies will have to shed their aversion to leverage now. For his part, Kim thinks that because these companies are so unlevered right now, there's a lot of room to run with that, but this is certainly something to keep an eye on. We'll close out today with two stories related to Perplexity. First, Snap has signed a huge deal to integrate Perplexity into their platform the deal will see perplexity paying 400 million in cash and equity for the ability to use Snapchat as a distribution channel. A revenue sharing agreement will kick in next year. While Snapchat might be behind TikTok and Instagram, it still has almost half a billion daily active users. Perplexity will be integrated into the chat function and according to a press release, the aim is to deliver clear conversational answers drawn from verifiable sources all within Snapchat. Snap CEO Evan Spiegel said, our goal is to make AI more personal, social and fun, woven into the fabric of your friendships, snaps and conversations. Now, Snap, generally speaking, is at a crossroads, becoming closer to the other social media platforms with features like stories and public content feeds. They've also made a big push into advertising, with ad revenue surging 8% last quarter. While many wondered if Snap's young audience was a good fit for Perplexity, markets liked the deal and Snap stock was up 25% in aftermarket trading following the announcement. In a slightly tougher story for Perplexity, Amazon is suing them over their data scraping practices. On Tuesday, Amazon filed a lawsuit against Perplexity in an attempt to block Perplexity's agents from accessing their e commerce platform. Amazon reportedly laid out their complaints in a cease and desist last Friday. They claim that Perplexity's web crawlers failed to identify themselves as associated with an AI agent. Perplexity fired back this week in a blog post called Bullying is not Innovation. They wrote, for the last 50 years, software has been a tool, like a wrench in the hands of the user. But with the rise of agentic AI, software is also becoming labor, an assistant, an employee, an agent. The law is clear that large corporations have no right to stop you from owning wrenches. Today, Amazon announced it does not believe in your right to hire labor to have an assistant or an employee acting on your behalf. This isn't a reasonable legal position. It's a bully tactic to scare disruptive companies like Perplexity out of making life better for people. Amazon noted that third party agents from other companies identify themselves as such, writing in a response blog post, we think it's fairly straightforward that third party applications that offer to make purchases on behalf of customers from other businesses should operate openly and respect service provider decisions, whether or not to participate. They took it a little further in their lawsuit, writing, no different than any other intruder, Perplexity is not allowed to go where it has been expressly told it cannot. That Perplexity's trespass involves code rather than a lockpick makes it no less unlawful. Now the dust up is interesting, of course, not as some psychodrama between two tech companies, but is a preview of a broader fight around agentic shopping. Multiple labs are preparing to let agents loose on this year's Black Friday sales, but Amazon, as the largest e commerce platform, can currently shut everyone down with the flick of a switch. So chalk this up as a skirmish in a larger battle. For now though, that is going to do it for today's headlines. Next up, the main episode. Today's episode is brought to you by superintelligent. Now for those of you who don't know who are new here, maybe Super Intelligent is actually my company. We started it because every single company we talk to, all the enterprises out there are trying to figure out what AI can do for them. But most of the advice is super generic, not specific to your company. So what we do is we map your AI and agent opportunities by deploying voice agents to interview your teams about how work works now and how your people would like it to work in the future. The result is an AI action map with high potential ROI use cases and specific change management needs. Basically everything you need to go actually deliver AI value. Go to BeSuper AI to learn more. Meet Rovo, your AI powered teammate Rovo unleashes the potential of your team with AI powered search, chat and agents or build your own agent with studio. Rovo is powered by your organization's knowledge and lives on Atlassian's trusted and secure platform, so it's always working in the context of your work. Connect Rovo to your favorite SaaS app so no knowledge gets left behind. 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Plus with delivery centers across the us, Canada, Europe and Latin America, clients get local expertise and global scale. For AI that delivers progress, not promises, visit robotsandpencils.com aidaily Brief this episode is brought to you by Blitzi, the enterprise autonomous software development platform with infinite code context. Blitzi uses thousands of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code. Enterprise engineering leaders start every development sprint with the Blitzi platform, bringing in their development requirements. The blitzi platform provides a plan, then generates and pre compiles code for each task. Blitzi delivers 80% plus of the development work autonomously while providing a guide for the final 20% of human development work required to complete the sprint. Public Companies are achieving a 5x engineering velocity increase when incorporating Blitzi as their pre IDE development tool, pairing it with their coding pilot of choice. To bring an AI native SDLC into their org, visit blitzi.com and press get a demo to learn how Blitzi transforms your SDLC from AI Assisted to AI Native welcome back to the AI Daily Brief. If you are looking for a way of understanding where the general sentiment around AI is right now, look no further than the difference in reception to two studies from Ivy League universities that have come out over the last six months. We spent a huge portion of this summer and frankly continue to have to deal with that inane MIT air quotes study, if you can even call it that, that, interviewed 52 executives seemingly chosen for convenience of being around and looked at public earning statements for companies explicitly saying that they were seeing new profitability from their AI initiatives, all on the way to proclaiming that 95% of AI initiatives were failing. That statistic has been included in so many analyses and media pieces and blog posts and pitches, it is honestly, at this point, much to my chagrin, probably the most quoted, most ubiquitous study around AI shared this year. Meanwhile, a longitudinal study from Wharton on its third year with a much more comprehensive and verifiable academic methodology that surveyed around 800 enterprise leaders across a variety of functions has gotten barely any attention at all. Now, ironically, it is probably the case that when it comes to the longevity of AI, it is probably a net better thing for the industry that everyone latched onto the skeptical study as opposed to the optimistic study because it shows that despite all the bubble screamers, the narrative at least is very, very far from overheated right now. But in any case, when we move beyond the meta interpretations of where the AI discourse is, there is still a ton of really valuable stuff in this Wharton study that very much deserves a review and that is what we are doing today. As I said, this is the third annual Wharton GBK study of Enterprise Gen AI adoption and the story by and large is of an AI moving mainstream adoption becoming ubiquitous and integrated into the fabric of everyday life and ROI not only beginning to be measured, but also showing up the big theme one let's call everyday AI or AI moving from curiosity to core workflow. The theme is basically that Gen AI is now part of daily work, not an experiment. 82% of enterprise leaders now use Genai and almost half of decision makers 46% report using Genai Daily. That's up 17 percentage points versus last year. Knowledge and familiarity with Genai has risen. 77% report being at least somewhat familiar with Genai. Although there are slight laggards in marketing and management, we're starting to see functional adoption patterns where key business tasks are seeing higher Gen AI adoption Marketing content creation is up. Internal support and help desk is up. Document and meeting summarization is up. Presentation and report creation is up. Idea generation and brainstorming is up. Data analysis and analytics are up. And while there are lots of different benefits of AI, half of the top 10 gen AI use cases directly boost employee productivity. Top 10 use cases in 2025 are in order Data analysis and analytics, document and meeting summarization, document and proposal editing and writing, Presentation and report creation, idea generation and brainstorming, Marketing content creation, customer service and support, Email generation, internal support and help desk and sales content creation. Interestingly though, AI agents are starting to emerge. 58% of enterprises are testing AI agents, mostly among this cohort for process automation, analytics and workflow orchestration. And yet really, the big story of this survey is not about usage but about roi. Enterprises are very clearly shifting from use to proof. First of all, ROI measurement has become standard. 72% of companies are formally tracking their Gen AI ROI. The functions that lead in structured ROI tracking, including HR at 84% and finance at 80%, maybe the biggest headline or statistic of the whole report. 3/4 of enterprises report positive ROI. 74% overall are seeing either moderately positive or significantly positive ROI, with smaller firms between 50 and 2 billion in revenue seeing more ROI so far than enterprises with 2 billion-plus in annual revenue. Now we have seen over the past couple of months just a slew of indications that ROI is coming faster than people in many cases would have thought. And the perception of ROI continues to rise. So what are going to be the big blockers? Well, as we've seen over and over again, it's going to be more about people than employees. While 89% of respondents said that AI enhanced skills, 43% still fear skill decline as well. And while overall, the vast majority of decision makers are saying they feel more positive about gen AI over the past year, they are also still cautious as well. What all of this sets up very clearly in my mind is a 2026 where the key theme of the year is going to be not only about measuring ROI and demonstrating roi, but about understanding how it compares. We are now up over 700 use cases that have been contributed to the AI ROI benchmarking study and getting just a huge degree of granular information around where the benefits are really coming. Part of why I wanted to launch this study is that I want to start to have benchmarks where organizations can understand A what type of benefit they're supposed to get out of AI and B, whether the results that they're seeing are actually commensurate with their peers and colleagues. On the first part, as much as we talk about AI and productivity, there are actually a variety of different types of benefits and impact that AI can have. There's time savings, cost savings, new capabilities, enhanced throughput and output, reduced risk, improved decision making, enhanced revenue, new revenue lines, and understanding which use cases are relevant for which of those different types of benefits is really important. Second, because we're all floating in new territory, we don't need to just know whether AI is improving things, but whether it's improving things in a way that's commensurate with what we would expect. For example, if a particular deployment is helping your team increase marketing throughput by 10%, that might seem great until you find out that for all of your competitors, it's increasing marketing output by an average of 20%. Look, ultimately, the ROI survey is just one very small part of what is going to be a big theme for all of next year. But still, if you want access to all the information that we find from that, go to roisurvey AI Contribute and you will get the results when they are completed towards the end of this month. Bringing it back to roundup on Wharton. What do they think about what 2026 will bring? The study authors write 2026 could be the turn from accountable acceleration to performance at scale, where today's ROI metrics, playbooks and guardrails let enterprises rewire core workflows, deploy agentic systems, and reallocate budgets towards proven returns. They point out that four out of five see Genai investments paying off in about two to three years, 88% anticipate increasing Genai budgets in the next 12 months. And everyone is trying to figure out how to make or get the talent that's required for this new era. So that is the story of the Wharton study. Optimism, excitement and ROI coming into focus for now. That's going to do it for today's AI Daily Brief. Appreciate you listening as always. And until next time, peace. Sam.