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GPT-5.4’s Hands-On Business Value: Five Features for Practical AI Use
OpenAI’s latest model, GPT-5.4, is not merely another incremental update. For those overseeing organizational AI adoption, several newly demonstrated features in GPT-5.4 translate directly into improved business outcomes. Here’s a granular look at what matters from the hands-on review, with detailed examples tailored for business value.
AI Market Landscape 2026: User Numbers, Revenue, and Enterprise Adoption
In March 2026, the “big four” – OpenAI, Google, Microsoft, and Anthropic – are contesting a multi-faceted AI race. OpenAI currently stands as the leader in consumer adoption with 900 million weekly active users, and an annualized revenue rate of $25 billion. Google, by contrast, boasts 750 million monthly active users and 8 million paid enterprise seats, positioning itself as a full-stack leader with deep integration across its ecosystem.
Microsoft, despite its early investment in enterprise AI solutions like Copilot, registers 15 million paid Copilot seats and claims 90% Fortune 500 penetration. However, Microsoft's advantage lies in its embedded workflow orchestration and security governance, more than standalone AI capabilities. Anthropic’s reported $20 billion annual recurring revenue suggests high monetization per user, emphasizing premium intelligence integration, but with far fewer users compared to OpenAI and Google.
AI Workflow Integration: Beyond Chatbots to Agentic Systems
The conversational chatbot era has faded. Today’s AI landscape revolves around agentic systems capable of executing complex enterprise workflows with greater accuracy and customization. Enterprise adoption is shifting from simple prompt-based chatbots towards platforms that deliver actionable, enterprise-ready outputs. The potential winner in 2026 will be determined less by headline model benchmarks and more by how effectively a provider enables seamless, agentic integration of business data to deliver enterprise-grade results.
Recent developments include every major player launching agentic products—platforms that execute multi-step tasks, integrate natively with desktop workflows, and automate routine business operations. Capabilities such as computer use, spreadsheet modeling, and data integrations are now setting the leader apart; for instance, OpenAI’s GPT-5.4 model excels in both transparency and general intelligence for daily enterprise operations.
Multimodal Capabilities: Google’s Full-Stack Advantage
Google’s competitive edge lies in its multimodal AI ecosystem. As the only major provider with native video input alongside text, image, and audio handling, Google leverages unique training resources from platforms like YouTube and offers robotics capabilities through Gemini. Deep integration across Gmail, Google Workspace, Android, Chrome, and YouTube, complemented by a new workspace overhaul, transforms Google Drive into an AI-powered, citable knowledge base for business users.
Enterprise customers utilize Gemini’s omnipresence within Google Workspace to synthesize, access, and analyze data from anywhere within their organization.
Model Benchmarking and Real-World Outcomes: Specific Strengths by Provider
OpenAI’s GPT-5.4 model leads scientific benchmarks and delivers an 83% win/tie rate in blind expert tasks, while Google’s Gemini models are dominating spreadsheet editing and creative tasks in Workspace environments. Anthropic’s Opus and Sonnet models excel in complex reasoning and technical applications, with the infrastructure-focused approach capturing high-value customers in financial workflows, coding agents, and model-agnostic deployments.
Microsoft’s advantage remains in its position as the enterprise control plane, integrating AI by default across Word, Excel, Teams, and Outlook. The learning curve for permissions and governance remains high, affecting ease of adoption, yet recent product management driven by the highest corporate leadership signals increased attention to usability and value.
Agent Coding War: The New Deciding Factor
The agent-coding segment is pivotal. Adoption of tools like Claude Code and OpenAI Codex is influencing measurable ROI at enterprise scale, with coding as the first operational area where AI delivers direct, quantifiable productivity gains. Anthropic’s Claude Code is responsible for 4% of all GitHub commits and $2.5 billion in annual revenue within months of launch, demonstrating high adoption in developer and technical workflows. Meanwhile, OpenAI Codex, although slower, reportedly holds a higher performance bar, crucial for teams requiring specialized system integrations.
Infrastructure spending is sharply increasing, with OpenAI, Google, Microsoft, and Anthropic all committing multi-billion dollar CapEx in pursuit of building proprietary data centers and accelerating processing capacity. The speed at which each company deploys such infrastructure is directly tied to their ability to maintain market leadership.
Strategic Recommendations: Modular Deployment and Data Integration
The evolving AI contest isn’t monolithic. Leadership rotates by workflow and quarter, and reliance on a single vendor brings risk as AI models and platforms can change without warning, affecting productivity and process reliability. Modular workflows and contingency planning for rapid migration between providers are essential.
Optimal deployment strategies suggest leveraging OpenAI for breadth of function, Anthropic for deep technical integrations, Google for scalability and multimodal tasks, and Microsoft for governance and embedded workflow orchestration. Mixing providers for specialized tasks, rather than depending on one platform, can boost resilience and unlock targeted value from each player’s strengths.
Conclusion: Translating AI Competition into Business Value
In 2026, AI’s value for business is determined not by flashy model benchmarks, but by actionable workflow integration and enterprise-ready system design. OpenAI leads consumer adoption, Microsoft dominates enterprise orchestration, Google delivers unmatched multimodal capabilities, and Anthropic maximizes technical efficiency for high-value tasks.
The next step for business leaders is redesigning enterprise processes around agentic systems and continuously matching platforms to specific operational needs, always with contingency plans for rapid provider switching. This nuanced approach positions organizations to harness the evolving strengths across the AI landscape and ensures sustained competitive advantage through precise, modular adoption.
Topics Covered in This Episode:
- AI Race 2026: OpenAI, Microsoft, Google, Anthropic
- Chatbot Era Ending: Rise of Agentic Systems
- OpenAI vs Google vs Anthropic User Stats
- Large Language Model Benchmark Comparisons
- Enterprise AI Adoption Trends
- Agentic Workflow Automation: Business Impacts
- Microsoft Copilot and Governance Features
- Anthropic Claude’s Premium Intelligence Integration
- AI Coding Tools: Codex vs Claude Code
- Strategic Equity Investments: Microsoft & Google
- Multimodal AI Ecosystem: Google Gemini
- CapEx Spending: AI Infrastructure Expansion
- Consumer vs Enterprise AI Market Leaders
- Future Model Capabilities and Agentic Data Integration
Episode Transcript
Jordan Wilson [00:00:17]:
What company will win the AI race in 2026? Yeah. It's a lot of fun for AI geeks like you and me to argue this and to follow the benchmarks and literally every single week or every other week argue about the new next best model. But the answer, obviously, to that question is much more nuanced than a single company. And the answers, obviously, hold extreme value for today's business owners and decision makers. That's because you've probably already, and if not, you will soon, look at the big four in the face and say, hey. Which company should our organization be using when it comes to AI? Microsoft, Infropic, Google, or OpenAI? So on today's show, we're gonna be giving you some of the answers, but let me just get straight to the big picture here. Three years ago, one company controlled AI in OpenAI, but that era is over because now you have Microsoft, Infropic, Google, and OpenAI all competing for the same thing. Two things mainly, the mind share.
Jordan Wilson [00:01:24]:
Right? That's the, the total number of consumers on the platform and then the enterprise dollars. Right? How quickly, can you get those consumers over to start using it on the business side? But I think the 2026 winner of the AI race will actually come down to the workflow and how easy and how accurate it is to bring in in an agentic manner your company's data and for that system to deliver enterprise ready outputs. And it's not necessarily gonna be the best model. Whoever makes it is gonna be the one that wins the AI race. So on today's show, we're gonna go over what the big four are actually competing for in 2026, why the chatbot era ended, and what comes next, where today's large language models from each company excel and where they struggle. And last but not least, I am gonna give you my kind of hot take, but, you know, educated, opinion, we'll say that, on who is going to win what AI race from the big four companies. Alright. I hope you're excited.
Jordan Wilson [00:02:30]:
Well, I am. So if you're new here, welcome to Everyday AI in our start here series. This is the essential podcast series to both learn the AI basics and to double down on your knowledge. So whether you are the key decision maker in your company or you're brand new getting into AI, well, the start here series is for you. So if you haven't already, please go to starthereseries.com. That is going to give you free access to our inner circle community. And in there, in the start here series space, you can go and listen to and read the entire start here series. I believe we're already on volume 12.
Jordan Wilson [00:03:09]:
Alright. And if you miss our last episode, and yes, it does help to listen to them in order. They're not super long. Right? Most of them are between twenty five and thirty five minutes. And if you listen on two x, they're even faster. Alright? But in our last episode, we covered measuring AI ROI, why you're doing it wrong, and the seven steps to fix it. It. My gosh.
Jordan Wilson [00:03:29]:
Listen to that episode. Put it into practice. But today, on our start here series volume 12, we're going over the state of the AI race. Who's gonna win? So let's get into it and talk about what's changed. And, well, to put it simply, the chatbot era is very gone. It's done. Right? Bless up. I'd say even toward the 2025, a lot of enterprise decision makers were still looking at AI like a chatbot.
Jordan Wilson [00:04:01]:
It's not like that anymore. In my opinion, I think GPT five four, thinking from OpenAI is kind of the first, daily driver model that you can look at across the entire business spectrum and be like, yes. We now have probably, right, depending on how educated you are. Right? In terms of, large language models and knowing how they work. Right? And, yes, there's other great models, Gemini three one pro, Claude Opus four six. But I think we're probably now finally in March 2026 at the time where you can have a single model that is generally intelligent enough and transparent enough to be like, okay. We can move pretty much all of our day to day operations under here if we have the right experts kind of driving this thing. And, it took a while, to get the the harnessing and the tool use around these chatbots to turn it into something more.
Jordan Wilson [00:04:56]:
Right? I've been calling it in one of our earlier, shows on the start here series was about the AI operating system. So make sure to go back and listen to that. But that's essentially where we've, kind of transitioned from away from AI chatbots, right, to now these are agentic systems that do work. Right? They deliver full outputs. And every major player of the big four has shipped a huge agentic product in the last ninety days. So let's go over some of the stats, some of the facts, some of the figures. Stock numbers. Okay? OpenAI, 900,000,000 weekly active users.
Jordan Wilson [00:05:36]:
Alright? Also, this is as of March 2026. Right? So if you're listening to this, I don't know, in November or December 2026, You know, obviously, a lot of this, the models, the numbers have changed, but I'm gonna guess, I have a pretty good, thumb on the pulse on these things. But I'm gonna guess my overall, vibe and, advice you on each of these models will still probably hold true by the end of the year if I'm being honest. But for the most part, OpenAI is the leader when it comes to the number of users. They have become synonymous. ChatGPT is AI. Right? You ask someone that isn't using AI every single day, it'd be like, hey. Have you ever used AI? They're gonna say, oh, you mean chat g p t? It is synonymous with AI.
Jordan Wilson [00:06:22]:
And that's because they have 900,000,000 weekly active users. And the last revenue estimate we got was $25,000,000,000 of annualized revenue. So this is the consumer default, but what most people don't realize, they're also the enterprise default as well just because they've done a great job at converting those individual weekly active users on the consumer side, onto the business plans and the enterprise plans. Google is all over the place in maybe a good and bad way. Right? So the latest reports that we got were 750,000,000 monthly active users. Okay? Different from the 900,000,000 weekly active users that we got from OpenAI, and 8,000,000 paid enterprise seats. And I'd say top to bottom, they're the full stack leader. Alright? That doesn't mean they're the best.
Jordan Wilson [00:07:15]:
Right? But, I mean, they have Gemini everywhere. Right? In AI mode, so there's a good chance that you're using Gemini all the time and you don't even know it. I believe it's 3.1 flashlight that powers, the AI overviews and the AI mode. It's it's coming out everywhere. Right? Especially if you use Gmail, if you use Google Workspace. We'll get into more of that later. But, from everywhere from, Vertex using Gemini in their Google AI Studio, it's legit everywhere. Alright.
Jordan Wilson [00:07:47]:
Microsoft. It's it's weird to say that Microsoft might be in third place when it comes to the enterprise even though they had an unfair head start. Right? They launched Microsoft Copilot in 2023. They were the first, enterprise product for AI. Right? And according to reports, you're seeing about 15,000,000 paid co pilot seats. And according to, those reports, 90% of Fortune five hundred penetration. But they are kind of the default, enterprise control plane. Right? Most companies I talk to, right, when they hire us for front end AI strategy or to train their teams on chat GPT or something like that.
Jordan Wilson [00:08:31]:
Most of all or mostly they're they're coming from Copilot. Right? And and what we've seen, I think a lot more recently, is companies that well, they're still gonna use Copilot because the company pays for it, but they're trying to move some of their operations in there. And I know Microsoft is doing a lot of work to counteract that and some of their more recent moves that we're gonna talk about later. Anthropic, last but not least, reportedly $20,000,000,000 in annual record, annual recurring revenue. So not too far behind, OpenAI has reported 25,000,000,000. So even though they're much, much smaller, they are doing a good job at least on the revenue side. We haven't seen a lot in terms of total users from Anthropic. I think it's because, you know, OpenAI and Anthropic are both reportedly going, going public in 2026 with an IPO.
Jordan Wilson [00:09:23]:
I would assume Anthropic keeps their, their overall enterprise numbers under wraps because it is very small. And I'm just gonna go ahead and say this now. Right? People always accuse me of being anti anthropic. No. I'm not. I love anthropic. I have a, you know, $200 a month anthropic max plan. Right? There's obviously great applications for anthropic.
Jordan Wilson [00:09:43]:
Right? But there's a lot of, information out there that's bad and wrong. Right? So I'm just here to set the record straight. I currently have also yeah. I currently have no, you know, no sponsorships or advertising with any of these four. Although, I have, we have advertised with Google and Microsoft in the past on this channel. Right? There's a lot of bad information floating out there. This is Anthropic is winning the, you you know, the enterprise race from ramp in Menlo. They're not.
Jordan Wilson [00:10:10]:
It's not even close yet. They're they're in fourth place. But what they've done a great job, they've built great products, fantastic models, and I would assume, right, they probably have the highest revenue per user because they don't have a lot of users. Right there. They're nowhere in the, you know, 900,000,000 or 750,000,000 range that OpenAI and Google are, but great models, great products, and like I said, they're probably doing the best in terms of revenue per user, which is an important metric to look at. So kind of the, for our livestream audience, you can kind of see the little graph here. If you're You're listening on the podcast. Nothing overly visual on today's show, but you can always watch the video version on our website at youreverydayai.com.
Jordan Wilson [00:10:52]:
And, essentially, there's a lot of overlapping races, because, ultimately, I don't think that there technically is one race because you can lose the, you know, the consumer mind share, like, Infropic is, and you can still win the overall race. Alright? But if I had to kind of, you know, peg each one, what is the lane that they're, running in? So OpenAI, I'd say they're con they're the consumer default. Right? They are synonymous with AI. They are AI. Right? Even though they didn't create it. Right? You gotta tip your cap to, to to Google there and the, the inventors of the transformer. But they are so far ahead of everyone else. I think, personally, obviously, the the numbers tell it on the consumer side.
Jordan Wilson [00:11:41]:
The numbers, seem to tell it also on the enterprise side. And when it comes to, the models, the benchmarks. Right? Their newest models, there as well. Full stack multimodal, that's Google. I think Google is in such a great position in the long run because they are the only one multimodal by default, accepts video inputs. They have probably the best source of training for the future of AI like AGI, when it comes to YouTube. Right? And, great on the robotics model side with their Gemini robotics as well. So, Google is, like I said, all over the place in a good and bad way, but I think they are primed to really excel in the long run.
Jordan Wilson [00:12:23]:
And I think they finally brought some updates to where people probably use Gemini a lot and had some bad experiences, which is in the workspace, and we're gonna get to that in a little bit. Bit. Then Microsoft, they are I'm just gonna say the enterprise control plane. Right. That's been historically dominated by Microsoft. Right? Because they are the only ones well, they are the actual operating system of the computer. Until Apple ever decides they wanna do AI, which they're not in the conversation, right, when you fire up your Windows PC, Copilot's there. Right? ChatGPT is not living on your desktop when you fire it up by default.
Jordan Wilson [00:13:05]:
Google Gemini is it. Anthropic Claude is it. It is Microsoft Copilot. However, their models are powered by OpenAI and Anthropic, but that's kind of their their lane. It is embedded workflow orchestration with the tools and the software, that your company already uses huge on the identity and security governance side, obviously. And then in Tropic, I'll say they are the premium intelligence layer. So, I don't think in the long run, they're gonna have the best models. Although, right now, their current models, Opus four six and SONNET four six are some of the best that there are.
Jordan Wilson [00:13:42]:
I don't think in the long run, I I I do think that's gonna be a Google Open AI conversation, but they have done a better job than probably everyone else at just kind of the premium intelligence integration. Right? So everything from coding agents and how you can use quad code in different places to their recent, you know, plugins that have literally shook the stock market. Right skills, you know, popularizing skills and MCP. So, they are kind of the the company that's inserting, you know, kind of their intelligence layer in more places in the high value financial workflows and model agnostic cloud deployments. So a little bit more in some of the strengths for each. Right? OpenAI, let's get to them. They're the default. They're the, you know, no matter who you're comparing against, whether you're currently a Copilot, you're saying Copilot versus, Chatt GPT.
Jordan Wilson [00:14:38]:
If your company is a Google, workspace company, you're saying, okay. Are we Gemini or are we Chatt GPT? Or maybe one of your teams really took off with Claude and you were using it early on, it's Claude versus ChatGPT. Right? ChatGPT and OpenAI, they're not gonna be out of the conversation for any anything, I don't think, in 2026 at least. Today, best model, GPT five four, thinking, GPT five four pro. Scientific benchmark side, they're winning. Everything from the traditional, kind of, you know, MMLU type. Right? The ACTs for the AIs to now the the coding, the agentic harnessing, the, computer use. So some of these, areas from a benchmark perspective that used to belong to Anthropic.
Jordan Wilson [00:15:27]:
Yeah. It's it's open AI. Right? I could obviously change next week. Right? Because anytime one of the big three come out with a step up model, a decimal model. Right? So going from a three one to a three two or a four six to a four seven or a 54 to a 55. Right? Right? Anytime that happens, the the the benchmark and the sentiment changes, but OpenAI is never going to be out of it. Right? They've got some huge CapEx, deals, right, more than a trillion dollars between SoftBank, Nvidia, and Amazon, sending huge deals all the time. And when it comes to getting work done, you have to talk about the GDP bow.
Jordan Wilson [00:16:02]:
Right? 83% win tie rate. So, in blind taste test, so to speak, producing work, yeah, GBT five four is better or ties expert humans 83% of the time, best in the business. Alright. Google, like I said, they're the multimodal full stack. Alright? And they are all over the place. But according to Google, more than a 120,000 enterprises, are using, their, their technology across the stack. More than 8,000,000 paid Geminis enterprise seats and, their year over year generative AI revenue is up 400%. So, yeah, it was the 2024 that Google just woke up and chose violence.
Jordan Wilson [00:16:50]:
So at least the last, like, fifteen months, I think Google has been the winner. Right? And then I think in terms of, you know, OpenAI versus Anthropic, they've been competing. But, you know, obviously, Google got off to a very bad start when it came to their Bard. Right? The the Bard model wasn't good. They came out with some marketing that kind of showed some capabilities of Google Bard that weren't exactly there. And I think that really set them back by probably more than a year. But what they're doing on the multimodal and creative side is absolutely bonkers. I mean, when you talk about VO 3.1, again, these models might have changed by the time you listen, y'all.
Jordan Wilson [00:17:27]:
I understand that. But when you talk about their video models in VO, their nano bananas, you you know, image generation model, what it can do with infographics and slide generation, right on the Gemini robotics side. I mean, their footprint is larger and wider than even Microsoft's. Even though Microsoft has that huge head start up just living in the operating system. Alright. Speaking of Microsoft, like I said, they are the enterprise control plane. Alright. So we've seen reports more than 15,000,000 paid, Microsoft three sixty five co pilot seats.
Jordan Wilson [00:18:03]:
And they did show a a 160% year over year growth. And they did just recently launch a new offering. So we'll see, what that does on the revenue side. It's called the m three sixty five e seven bundle. It's kind of a higher tier, with some more inclusions than your basic Microsoft three sixty five Copilot seat, as well as the Copilot co work, which we're gonna talk here in a little bit. But, last but not least, you have anthropic. And I do think that they've come to dominate that premium execution layer. So essentially, inserting their intelligence in different ways because I think that they've been developer friendly and developer focused from the beginning.
Jordan Wilson [00:18:47]:
So when it comes to large enterprises, a lot of their teams that, maybe were helping make the decisions were maybe more comfortable, with some of the earlier, Opus and SONNET models. Obviously, they were kind of first to the game, with Claude Code even though, yes, Microsoft, you you know, Microsoft GitHub Copilot has been around for a very long time. But when it came, from a, perspective of an agentic command line interface coding tool that came out to a desktop program, even though I think that was still Microsoft GitHub Copilot should have, could have been that tool. But for whatever reason, it was anthropic, and that's helped them get extremely, great traction. Yeah. So reports we've seen anywhere from 14 to $20,000,000,000 on the annualized run rate, run rate. Same thing, investing a lot on the CapEx building their own actually, and the product footprint, everything from Claude Code, which is on itself a unicorn. Right? Reportedly $2,500,000,000 in revenue just from Claude Code.
Jordan Wilson [00:19:49]:
They have the new code work, sorry, co work, which we'll talk about in the Microsoft side as well, which is, you know, allowing you to do your work, on your desktop. So it's kinda like cloud code for non developers. The new quad marketplace, the office add ins, the plugins, right, and traffic over the past probably, three months has been their best three month run to date. Alright. And then we have to talk about equity investments because that's where this race gets not tricky, but the answer is nuance because some of these companies might not be competing in areas where they could, well, because they already have their money and their equity in someone that's winning. So as an example, as of October, when OpenAI, converted its operating structure from a nonprofit to a PBC or a public benefits corporation, Well, micro Microsoft is the single largest shareholder of the OpenAI Group, PBC with a 27% stake in the company. They yeah. They are the technically, the largest single shareholder in the PBC.
Jordan Wilson [00:21:00]:
Also, Microsoft has a total investment commitment of $5,000,000,000 in anthropics. So Microsoft has a lot to gain even if they are losing consumers. Right? If they have, you know, if they're shedding copilot licenses and those people are ultimately going to Chad GBT, or to Anthropic, well, maybe it's a dime out of the left hand but a dollar in the right hand or vice versa. Right? But ultimately, as long as they're not losing to Google, Microsoft is winning. I think a lot of people are overlooking that. Google also big investments. So and reportedly, about a 14 or to 15% ownership stake in anthropic. So where Microsoft has a very large, stake in OpenAI, Google, parent company Alphabet, has a pretty big slice of that anthropic pie, which from a revenue only side is growing faster, according to reports than anyone else's revenue pie.
Jordan Wilson [00:22:06]:
Alright. So let's get back to OpenAI and tell the story a little bit that way. So Chattopty went from zero to 900,000,000 weekly active users in just over three years, which going from truly zero to nearly a billion. Right? Probably by the time most people are listening to this, it's gonna be a billion weekly active users. It's never been done. It is just straight up hockey stick to the moon growth. Also, revenue finished with $2,000,000,000 in 2023. Now very quickly up to, that reported $25,000,000,000 annualized revenue rate.
Jordan Wilson [00:22:44]:
And it's not just consumers. Yes. The overwhelming majority of those 900,000,000 are free users using ChatGPT, but they do have 50,000,000 consumer subscribers and 9,000,000 different businesses that now depend and use and use the platform. And I'd say, kinda my take here, chat g b t is the easiest to use. It is. Alright. I kinda wish they had their codex, their new coding platform. I kinda wish it worked inside of Chad GPT whether you're using it on the web, or the app.
Jordan Wilson [00:23:15]:
That's the thing. Right? I think Anthropic has done a great job with their desktop app for Mac as an example. You know, having the chat, co work, and code all under one roof. So I do think that was maybe a miss there from OpenAI, not just kind of, integrating codex a little bit more tightly into chat g p t specifically when it comes to the desktop app, but it is still the easiest to use by far. Right. Anthropic, yes. It's a little it can be a little confusing, but I'd say anthropic is probably the second easiest to use. But the UI, UX, ease of use, right, if if your grandparent or parents are using AI, they're probably using chat g p t because it is the easiest.
Jordan Wilson [00:23:59]:
And like I said, it's become synonymous. And the new model I think is, really, really, really good. Right? I did a recent show on it so you can go check that out if you want to. But, I mean, it introduced native computer use, spreadsheet modeling, and direct financial data integrations. The trade off, well, the cost can get high. Right? Especially on the enterprise side, you know, they don't publicly disclose those but, you know, we hear anything from, you know, 50 to $70 per enterprise seat. Right? So a little more than, Microsoft's baseline, enterprise seat licensing. Obviously, they're new $99.
Jordan Wilson [00:24:36]:
It OpenAI's enterprise one will come under that. But, you know, the the trade off there, and I've been saying this, OpenAI, I don't think cares about being profitable. Right? They've updated their profitability projections to say they might not be profitable until 2030. So, essentially, you've had, you know, Infropic and OpenAI, the two kind of quote, unquote AI startups take a very different approach. OpenAI has said we care about users, and they're winning that game by far. And I think Infropic has cared probably more about profitability. Again, we don't know the price per user, but my strong assumption is entropic is crushing everyone else when it comes to revenue per user because I don't think they have a lot of users, but I do know they have a ton of revenue. Alright.
Jordan Wilson [00:25:21]:
So their biggest strength might also be their biggest weakness. Right? OpenAI kind of had their infamous code red where, they kind of realized that they maybe they were lagging behind a little bit on the model side. So I do think over the last month or two, they've really, corrected course on that. But, yeah, a lot of people argue that maybe OpenAI, is a little too distracted. Right? So they have their video product. You you know, it's it's seems like they're trying to compete maybe with Google and Microsoft and Apple all at the same time. Could they do it? Maybe. Right? Whereas, Anthropic, its closest competitor is not doing any of that.
Jordan Wilson [00:26:01]:
They're not doing images like OpenAI is. They're not doing video. Right? OpenAI reportedly going into consumer hardware with devices maybe, you know, early twenty twenty seven. But the consumer focus maybe, has slowed down some of their model progress, some of their research because they're having to devote a lot of their compute to things like this Soarer app. Right? Things like that. But, they're spending reportedly more than anyone else, but at least they are winning on the overall numbers game. Alright. Anthropic, I think is the best for high stakes, high value technical work.
Jordan Wilson [00:26:42]:
Emphasis on technical because I do think if you're looking at overall, general work productivity, I still do think that OpenAI and Google are probably the best for that. But Claude is a leader on complex reasoning, long documents, and economically valuable knowledge task. And they do say that eight of the fortune 10 are cloud customers, and there's 500 plus companies that are spending over, a million dollars annually. So, the product surface is very narrow. Anthropic, you can make the argument is a company that is extremely, focused on doing one thing very, very well, and that's having very capable models, that have a product market fit in usually niche areas. But now they are starting to broaden out. I think toward the 2025, again, anthropic has shocked me because they were really just geared toward the software developments, the the the devs, right, highly technical financial tasks, and they have really branched out. I think Claude Cowork, you know, was one of those things, but really pushing skills, pushing the plugins.
Jordan Wilson [00:27:54]:
I do think that they're broadening out from maybe, you know, the the the technical, model of choice to now they're probably, you know, starting to win consumers over, as they've branched out a little bit. And I think Cloud Code is one of the reasons why. Cloud Code, really good. Personally, I do like codex better, but QuadCode has been a massive hit. You could make the argument. It could be a top five, you know, AI product of all time. I mean, just QuadCode in, you know, less than six months, came into $2,500,000,000 in annual recurring revenue. And that's, right now, 4% of all GitHub commits, which is a pretty big amount for a product that is this new.
Jordan Wilson [00:28:41]:
Also, they just launched the their quad marketplace, with six different partners where you can kind of, companies using that can commit their spend, to some of their partners, quad partners in their, kind of plug in ecosystem. Alright. Microsoft. Microsoft, I'd hate to say it. They are the safe, kind of, you could say old school AI. Right? They're the safe AI, the safe bet. And and one of the reasons is, well, it's the one that's approved by most enterprises out of the box because it is literally built into the ecosystem. It is built into the operating system.
Jordan Wilson [00:29:20]:
So it's already embedded, according to reports. More than 90% of Fortune 500 companies are using Microsoft three sixty five Copilot, daily. A big new shift. Well, Microsoft announced Copilot Cowork powered by anthropics co work technology. And, it is gonna be probably a slow rollout over the next few quarters until the, the the wider business world has their hands on it. But this does bring that multi step task, you you know, where essentially it's just doing your work. Right? If you've used Claude CoWork, it has access to all your files on your computer. It can produce documents.
Jordan Wilson [00:30:03]:
It can use a terminal. It can power a power and control a browser. Right? So it is very much like an intern or a junior researcher. It can access all your files, create files, use a computer, use a terminal, use control a browser. Right? All these same things that a human can. So I do think that this co work, kind of movement now that, Microsoft, is is starting to productize as well is one worth paying attention to. Alright. Microsoft, their biggest advantage is one that no one else can really replicate.
Jordan Wilson [00:30:34]:
That's AI by default. Right? Like I said, even if people maybe don't want it, they're gonna see Copilot inside of Word, Excel, Teams, and Outlook. Although, I do think it's gotten much much better. I think Microsoft, probably had some of the same early problems as Google when, you know, they were slapping their copilot in all of their, you know, all of their office products, and it wouldn't always work very well. I think they've gotten that tied up in the last, probably six months. And now that they have kind of the, the agentic options inside of their office products even more so. And we'll see what happens with this new $99, per seat per, for the e seven frontier suite That kind of bundles, AI security and governments and as well as, Copilot co work. But the biggest setback for Microsoft, it is the learning permissions and governance curve.
Jordan Wilson [00:31:28]:
It is way higher than the other three. That's because, well, it's there by default. So it is it's kinda like a a running joke that Microsoft Copilot could be the best AI out there if anyone could figure out how to use it. I do know that that's something Microsoft is tackling. We've seen reports that their CEO, Sunny Nadella, is essentially, you know, putting in some work as a product manager on Copilot, which is very rare for the CEO of a multitrillion dollar, market cap company to start working on product, but that's what we've seen. So I am actually, rather bullish long term, on Microsoft Copilot for that very reason. Right? When you have the CEO, rolling up their sleeves to say, hey. This isn't working.
Jordan Wilson [00:32:16]:
We've gotta change this. I think that's the way to go. Alright. And then last but not least, Google, the most powerful multimodal AI ecosystem on Earth. So like we said, 750,000,000 monthly Gemini users, with 8,000,000 of those reportedly paid seats and huge year over year growth. And they are the only major provider with native video input, which is big. I still people still aren't using this, and it's such a cheat code, alongside text image and audio handling. And there's deep integration literally everywhere.
Jordan Wilson [00:32:47]:
So across search, Android, Chrome, YouTube, Drive, Docs, Sheet. Right? So if you are a, Gemini sorry. A Google workspace organization, well, it's gotten a lot better. Again, early, you you know, mid twenty twenty four when you started to see, you you know, Gemini rollout in beta across workspace, it wasn't good. There's actually some instances where it was downright bad. Right? I remember doing a couple videos on our YouTube channel just feeling like, yo, this doesn't work. Now it's the best. Right, an update they actually had this week.
Jordan Wilson [00:33:20]:
So in March 2026. Right? Like certain benchmarks, like, you know, spreadsheet editing. Now they're the best. But it's all it is all over the place. So again, kind of a good and bad thing, but you have your Gemini. There's a different version of Gemini for business and enterprise, notebook LM, Gemini and Vertex AI studio. It's everywhere. But one of the newer things is the new workspace overhaul.
Jordan Wilson [00:33:44]:
So this fills, you you know, it puts Gemini in everywhere in, Gmail, in Drive, in Docs. Right. So you can essentially talk to Gemini now anywhere inside Google Workspace. Whereas before, it wasn't quite as easy. So now we can just, you know, synthesize and understand your files, emails from anywhere. Right? So you can essentially leverage and tap into, your entire Google workspace ecosystem no matter where you are within workspace. And now Google Drive is also being kind of repositioned, as like a rag database. Right? It's an active citable AI knowledge base across your entire history inside Google Workspace.
Jordan Wilson [00:34:27]:
Now shifting away a little bit here, I think what we have to pay attention to is the agent coding war. I think that is maybe where this thing starts to get decided. Because coding is the first use case where AI created a concretely measurable ROI at enterprise scale. And gains in coding and computer use, I think, do spill over into nontechnical applications in large language models. Because, I mean, we've heard from both anthropic, we've heard now from OpenAI as well that, their models are writing their future models. Right? Which is also kind of scary. Right? We have this self learning and recursive AI that's writing itself. Right? But once that happens, that means that then those yeah.
Jordan Wilson [00:35:13]:
I know this sounds weird, but then those models can write hundreds or thousands of specialized models that are then just better at all these other tasks maybe on the nontechnical side. So you do have to pay attention to the agent race, and the computer use race, because those are things that are ultimately going to impact the nontechnical everyday business work that most knowledge workers are doing. I'd say right now, Claude Code is leading in adoption, and it's trending. But codex, I think, is probably the highest on the market. Along with the new g p d five four models inside codex, I do think it's yes. It's way slower, but my personal opinion of burning billions of tokens in codex in in quad code, I'm maxed out on all those. I I I am way more bullish and, I I do think that it has the higher, bar right now codex does. And then, obviously, you have Microsoft GitHub Copilot that is kinda like one of the OGs when it comes to, you know, AI coding assistance.
Jordan Wilson [00:36:12]:
And Google, again, both great and confusing. Google's kind of all over the place here. They have everything from Firebase to Jules to Code Assist, to the Gemini CLI to anti gravity. Right? So Gemini, obviously, on the coating side has a lot of offering. But I do think the coating winner could set the template for every agentic category that follows. And also the infrastructure side. Right? You have to see where these companies are investing, on CapEx. So OpenAI, reportedly, yeah, $110,000,000,000, funding round targeting 600,000,000,000 in total compute spend through 2030.
Jordan Wilson [00:36:51]:
Yeah. They're saying we're spending a ton of money on compute, and that's one of the reasons they're saying they're not gonna be profitable. You know, or not as profitable as quickly as maybe some of their other competitors. Google, spending up to a $185,000,000,000 in CapEx. Microsoft, 37,000,000,000, in quarter four twenty twenty five alone. Anthropic has launched a massive 50 bought $50,000,000,000 investment initiative to own and cons, construct their own AI data centers in The US. So, that's technically kind of separate. Right? But the faster that these companies can get up these CapEx, you know, AI data centers, right, that's gonna help them get ahead in in the kind of the day to day in the week to week AI race.
Jordan Wilson [00:37:36]:
Alright. So as we wrap here, how do you navigate this? Alright. I gave you a very quick I know it's 37 minutes in here. I gave you a very quick recap of where we've been over the last three years and the pros and the cons of where, these big four companies are. And, yeah, it's the big four companies. Maybe Meta will reenter the discussion. Perplexity is not really its own, model maker. Right? Because I'm sure people are gonna be like, oh, what about, you know, Amazon, AWS.
Jordan Wilson [00:38:04]:
Right? There's second tier right now that could change. Right? But right now, it is essentially the three, frontier AI providers and Microsoft that leverages both of them and Microsoft making their own models. But for the most part, stop buying one vendor for it for everything. You know, leadership changes by workload and by the quarter. Even if you have a great workflow right now with one of the big four, you need to be working on your one b plan because I can't say this enough. Oftentimes, these companies are going to change something in their big model, and they might not even announce it. It might not even be a decimal point change. It just might be an under the hood change, and things could go off the rails for your company.
Jordan Wilson [00:38:44]:
You always need to be building modularly. You need to redesign processes for agents first that take action, not just chat bots waiting to be asked. So that's a big, kind of change management, piece for enterprise leaders out there. And you need to match the platform to the problem. Right? So as an example, maybe right now it's open AI for breadth, Claude for depth, Google for scale, Microsoft for governance, whatever it is. There's no problem in having, you know, two different. Although I do think it is best to move as many of your day to day knowledge work processes into an AI operating system. But I think for specialized tasks and for certain departments, I think it's okay to have a secondary, you know, tool or a secondary company.
Jordan Wilson [00:39:26]:
So let's end it here. Who's gonna win the AI race? Alright. I'm gonna break it down because like I said, there is no one race. It's many different races, but I think there's a couple there's three big races, I think, that are being run. Consumer, enterprise, and models. Consumer, OpenAI. No one else is gonna touch them. Google is starting to close the gap.
Jordan Wilson [00:39:47]:
OpenAI is so far ahead. I don't see them losing that lead anytime soon. Enterprise, I do think as strange as this sounds, this has always been Microsoft's, battle to lose. And I think that from 2023 to 2025, they were losing. So I think right now, it's Microsoft versus OpenAI. I do think Google is trending. Google has a fantastic, Gemini for business and Gemini for enterprise product, but I don't think anyone knows about it. Right? People think it's just the gemini.google.com.
Jordan Wilson [00:40:21]:
No. That's the consumer version. I think Google, could start to dominate in that category. You you know, at least when you talk about nontechnical front end users. Right? Obviously, they have everything on the Vertex side, the AI studio. But yeah. It anthropic, not in the picture. Sorry.
Jordan Wilson [00:40:38]:
They're they're not in enterprise, player when it comes to enterprise total enterprise users. Alright. And then model capabilities, that's a toss-up. Right? Obviously, Infratix models top tier, top of the class, open AI's new releases, you you know, in certain areas, great benchmarks as well. And then Google. I think I've said it before. Google at any time because of the mass, training data that they have. I think anytime they can come out with a new Gemini three two, Gemini three three, and be the best model in the world.
Jordan Wilson [00:41:12]:
So I don't think, although we always are watching that race, the model race, I think it's the least important of all three because it's becoming more and more important. The harnessing, the tool, the tool use. And like I said, it's not about who has the best model. It's about who helps you bring your data and all of your, day to day workflows agentically into the into the picture. That's what it's ultimately about. Alright. I hope this one was helpful as we went over the state of the AI race. Again, this is part of our start here series.
Jordan Wilson [00:41:48]:
So whether you are brand new to AI or you just want to double down on your knowledge, please go to starthereseries.com and go sign up, and go listen to the entire series there. So thank you for tuning in. Hope to see you back tomorrow and every day for more everyday AI. Thanks y'all.