AI: The Fourth Industrial Revolution
Three-plus years into the release of ChatGPT, this AI revolution—encompassing everything from cloud computing, data centers, and robotics in addition to the staggering progression of analytics, content creation, and inference—just keeps gaining momentum. Investment in the AI build-out is one way to measure it. Spending by just five hyperscalers (Alphabet, Amazon, Meta, Microsoft, and Oracle) is expected to reach an estimated $741 billion in 2026, according to this recent Wall Street Journal article. That’s a whopping 75% higher than in 2025. Of course, the financing needs to come from somewhere, and corporations have embarked on a borrowing spree in order to fund this AI race. Alphabet, a cash machine of a company, turned to the global debt market this year to raise tens of billions of dollars (including the issuance of a rare 100-year bond) for hardware and data center funding. Altogether, these five hyperscalers have solicited $159 billion of debt worldwide so far in 2026, compared to $108 billion for the entirety of 2025 and $17 billion in 2024.
These companies, and plenty of others, are in an industrial race for AI dominance and supremacy. And the pace is breathtaking. As such, it’s not always feasible to stop and consider every dollar spent before throwing it at this burgeoning industry to secure footholds and purchase market share. But some investors harbor growing concerns about the massive borrowing and spending; occasionally, they step back, take a hard look at future profit potential, and become jittery, as we saw during late June’s market sell-off—and last week’s one-day $890 billion market rout of the Magnificent 7.
Which brings us to our larger point. Any particular investor, big or small, only has so much capital to allocate. Case in point: Retail investors sold stakes in stalwarts like Apple and AMD in early June in order to allocate money to the SpaceX IPO. We can only imagine what might play out in similar veins when rivals OpenAI and Anthropic go public. IFI’s advice: take time to examine the patents before placing bets on which companies might win the AI race. For companies that are technically innovative, patents can act as a market signal to investors—and provide that extra bit of competitive edge. Patents can raise red flags or provide assurances, reducing uncertainty. Patents protect current revenue and foretell future growth. Here is the latest examination of AI patents, something we’ve been keeping our eye on since the introduction of ChatGPT in late 2022. AI has developed rapidly since then. Today we’re all talking about agentic and inference AI. But we’ve also started to see growing indications in the patents of symbolic and semantic AI, as well as AGI (Artificial General Intelligence). We’ll have to get back to you on those concepts at some point. Regardless of the future directions AI takes, the expansion of this revolution will be limitless.
Highlights from our research below:
Patents in the AI Universe
In the few years since generative AI burst upon the scene, the entire AI landscape has progressed in both sweeping and narrow ways. The AI advancement has generated both complexity and depth as new phases of AI form from previous achievements. Of the 209,518 patent applications in artificial intelligence filed around the globe in 2025, some 23% of those are directly related to generative AI—the kind of AI that uses large language models on massive pools of data in response to human triggers. These sophisticated algorithms then create original text, images, video, and other human-like output.
Within the AI sphere, 9% of those are taken up by yet another variety that has companies and investors looking for onramps: agentic AI, which performs even more independently than GenAI. AI agents can ideate, determine, and execute complex workflows to achieve tasks. The agentic imprint is small but increasing, taking up 9% of global applications this year compared to 5% from our previous study.
For just U.S. applications in 2025, the agentic AI frenzy is more pronounced. GenAI covers 16% of the AI patent domain, about the same as before. But agentic AI now comprises 15%, up from just 7% in IFI’s previous findings.
AI Patents Powering Up
The past decade has seen a surge of invention around artificial intelligence. Global AI grants have risen at a compound annual rate of 35%, while applications have grown by 29%. For U.S. patents, the trendline was quite steep from 2018 to 2023, but has leveled off over the past couple years in both grants and applications. Generative AI has posted strong and steady patent gains on both fronts though. Around the world, grants have expanded by 54% on an annual basis, while applications escalated 44%. Growth is remarkable too in the U.S. with GenAI grants progressing 31% as applications increased 29%. As for agentic AI? The curve also rises: global grants turned up 42%, with applications up 43%. In the U.S., grants rose 27%, as applications climbed 22%. Drilling down a little more on applications, notice how sharp the incline is in the last two years, a signal of intense interest in protecting inventions around agentic technology. Worldwide, agentic applications rocketed 59% over the past two years, while in the U.S., they’ve risen by 40%.
Essential Technologies
One of the biggest misinterpretations around inventions is that a patent protects something that is utterly new. But inventions stand on the shoulders of previous inventions, which are, in turn, buttressed by patent technologies that have been cultivated for decades. Generative AI has certainly bowled the world over. But the underlying technologies upon which GenAI inventions are built have been hanging around for some time now: machine learning, image analysis, information retrieval, handling natural language data. It’s just that they all came together in a way that created this new technological wonder. The patent subclass key to GenAI comes from the field of life sciences; it’s called “computing arrangements based on biological models,” and has appeared on IFI CLAIMS’ annual list of Top 10 Fastest Growing Technologies for a number of years as GenAI was quietly developing behind the scenes. GenAI patents rely heavily on this class because it makes use of deep learning (especially convolutional neural networks), a technology furthering computing that mimics human reasoning.
Agentic AI leans heavily on many of the same technologies; in fact “computing arrangements based on biological models” looms even larger in this area. “Administration; management” is an essential technology for agentic AI—perhaps for all the office work our AI agents are expected to perform for us humans?
Qualified AI Applicants
When it comes to the overall area of artificial intelligence, Samsung is the company that applied for the most patents worldwide in 2025 with 2162 filings, followed by Huawei (1822) and Google (1672). When looking at just U.S. filings, Samsung also places first with 682 applications, followed by Google (671), and Microsoft (585). Other stalwarts at the top include IBM (460), Nvidia (401), and Qualcomm (300).
Narrowing the field to generative AI patent applications, Google takes top billing both globally and in the U.S., compared to Samsung’s fifth-place showing in both listings. Microsoft and Nvidia are the other companies inventing robustly in this space. One Google patent filed last year in GenAI is this one for a generative model routing system. As for Microsoft, the company put forth this patent in 2025 for a fine-tuning simulator for machine learning models. And here is an Nvidia patent for generating a response in an AI system after an image or video input. All are still pending.
Google is also a prime patenter in the field of agentic AI. But it doesn’t take the top spot. That goes to Nvidia, the Wall Street darling of the AI boom, which is first in both global and U.S. agentic patents, with 225 and 128 applications, respectively. Google comes in second worldwide and third stateside (222 and 91), while Microsoft rounds out the top three in both categories (217 and 112). This recent application from Nvidia for an interactive agent platform is still pending. Here’s another pending patent, this time from Google for a conversational AI agent. And this Microsoft patent uses agents to determine whether or not certain data is malicious. It was granted this past April.
GenAI Focus Groups
Innovations filling the spaces of image, speech, text, and video creation take center stage for generative AI patents. Any company competing in GenAI is surely looking to protect in each of these areas, but some companies are emphasizing these inventions more than others. IFI plotted the top five companies in each of these technologies in the chart below. It’s important to note, however, that these companies may have patents in the other areas; they just didn’t make the top five.
Nvidia places most of the company’s patent weight in the areas of image and video, as seen in this pending application for video scene understanding. Microsoft leads in text, on display in this application from 2025 for prompt generation for a machine learning model. And Google is out ahead in speech. Here is a Google patent for entry points for large language model assistants. Just one company in the chart leans into all four bases: Google. Nvidia throws its GenAI patent weight into three of the zones, while Microsoft occupies two of them.
Intel, a former laggard that has been on a market tear for the past year, doesn’t nearly have the breadth or scope in GenAI focus as other big players on the field. Nonetheless, the giant chipmaker is in the game. Like Nvidia, Intel specializes its GenAI patent strategies in image, but it still has plenty of recovery ahead. Don’t tell that to Intel’s stock price though; it’s up more than 350% over the past year and may still have a lot of runway to go as the company continues to regain its footing.
The AI Contenders
AI is a giant sandbox, and every company seems to be playing in it. But we wanted to take a look at just a handful for the moment—the ones garnering more of the attention in the business press and from investors. Not surprisingly, big company competitors Google, Microsoft, and Nvidia are way out in front when it comes to filing patents globally and in the U.S. But disruptors OpenAI and Anthropic, both on the cusp of going public sometime in the near future, are also protecting their inventions. Anthropic filed 8 patents worldwide and 7 with the USPTO in 2025. One such example is this one for training agents to automate tasks, filed last year. For its part, OpenAI is also racking up patents, with 35 around the world and 27 in the U.S. This is quite a jump from some two years ago when IFI found fewer than five patents from the pioneering GenAI company. Last year, the company pledged to use its patents only for defensive purposes: “We recognize the role that patents play in the technology landscape, and commit to using our patents in a way that supports innovation,” according to OpenAI’s statement on its approach to patents. Here is a recent OpenAI application for a generative response system using chain-of-thought logic.
Deepseek, a Chinese model that shook the stock market in early 2025—Nvidia’s stock price suffered a $600 billion loss in one day—when its LLM performed as well as ChatGPT at a fraction of the investment, doesn’t hold any patents related to its technology. (Deepseek is preparing to list in Shanghai sometime next year.) And xAI (a subsidiary of SpaceX, which recently debuted in a historic public offering that minted Elon Musk as the world’s first trillionaire), holds no patents that we could find. This is not a shock. Musk has long preferred open source and trade secrets over patents, which he sees as a tool to suppress progress. “Patents are for the weak,” he famously told Jay Leno a few years ago during a tour of Starbase in Texas. “They’re used like landmines in warfare,” he went on. “They don’t actually help advance things; they just stop others from following you.”
AI Titans and Their Technologies
The Cooperative Patent Classification (CPC) codes are hierarchical tags that label and organize technologies contained within an invention. Monitoring the increase (or decrease) in CPC codes overall or by company can signal to the market what technologies are gaining traction or attracting interest—and which entities are in hot pursuit of them.
In breaking down our narrow group of companies by the main technologies that are contained in their AI patents, we can see, for instance, that computing arrangements based on biological models (G06N 3) is, by far, the main covered area by most of the top AI applicants. Within this class, Google patents specifically on neural networks (G06N 3/08) and combinations of networks (G06N 3/045). Google’s other top classifications include language technologies (G06F 40) and machine learning (G06N 20). One of Nvidia’s top technology areas is image and video recognition, particularly pattern recognition through combinations of neural networks (G06V 10/82).
ChatGPT creator OpenAI is mostly pursuing language technologies (G06F 40), specifically translation of natural language (G06F 40/40) and lexical analysis (G06F 40/284). Its rival Anthropic also covers lexical analysis and most recently, image and video recognition using neural networks (same as Wall Street superstar Nvidia).
As for Chinese companies Alibaba and Baidu? Apart from covering the main AI area (G06N 3) they are mostly focused on information retrieval (G06F 16).
Why is this important to understand? Studying the direction of CPC codes provides a layer of nuance when trying to predict industry trends or eventual winners in a market. Much has been written about the rivalry between OpenAI and Anthropic—and that competition will continue to play out in the years to come. Both companies are expected to go public soon and their financials will be scrutinized and compared as heavily as their LLM models. As investors decide how to allocate their dollars between all these AI companies, seeing where their CPC codes overlap and diverge can help identify the company’s potential strengths and weaknesses and pinpoint their most important technological hotbeds.
This analysis was produced in partnership with IALE Tecnología.
AI is rapidly enlarging. For this iteration of our research, IFI and IALE used an extensive list of keywords and CPC codes to define specific technologies for both generative AI and agentic AI. For more information on our methodology and how patent data can enhance corporate and investment due diligence, please contact us.
