THESE AI STOCKS COULD 10X THIS DECADE

[00:00:00]Artificial intelligence is changing our world [music] very quickly. Um you probably see it every day in small ways.

[00:00:07]It [music] might be in the phone in your pocket. It could be in the shows that are recommended to you online, but this is just the beginning of a very big change. [music] Over the next 10 years, AI is expected to grow much, much more.

[00:00:20]>> [music] >> It will become a fundamental part of almost every industry.

[00:00:25]Think about how the internet changed everything [music] 20 years ago. Experts believe AI could have an even bigger impact on our lives and on the global economy. This transformation presents [music] a major opportunity for long-term investors who can see the big picture.

[00:00:42]Many people are talking about AI right now.

[00:00:44]>> [music] >> The news is full of stories about new technologies and new companies. It can feel [music] exciting, but also very confusing. It is hard to know which companies will succeed and which will fail. [music] The stock market can go up and down very fast based on daily headlines.

[00:01:02]>> [music] >> This essay is not about short-term trading or chasing quick profits.

[00:01:07]Instead, [music] we are taking a much longer view.

[00:01:10]We will look 10 years into the future.

[00:01:13]We want to understand [music] which companies are building a strong foundation with AI that could lead to [music] significant growth over the next decade.

[00:01:22]This long-term perspective is very important for investing.

[00:01:25]A decade gives a company enough time to develop [music] new technology.

[00:01:29]It allows them to find customers and grow their business in a meaningful way.

[00:01:35]Short-term news [music] can be noisy and distracting. A company might have a bad quarter or a good one, but that does not always tell you about [music] its long-term potential.

[00:01:47]By focusing on a 10-year horizon, we can look past the daily noise. We can focus [music] on the fundamental strengths of a business, its strategy for using artificial intelligence, creating [music] lasting value for its customers, creating lasting value for its shareholders.

[00:02:05]So, how do [music] we find these potential winners?

[00:02:08]We need to look for companies that are not just using AI, but are making it [music] central to their business.

[00:02:15]This could be a company building the basic tools [music] for AI, like powerful computer chips, or it could be a company using AI to solve a very specific problem, like discovering new medicines.

[00:02:28]In this essay, we will explore a range [music] of companies across different sectors. Our goal is to provide a clear [music] and data-led countdown. This will help you understand the landscape of AI investing and think about how this powerful [music] technology might shape the market for years to come. To identify companies with strong long-term potential, we need a clear and consistent method. This is not about guessing or following [music] hype. Our approach is based entirely on data.

[00:02:59]Simple, [music] understandable criteria.

[00:03:02]We looked at hundreds of public companies involved in artificial intelligence.

[00:03:07]From that large group, we created a ranked list based on a few key factors.

[00:03:13]Our main goal is to be transparent about how we made these [music] choices.

[00:03:18]This will help you understand the reasoning behind each [music] company's position in our countdown. We believe that a good method helps to separate real opportunities [music] from temporary trends. Our analysis rests on three main pillars. First, [music] we examine the company's business model and its specific AI advantage. Is it creating the core technology, >> [music] >> or is it applying AI in a unique way?

[00:03:43]Second, we look at the size of the market it [music] is trying to serve.

[00:03:47]A large and growing market gives a company more room to expand. Third, we review [music] recent financial signals, revenue growth, research and development spending, profitability. We get this information from reliable [music] sources, official company filings with the SEC, reports from Bloomberg, The Wall Street Journal, industry analysis from firms like Gartner.

[00:04:12]For each company on our list, >> [music] >> we will present the information in a simple format.

[00:04:18]We'll explain what the company does and what makes its approach to AI special.

[00:04:23]We will provide [music] key data points to support our analysis.

[00:04:27]But we know that the future is never certain.

[00:04:30]That is why we will also discuss the potential risks for each company.

[00:04:35]What could go wrong?

[00:04:36]What challenges might they face?

[00:04:39]To make this more concrete, we will present two possible scenarios for the next 10 years. A bull scenario where [music] things go very well, a bear scenario where the company struggles.

[00:04:52]>> [music] >> This essay is written for a general audience. You do not need to be a financial expert or a data [music] scientist to understand it. We use plain language and avoid complicated jargon.

[00:05:03]The sentences are short and direct. Our aim is to be informative and neutral. We are not giving investment advice or telling [music] you to buy or sell any particular stock.

[00:05:15]Instead, we are providing a framework [music] and the data you need to do your own thinking.

[00:05:20]The goal is to empower you with knowledge so you can watch the AI sector with more confidence over the long term.

[00:05:26]>> [music] >> Table of contents, part two, act one, one.

[00:05:31]The AI infrastructure layer, building the digital brains. Two, the cloud kings, [music] running out the AI revolution. Three, the chip titan, Nvidia's unshakable moat. Before any company can create an exciting AI application, something else needs to exist first.

[00:05:51]>> [music] >> They need the basic tools and building blocks.

[00:05:55]This is the infrastructure layer of the AI economy.

[00:05:58]Think of it like the roads, bridges, and power plants of a physical city. [music] Without this foundation, nothing else can be built on top.

[00:06:07]In the world of artificial intelligence, this infrastructure consists of powerful [music] computer chips, massive data centers, and the complex software that makes it all work together.

[00:06:19]The companies that control this layer have an enormous [music] advantage. They are not just participating in the AI revolution, they are supplying the picks and shovels for it. They sell to other large technology firms, to small startups, and to companies in every [music] industry, healthcare, finance.

[00:06:38]This creates a very broad and stable customer base.

[00:06:42]As more [music] and more businesses adopt AI, the demand for this underlying infrastructure [music] naturally grows.

[00:06:49]This makes the companies in this space some of the earliest and biggest winners in the AI boom.

[00:06:55]Their growth is tied to the growth of the entire AI market, not just [music] one specific application or trend. This provides a powerful and resilient business model for the long term. The economic power of this layer is immense.

[00:07:10]According to market research [music] firm Gartner, the market for AI chips alone is projected to exceed $100 billion annually by 2027. [music] This is just one piece of the puzzle.

[00:07:24]When you add in the markets for cloud computing services, data storage, networking equipment, the total addressable market is worth trillions of dollars over the next decade. Companies that establish a dominant position here can capture a significant portion of that value. They benefit [music] from economies of scale, meaning it becomes cheaper for them to produce each additional [music] unit as they grow larger, making it very difficult for new competitors [music] to enter the market.

[00:07:55]This foundational layer is where the most intense competition [music] and innovation are happening right now.

[00:08:02]The leaders are investing tens of billions of dollars each year into research and development. [music] They are racing to create faster, more efficient chips and more powerful software platforms.

[00:08:14]These investments create a strong competitive moat, a kind of protective barrier around their business.

[00:08:21]For an investor looking at a 10-year horizon, understanding which companies are winning this foundational race is one of the most [music] important first steps.

[00:08:31]These are the giants on whose shoulders the rest of the AI world will stand for years to come. One of the biggest shifts in technology over the last decade has been the move to the cloud. [music] Instead of buying and managing their own physical servers, companies can now rent computing power from large providers.

[00:08:49]>> [music] >> The three dominant players in this market are Amazon Web Services, [music] Microsoft Azure, and Google Cloud.

[00:08:58]These companies are now at the center of the AI revolution.

[00:09:02]Developing advanced AI models requires a staggering amount of computational power.

[00:09:08]Most companies [music] cannot afford to build their own massive data centers, so they turn to the cloud kings who have already invested billions in building a global network of them. [music] The business model for these cloud providers is very powerful.

[00:09:23]They offer AI as a service.

[00:09:25]>> [music] >> Um this means that any developer or company can access top-tier AI tools and infrastructure [music] with just a credit card.

[00:09:34]They can rent access to the most advanced [music] AI chips and use pre-built software to create their own applications.

[00:09:41]Microsoft Azure, for example, has a close partnership with OpenAI, the creator of ChatGPT. [music] This allows Azure customers to easily use OpenAI's powerful models within their own products.

[00:09:54]The financial data shows just how big this business is.

[00:09:58]In its most recent fiscal year, Microsoft's [music] cloud division generated over $100 billion in revenue.

[00:10:05]Amazon's [music] AWS remains the market leader with revenues of over $90 billion annually.

[00:10:13]These are not small speculative businesses. They are established giants with a clear path to monetizing AI.

[00:10:21]The primary [music] risk for these companies is intense competition.

[00:10:25]They are constantly cutting prices. This price pressure could potentially squeeze their profit margins.

[00:10:31]>> [music] >> Another risk is regulation. However, their massive scale [music] and deep integration into the global economy provide a strong defense. For the next decade, they are poised to be the primary landlords of the AI-powered [music] digital world. When we talk about the hardware that powers artificial intelligence, [music] one name stands above all others, Nvidia. Um for years, the company was primarily known for making graphics processing units for video games. These chips were designed to render realistic 3D graphics, a task that runs many simple calculations in parallel.

[00:11:10]That parallel processing is exactly what's [music] needed to train large AI models.

[00:11:16]That gave Nvidia a massive head start in the AI hardware market. [music] Today, its advanced GPUs are the industry standard for building and [music] running sophisticated AI systems. Nvidia designs highly specialized [music] chips and sells them to a wide range of customers.

[00:11:34]Biggest clients, cloud providers, Amazon, Microsoft, Google. [music] Nvidia also sells to AI startups, research universities, and automotive companies developing [music] self-driving cars. The dominance shows up in its financials. Revenue more than tripled year-over-year in the latest quarter, [music] driven almost entirely by its data center segment. The company's key AI advantage is not just hardware, [music] but CUDA, its software ecosystem. CUDA lets developers unlock the full power of Nvidia GPUs for general purpose computing. Over 15 years, millions of developers and researchers learned CUDA.

[00:12:17]They built countless applications and scientific models on it. That creates an incredibly strong competitive moat.

[00:12:25]Even a slightly faster rival chip [music] would still face the huge task of convincing the AI community to switch platforms.

[00:12:34]Nvidia does face risks. Biggest [music] risk, dependency on a few very large customers. If a cloud giant builds chips in-house, [music] Google has begun doing this with TPUs, it could hit Nvidia's sales. Competitors like AMD [music] and Intel are pushing to catch up. For now, Nvidia's tech lead and CUDA make its position look very secure. It is [music] the undisputed king of the AI chip market. Beyond the foundational giants, a new class of companies is emerging.

[00:13:05]These are the specialists. They do not build the basic AI infrastructure.

[00:13:09]>> [music] >> Instead, they use AI to solve very specific high-value problems for businesses.

[00:13:17]One of the clearest leaders in this space is ServiceNow.

[00:13:21]The company [music] has built a powerful cloud-based platform that helps large organizations manage and automate their internal [music] workflows.

[00:13:29]This includes everything from IT support tickets, human resources [music] requests, to customer service management.

[00:13:36]For years, ServiceNow has been the digital plumbing that [music] keeps big companies running smoothly behind the scenes. Now, it is embedding AI into every corner of its platform.

[00:13:48]ServiceNow's business model is based on a subscription service.

[00:13:52]Companies pay an annual fee to use its Now [music] platform. This provides a stable and predictable stream of revenue.

[00:14:00]Its AI advantage comes [music] from its unique position inside its customers operations.

[00:14:07]By applying generative AI to this data, it can provide intelligent suggestions, automate repetitive tasks, [music] and predict future problems before they happen, making businesses more efficient. [music] The financial signals for ServiceNow are strong and consistent. The company [music] has a long track record of growing its revenue at over 20% per year, and it has maintained very high customer retention rates, often above 98%.

[00:14:37]The primary risk for ServiceNow is increased competition.

[00:14:41]Another risk is execution.

[00:14:43]Integrating complex [music] generative AI tools across a vast platform is a major technical challenge.

[00:14:51]For a 10-year bull scenario, ServiceNow becomes the essential AI operating system for the enterprise. [music] In a bear scenario, it loses ground to bigger rivals, and its growth [music] slows significantly. Some of the most complex organizations in the world, from government intelligence agencies to global manufacturing firms, are drowning in data.

[00:15:13]They collect vast [music] amounts of information, but they struggle to connect the dots.

[00:15:19]This is the problem that Palantir [music] Technologies was built to solve.

[00:15:23]Palantir provides a software platform that acts as a central operating system for an organization's data.

[00:15:30]This allows human analysts and decision-makers [music] to see patterns and connections that were previously invisible.

[00:15:38]Palantir's [music] business model involves selling its two main software platforms, Gotham, >> [music] >> which is used primarily by government clients, and Foundry, which is tailored for [music] large commercial enterprises.

[00:15:51]Palantir's AI edge is its ability to create a digital twin of [music] an entire organization.

[00:15:59]Its new artificial intelligence platform allows customers to [music] ask plain language questions and run simulations.

[00:16:08]The company's recent financial signals have shown a notable shift. Its commercial business [music] is now growing much faster.

[00:16:16]Palantir's US commercial revenue grew 40% year-over-year, driven by strong demand for its AIP.

[00:16:24]The biggest risk for Palantir has always been its controversial reputation.

[00:16:29]This can [music] make some commercial clients hesitant.

[00:16:33]Another challenge is the complexity and high cost of its platform, [music] which can lead to long sales cycles.

[00:16:40]For a 10-year bull scenario, Palantir's Foundry and AIP become [music] the default data operating system for the Fortune 500. In a bear scenario, its commercial push stalls, and it remains a niche government contractor, [music] facing competition.

[00:16:59]>> Section three, the healthcare AI innovator, Intuitive Surgical's robotic precision. Artificial [music] intelligence is not just about software and data centers. It is also about the physical world. Robotics is a field where AI is making a profound impact.

[00:17:16][music] Its da Surgical Systems are used by surgeons around the world to perform minimally invasive procedures [music] with greater precision and control than is possible with the human hand alone.

[00:17:29]Intuitive Surgical operates on [music] a razor and blades business model. It sells the daVinci systems, then it generates recurring [music] revenue by selling the proprietary instruments and accessories and from [music] service contracts. Its AI advantage is rooted in the immense amount of data it has collected. [music] With over 14 million procedures performed, it is now using AI to analyze this data [music] to provide surgeons with real-time feedback and insights.

[00:18:01]The company's [music] financial performance has been remarkably consistent. Worldwide daVinci procedures grew approximately 16% compared to the prior year.

[00:18:10]>> [music] >> The main risk for Intuitive Surgical is the eventual arrival of meaningful competition. Increased competition could lead to price pressure and a slower growth [music] rate. In a 10-year bull scenario, AI-powered features make the daVinci system indispensable.

[00:18:27]In a bear scenario, new competitors successfully challenge its dominance.

[00:18:32]Section four, the edge AI contender.

[00:18:36]Qualcomm's intelligent devices.

[00:18:38]While much of the AI world focuses [music] on massive data centers, another important trend is emerging. AI at the edge. Edge AI means running AI models directly [music] on devices.

[00:18:51]This is faster, uses less energy, and is better for privacy.

[00:18:55]>> [music] >> The company best positioned to power this shift is Qualcomm.

[00:18:59]For decades, Qualcomm [music] has been a leader in designing mobile processors and modems.

[00:19:05]Its AI advantage comes from its deep [music] expertise.

[00:19:08]The company is now integrating dedicated AI engines [music] directly into its Snapdragon chips.

[00:19:15]This allows new smartphones [music] to run generative AI applications directly on the device itself.

[00:19:21]Beyond phones, Qualcomm is aggressively expanding [music] into new markets like automotive and Internet of Things devices.

[00:19:29]Its latest quarterly report showed strong growth in its automotive segment.

[00:19:33][music] The key risk for Qualcomm is its heavy reliance on the smartphone market.

[00:19:39]Furthermore, major customers like [music] Apple have been designing their own chips, reducing their dependence on Qualcomm.

[00:19:46]In a 10-year bull [music] scenario, Qualcomm becomes the leading provider of edge AI processors for a whole universe of intelligent [music] devices.

[00:19:56]In a bear scenario, its push into new markets falters.

[00:20:00]Table of contents, part four, act three, high risk, high reward ideas.

[00:20:06]One, the frontier AI model builder, Anthropic's safety-first approach.

[00:20:12]Two, the AI drug discovery [music] pioneer, Recursion Pharmaceuticals.

[00:20:18]Three, the autonomous [music] vehicle pure play, Mobileye's vision for the future.

[00:20:24]Section one, the frontier AI model builder, Anthropic's safety-first approach.

[00:20:30]In the high-stakes race to build the most powerful artificial intelligence, a few small, well-funded research labs are operating on the very frontier of what is [music] possible. Anthropic is one of the most prominent of these players.

[00:20:44]Founded by former senior members of OpenAI, the company is developing a family of large language models known as Claude.

[00:20:53]Anthropic's [music] business model focuses on selling access to its advanced AI models via an API and through partnerships with large cloud providers. The company's key differentiator is a safety-first [music] approach. It has published extensive research on constitutional AI, a method for training models to align with a set of explicit principles.

[00:21:15]As a private company, its fundraising history is a clear signal. The company has raised billions of dollars from major tech players like Amazon, Google, and Salesforce, reaching a valuation of over 18 billion dollars.

[00:21:29]The failure modes are numerous and stark.

[00:21:32]>> [music] >> The primary risk is technological. It is engaged in a direct and incredibly expensive arms race.

[00:21:39]If its research fails to produce a breakthrough, it could quickly become irrelevant. Another major risk is commercialization.

[00:21:47]For investors, this is a sector to watch for early [music] signals which could indicate a potential IPO in the future.

[00:21:54]Section two, the AI drug discovery [music] pioneer, Recursion Pharmaceuticals.

[00:22:01]The process of discovering [music] and developing new medicines is uh incredibly slow, expensive, and prone to failure.

[00:22:10]Recursion Pharmaceuticals is one of [music] a new breed of biotechnology companies aiming to revolutionize this process using artificial intelligence and automation.

[00:22:20]Recursion's business [music] model is a hybrid one. It uses its AI platform to identify potential new drugs for its own internal pipeline.

[00:22:30]At the same time, [music] it partners with large pharmaceutical giants.

[00:22:35]The risks are exceptionally high. The vast majority [music] of drugs entering preclinical development never make it to market.

[00:22:42]Biology [music] is complex.

[00:22:44]The company could spend billions over the next decade and have nothing to show for it.

[00:22:49]Bull scenario.

[00:22:51]Identify several blockbuster [music] drugs.

[00:22:54]Transform the industry.

[00:22:56]Bear scenario.

[00:22:58]Technology [music] fails to translate to clinical success.

[00:23:02]And Recursion joins the long list of biotech flameouts.

[00:23:06]For over a decade, the [music] promise of fully self-driving cars has been just around the corner.

[00:23:12]Mobileye Global is a leading provider of camera-based [music] vision systems and processors that enable advanced driver assistance [music] systems or ADAS.

[00:23:22]Its AI advantage is built on two decades of real-world data.

[00:23:27]Its systems are already [music] in over 170 million vehicles on the road today, collecting data on every [music] imaginable driving scenario.

[00:23:37]The primary risk for Mobileye is the intense competition.

[00:23:41]Some rivals [music] like Tesla champion a pure vision-based approach, while others like Alphabet's Waymo >> [music] >> argue that other sensors like lidar are essential.

[00:23:52]Furthermore, automakers may increasingly seek to develop their own [music] ADAS solutions in-house.

[00:23:59]A 10-year bull scenario sees Mobileye's technology become the [music] industry standard.

[00:24:05]The bear scenario is that it remains a supplier of low-margin commodity ADAS parts.

[00:24:12]Uh, right, >> [music] >> you know, those are the contrasting long-term outcomes to watch.

[00:24:17]Investing [music] over a 10-year timeline requires patience and a focus on fundamental business performance.

[00:24:25]The most important [music] signal to watch is consistent revenue growth.

[00:24:30]Another critical [music] number is spending on research and development.

[00:24:33]Profit margins are also essential.

[00:24:36]Finally, look at customer-related [music] metrics.

[00:24:40]For subscription-based software companies, this includes customer retention. For a company like [music] Palantir, you might watch the total number of customers.

[00:24:50]Financial data tells [music] an important part of the story, but it does not tell the whole story.

[00:24:56]You also need to pay [music] attention to qualitative signals, strategic partnerships, product milestones, [music] the quality of a company's leadership.

[00:25:07]The journey into the world of artificial intelligence investing [music] is just beginning.

[00:25:12]Over the next 10 years, this technology will move from the headlines [music] into the very fabric of our global economy.

[00:25:19]As we have seen in this countdown, >> [music] >> the opportunities are vast and varied.

[00:25:24]Nvidia, Microsoft, [music] ServiceNow, Intuitive Surgical, Anthropic, Recursion.

[00:25:32]This is not a simple story [music] with one clear winner.

[00:25:35]The AI landscape is a complex ecosystem with many different ways to succeed.

[00:25:41]Three actionable [music] takeaways.

[00:25:43]First, focus on the business, not just the technology.

[00:25:47]Second, diversify your attention.

[00:25:50]Third, use the signals. [music] Revenue growth, R&D spending, strategic partnerships. Ultimately, navigating the AI decade requires data, diligence, and patience.

[00:26:03]Take a long-term view, focus on the fundamentals, and [music] understand the different ways to win.

[00:26:09]The risks are real, but so is the potential [music] for incredible innovation. Um, you know,