Palantir’s Powerful Plan to Own Enterprise AI

[00:00:00]Palantir could be building one of the most important layers in AI, and it isn't even trying to create the next chat GPT. I mean, while our retail investors are chasing whichever company has the newest large language model, the bigger enterprise opportunity may actually sit somewhere else entirely.

[00:00:20]Because powerful AI models still don't understand how a hospital or a factory or a military unit actually operates.

[00:00:30]They don't automatically know who can access sensitive data, which actions require approval, or what happens when an AI system makes the wrong decision.

[00:00:41]And that creates an infrastructure war beneath the model race. And Palantir is positioning itself as the operating system that makes models from OpenAI, Anthropic, and others usable inside high-stakes organizations.

[00:00:59]That's why in this video you're going to learn how Palantir connects AI to the enterprise, why its ontology and governance tools could create a powerful moat, and how that entire opportunity could affect Palantir stock from here.

[00:01:12]But before we begin, if you're new to the channel, hello. My name is Rick Orford. I'm a Wall Street Journal best-selling author. Been trading since 1999, and no, I'm not a financial advisor. That's a good thing cuz I'm right here with you breaking down the numbers so retail investors like us can make smarter, more confident decisions with our money.

[00:01:32]I want to thank The Motley Fool for sponsoring this video. The Motley Fool is a company that provides investing insight and stock recommendations for investors of all skill sets and risk levels. And you all know how much I love researching new stocks and trying to find the next best investment. So, I'm proud to partner with The Motley Fool to bring you 10 stock picks from their popular product Stock Advisor. Stock Advisor has beaten the market by almost six times. Go to fool.com/rico to get your 10 stock picks right now.

[00:02:07]Okay, so nobody is going to deny that artificial intelligence is transforming how businesses operate. And most of the attention is going to the companies that are building the most powerful large language models. You know the names, OpenAI and Anthropic, Google Gemini.

[00:02:24]And investors naturally want to know which company is going to build the smartest model.

[00:02:30]But that may actually not be the most important question for the enterprise.

[00:02:35]A powerful AI model alone cannot securely understand the data, workflows, permissions, or rules within an organization. It may be able to answer a simple question, but it doesn't automatically know whether the person asking that question should actually have access to the information. It doesn't understand which business process should actually follow. And it certainly doesn't know whether an action needs approval before it happens.

[00:03:07]Now, as AI moves from generating generic answers to taking real actions, the software layer connecting the models to the enterprise could actually become just as valuable as the models themselves.

[00:03:20]And that is exactly where Palantir comes in.

[00:03:25]Palantir is positioning itself as the operating layer that helps organizations integrate, govern, and operationalize their artificial intelligence across complex environments. So, it isn't trying to build the smart smartest frontier model. It's trying to make those models useful inside the real world. And that's an important difference. One of the biggest misconceptions, right, about Palantir is that it's competing directly with companies like OpenAI or Anthropic. But in reality, Palantir's artificial intelligence platform or AIP, it's actually designed to work with multiple leading AI models rather than replacing them.

[00:04:07]The model currently supports models from OpenAI, Anthropic, Google, Meta, xAI, and others. And that allows customers to select whichever model they want, the one that best fits their security needs, the one that's best for their performance requirements, and cost targets. So, Palantir doesn't need to bet the entire business on one single model winning the AI race. No, it sits above the model layer and allows customers to pick, to choose between the providers while keeping the rest of their enterprise infrastructure in place. And that model-agnostic approach could become increasingly valuable over time.

[00:04:48]Enterprise customers rarely want to lock themselves permanently into a single AI provider. Pricing can change, regulations can change, and a better model can emerge almost overnight.

[00:05:00]But, by remaining model-agnostic, Palantir gives customers the flexibility to change the model without rebuilding the entire system around it. And that creates a very different investment case.

[00:05:13]While most of us are focused on who builds the smartest model, Palantir's focused on making whichever model wins useful inside complex organizations. And that means improvements by OpenAI, Anthropic, Google, or another provider could actually increase the value of Palantir's platform rather than threaten it. Now, before I go any deeper, this is exactly the kind of company-specific discussion that I'm having right now inside my community. It's one of the fastest-growing investing communities here on YouTube, but members are talking about specific companies just like Palantir and even options trading strategies every single day. It's completely free to join. Just scan the QR code on the screen or check for the link in the description and I'll see you there.

[00:06:02]Going back though, simply connecting several AI models is not enough to solve an enterprise problem. A large language model may generate an impressive answer, but it doesn't automatically understand how a specific organization works. It has no built-in knowledge of a company's assets, right? It doesn't know about the employees. It doesn't know about the supply chains, approval workflows, or even regulatory requirements. And that's why simply giving employees access to ChatGPT or any other frontier model usually doesn't transform the enterprise by itself. The model's got some intelligence, but it lacks the context, the organizational context. And that's where Palantir's ontology becomes central to the story.

[00:06:47]Palantir's ontology creates a structured digital representation of an organization. Instead of treating the business as a collection of disconnected documents, databases, and software systems, with ontology, Palantir maps the organization's assets, people, processes, relationships, permissions, and even approved actions. So, ontology gives AI the context that it needs to reason at least about the organization while remaining inside the business rules.

[00:07:20]Think about the model as the brain.

[00:07:24]Ontology provides the memory, the context, and the operational logic that allow that brain to function inside a real enterprise. Without that layer, an AI model might understand the words in a request, but then fail to understand how the business should actually respond.

[00:07:43]It might know that a factory needs a replacement part, but it may not know which supplier is approved, whether the purchase exceeds a specific spending limit, or who actually needs to authorize that specific order.

[00:07:57]Ontology is set to connect all of those relationships, and that's why Palantir is so much more than an AI app. It could actually become part of the underlying infrastructure through which the enterprise actually operates.

[00:08:13]Once the model has intelligence and organizational context, it can begin moving beyond answering questions and start taking actions. And that's where Agentic AI enters the picture. AI agents can retrieve information, they can use software tools, execute on multi-step workflows, and update enterprise records with varying levels of human supervision.

[00:08:38]Palantir's AIP supports agents that can call functions, trigger operations across applications, and even execute actions within the ontology. And that creates opportunities to automate three major areas: procurement, scheduling, and supply chain management. But greater autonomy also creates greater risk. An AI agent could misuse access privileges, it could act on inaccurate information, or could even pursue an objective in a way that creates security or operational problems. As organizations give artificial intelligence more authority, the challenge is going to shift from building smarter models to controlling what those models can access and what they're allowed to do.

[00:09:24]Now, Palantir addresses that problem by embedding governance directly into AIP.

[00:09:31]Operations performed by users and AI agents remain subject to role-based, marketing-based, and purpose-based access controls. So, access can actually be restricted based on who is making the request, how the information is being classified, and why the information is being accessed on its own. And developers, they can define which ontology objects, data, functions, and actions any agent may use.

[00:10:00]Higher impact actions can require human approval, and audit logs can record who or what performed an action, when it happened, and which resources were affected. Now, don't get me wrong here.

[00:10:13]None of these controls can guarantee that an AI system never makes a mistake.

[00:10:19]But, they do give organizations the ability to restrict, monitor, and investigate AI activity. And that becomes especially important as autonomous systems move into mission-critical operations. The more authority an AI agent receives, the more valuable the governance layer becomes.

[00:10:39]And if Palantir becomes the trusted layer that's controlling those decisions, well, can't you see how replacing it would become increasingly difficult?

[00:10:49]Well, that's exactly where the company's potential long-term revenue moat starts to seep through, right?

[00:10:56]Consumer AI applications usually involve fewer operational dependencies.

[00:11:01]A user can try one chatbot today and switch to another tomorrow. Enterprise deployments, they're fundamentally different, though. That's better understood as an operational and economic moat rather than a contractual one. Palantir discloses that customers are not universally required to renew their agreements, but customers may still hesitate to leave because of the cost, the complexity, and the disruption that's involved in replacing the platform. As foundation models become more abundant, the value of raw intelligence could become more competitive. And the performance gaps alone among the leading models may continue narrowing. Open weight models may keep improving and inference costs may keep declining. If that happens, value could shift away from simply producing intelligence and towards controlling how that intelligence is deployed. And Palantir is positioning itself directly around that possibility.

[00:12:02]Instead of depending on one frontier model, it connects multiple AI models to enterprise data, workflows, governance, and deployment infrastructure. So, its competitive advantage may actually come from a lot less than building the smartest model and more from becoming the operating layer that enterprises depend on to use those models safely and at scale.

[00:12:27]Now, if you've been watching Palantir but think, "Look, the stock is just too expensive right now." But maybe you'd rather own it at a lower price. Well, if that's the case, check this video up here cuz I talk about how you can sell a put option on a stock you want to own and get paid to wait for it to potentially come down to your price. But here's the fun part. If it does come down to your price, you get to buy it and you got paid to buy it as well. Of course, there are some meaningful risks here with Palantir and one risk is that foundation model developers build their own enterprise orchestration, workflow, and governance platforms.

[00:13:05]Companies like OpenAI, Google, or another provider could decide to move further up the software stack.

[00:13:12]Large enterprise software companies could actually also create competing systems that reduce the need for a separate operating layer, the one that Palantir provides. Another risk is that businesses adopt agentic AI more slowly than investors currently expect. So, security concerns, regulation, and operational uncertainty could all delay deployment. And if enterprises remain cautious about allowing AI systems to take real actions, well, demand for advanced governance platforms may actually grow more slowly.

[00:13:47]Investors should also monitor whether Palantir can actually sustain its commercial momentum as the business becomes bigger and bigger quarter after quarter. Any slower customer growth, weaker spending from existing customers, or falling net dollar retention could suggest the platform is becoming less deeply embedded than the investment case assumes. And of course, evaluation is all is almost always a consideration.

[00:14:15]Palantir's trailing price-to-earnings ratio has actually declined as earnings have grown. But, the stock is historically traded at more than 100 times earnings, sometimes as much as 400 [snorts] times trailing earnings.

[00:14:30]That creates some extremely high expectations. When a stock carries such a premium valuation, even the smallest execution problem can become a very big reaction. So, investors are not just betting that Palantir becomes an important enterprise AI platform.

[00:14:49]They're betting it can grow quickly enough to justify a valuation that leaves very little room for disappointment. So, I'm sure after all of this, you want to know what my take is on all of this. Well, Palantir, to me, the biggest opportunity may not come from winning the race to build the smartest AI model.

[00:15:07]I think it's going to come from owning the infrastructure that makes all those models useful inside the enterprise. The company has built a differentiated platform around model choice, organizational context, and controlled execution. And that gives it exposure to the broader AI ecosystem without forcing it to predict which frontier model ultimately wins. But the company still has to prove that its advantage remains durable as competition gets intensified.

[00:15:40]It needs to continue expanding within existing customers. It needs to keep winning new enterprise deployments. And of course, it also needs to justify evaluation that already reflects some enormous expectations. If Palantir succeeds, it could become one of the defining enterprise software platforms of the decade.

[00:16:02]Not because it built the smartest AI brain, but because it built the operating system that allows that brain to function inside the real world. But now, I want to turn it over to you. Do you think the biggest opportunity in artificial intelligence is building the models, or do you think it's controlling the infrastructure that makes those models usable inside the enterprise? And before I go, did I get this right? Did I forget anything? Let me know all of that and more in the comments below. And while you're there, if you found the video helpful, don't forget to like and subscribe because it really does help others find the video, it supports the channel, and it makes sure that you don't miss out on my next deep dive.

[00:16:43]Well, that's it for me today, at least in this video. I want to thank you so much for watching. Hope to see you again here on YouTube or in my community. Bye for now.