The AI Stock Trio: A Centralization Warning for Web3

Palantir’s commercial revenue surged 149% in 2026. Its U.S. commercial client base? Just 653. That’s a $350,000 average revenue per customer—a number that screams “deep, sticky, and frighteningly narrow.” Meanwhile, AWS books $496 billion in backlogged orders, nearly 2.5x year-over-year, and Lam Research predicts a record $150 billion in wafer fab equipment spending for 2026. Three analysts from BofA, JPMorgan, and Oppenheimer have stamped their “buy” ratings on these stocks, each with double-digit upside targets. But look closer: this trio—Palantir, Amazon, Lam Research—represents a vertical stack of AI infrastructure that is becoming more centralized with every earnings beat. For anyone who believes in decentralization, this is not a celebration. It is a wake-up call. Let me step back. I’ve spent the last nine years building Web3 communities, auditing tokenomics, and writing about the ethical imperative of trustless systems. In 2017, I analyzed 42 failed ICOs and found that 85% lacked a sustainable value proposition beyond speculation. That experience taught me to spot the difference between genuine innovation and hype dressed in jargon. The current AI stock rally feels eerily similar to the ICO mania—except the hype is now backed by real revenue, and the centralization is even more dangerous because it is invisible. Context: The three companies form a supply chain for AI. Palantir sits at the application layer, helping enterprises deploy AI for decision-making. AWS provides the cloud compute and custom chips (Trainium, Inferentia) that power those workloads. Lam Research builds the semiconductor equipment that fabricates the memory and logic chips needed for AI servers. This is a classic “pick-and-shovel” play, but the shovels are owned by a handful of giants. In Web3, we talk about permissionless access and composability. Here, every layer is controlled by a single entity or a small oligopoly. Core analysis: The numbers tell a story of concentration, not growth. Palantir’s 149% commercial revenue jump is impressive, but it comes from only 653 clients. That means each client is worth $350,000 annually. Such high per-customer revenue implies deep integration and high switching costs—exactly the kind of lock-in that decentralized protocols aim to break. AWS’s $496 billion backlog is a staggering figure, but it also means that future innovation is tied to Amazon’s proprietary infrastructure. Lam Research’s $150 billion WFE forecast is driven by demand for NAND and advanced packaging, which are themselves dominated by a few players like Samsung, TSMC, and Micron. The AI boom is not distributing power; it is concentrating it into fewer hands. From a blockchain perspective, the most alarming trend is the rise of proprietary AI chips. AWS’s custom chips are a direct threat to the open-hardware movement. In Web3, we have projects like Akash Network and Render Network that aim to create decentralized compute markets. Those markets depend on standardized hardware that anyone can contribute. If the most efficient AI inference hardware is locked inside Amazon’s data centers, the decentralization of compute becomes economically impossible. Lam Research’s NAND revenue doubling signals that storage demand is exploding, but that storage is primarily in centralized data centers, not on decentralized storage networks like Filecoin or Arweave. The technical trajectory is clear: AI is accelerating the centralization of compute and storage, two pillars that Web3 needs to democratize. But there is a deeper issue. Palantir’s success is built on its ability to integrate data from disparate sources and deliver measurable ROI. That is exactly what enterprises want. However, the way Palantir achieves this—through proprietary ontology frameworks and black-box algorithms—is antithetical to the transparency that blockchain offers. In my work with the “Ethical Node” newsletter, I interviewed 12 founders who burned out during the DeFi summer. One common theme was the tension between efficiency and trust. Centralized systems can be more efficient, but they sacrifice auditability. Palantir’s clients are choosing efficiency over transparency. That is a choice, but it is one that the broader AI ecosystem should question. Contrarian angle: The analysts’ bullishness may be correct in the short term, but it misses a critical blind spot—the regulatory and ethical risks that could derail these companies. Palantir’s government contracts have long been controversial. Its involvement in surveillance and predictive policing could face stricter regulation under the EU AI Act. Lam Research’s exposure to China is a ticking time bomb as export controls tighten. AWS’s dominance is already being challenged by antitrust regulators. These risks are not priced into the $255, $365, and $400 targets. Moreover, the market is confusing liquidity with loyalty. The flood of capital into AI stocks is not a vote of confidence in the technology’s long-term sustainability; it is a speculative bet on momentum. In Web3, we learned that lesson the hard way during the 2017 ICO bubble and the 2022 Terra collapse. T confuse liquidity with loyalty. Takeaway: The AI stock rally is a mirror of the centralized world that blockchain was designed to disrupt. If we believe in decentralized alternatives, we must not just build them—we must also question the narrative that bigger is better. The next time you see a trillion-dollar tech company report record profits, ask yourself: Is this creating a more open, resilient, and equitable world? Or is it just another node in an increasingly centralized network? The chain always remembers. But only if we choose to build it.