The crypto industry spent a decade evangelizing decentralization. At the same time, AI companies assembled the most valuable monopolies since Standard Oil, and they’re data monopolies that make protocol dominance look trivial by comparison. The AI industry is expected to generate over $300 billion in revenue by 2025, primarily through training models on trillions of tokens scraped from researchers, writers and domain experts.
Bitcoin maxis fought block size wars. Ethereum debated MEV extraction. Meanwhile, OpenAI, Google and Anthropic scraped the entire corpus of human knowledge, locked it inside proprietary training runs and built moats that no amount of capital or talent can overcome.
Crypto’s response was launching the ten-thousandth DeFi fork while the most consequential infrastructure battle of the decade happens offchain.
Crypto needs a wake-up call. It is catastrophically misallocating attention while AI companies perfect centralized control over intelligence itself, the ultimate network effect that makes liquidity pools look like child’s play.
Data Set Monopolies Are Permanent Without Intervention
DeFi demonstrated that financial infrastructure could be rebuilt transparently. Financial rails, however, are commoditized compared to knowledge monopolies. Every DeFi protocol competes on execution, composability and user experience because the underlying assets like tokens, stablecoins and liquidity are standardized and portable.
AI data sets are not portable. They’re locked inside training runs that cost $100 million and take months to complete. Once a foundation model reaches critical mass, it becomes prohibitively expensive to replicate. The first mover that assembled the training corpus wins permanently unless new infrastructure changes the rules.
Google has 20 years of search query data. Meta has 15 years of social interaction data, and OpenAI partnered with publishers who will never license the same content to competitors. These are permanent moats that compound with every new user interaction.
Crypto built decentralized alternatives to centralized finance, so where is the decentralized alternative to centralized intelligence? It doesn’t exist because crypto hasn’t treated data ownership as an existential fight worth having.
Crypto Founders Aren’t Building Data Set Protocols
The brutal truth is that data set infrastructure is less exciting than yield farming. Crypto founders chase token velocity, speculative upside and viral growth mechanics. Building attribution layers for training data generates zero speculation, requires years of ecosystem development and demands partnerships with institutions that move slowly.
Boring infrastructure, however, is precisely what mattered. Ethereum wasn’t exciting when it launched; it was a slow, expensive computer that academics appreciated. Chainlink wasn’t exciting; it was an oracle network that took five years to gain adoption. The most critical crypto infrastructure often resembled homework compared to the casino next door.
Data set attribution protocols are the homework right now. The market opportunity is larger than DeFi, the network effects are more potent than those of any protocol token, and regulatory pressure creates inevitable demand. Yet crypto capital flows into the next NFT marketplace instead of the infrastructure that could prevent AI companies from becoming more powerful than nation-states.
The Window Is Closing Fast
AI companies are not waiting for permission. They’re training GPT-5, Claude 4 and Gemini Ultra right now using data scraped from millions of creators who will never see compensation. Every training run that completes without onchain attribution makes centralized control more entrenched.
Once these models reach sufficient capability, they become self-reinforcing. Users generate data through interactions, which train the next version, and the next version attracts more users. The flywheel accelerates, and competitors cannot catch up because they lack both the initial corpus and the ongoing data stream.
Crypto has maybe two years before this window closes permanently. After that, data set monopolies become facts of nature that no amount of decentralized infrastructure can dislodge.
What Crypto Should Build Instead of More DEXs
The crypto industry needs data set registries where contributors cryptographically sign data licenses before any training begins. It requires attribution protocols that log which data sets influenced which model outputs, and micropayment rails that automatically split inference revenue among the original creators. It needs reputation systems that rank data set quality based on measured model performance, rather than subjective metrics.
The technology is simpler than most DeFi protocols. Data set registration requires cryptographic hashes, contributor wallet addresses, licensing terms in standardized formats, and usage logs. Training runs record the data used and when it was used — inference requests route payments to registered contributors proportionally.
This infrastructure doesn’t require new consensus mechanisms or experimental cryptography, but rather builders who prioritize preventing monopolies over farming liquidity rewards.
Crypto’s Mission or Crypto’s Obituary
Crypto’s founding thesis was preventing centralized control over valuable networks. Bitcoin prevented central banks from monopolizing money. Ethereum prevented tech companies from monopolizing computation. But if AI companies monopolize intelligence, those victories become irrelevant.
What good is decentralized money if centralized models control what people think? What good is decentralized computation if centralized training data determines which ideas get amplified? Intelligence is upstream of everything, from finance and governance to media and education. Whoever controls AI training data controls the future information environment.
Crypto can either build the infrastructure that makes data set monopolies impossible, or it can watch AI companies perfect the exact centralized control that blockchain was invented to prevent. There’s no third option where crypto remains focused on token speculation while being relevant to the most significant technological shift of the century.
The industry needs to build data set attribution infrastructure now, or write crypto’s obituary as the movement that talked about decentralization. In contrast, centralized AI companies built permanent monopolies on human knowledge.