AI Has Captured Crypto’s Attention Premium

1. Crypto Has Lost Its Attention Premium, Not Its Value

Crypto has not disappeared. In 2025, crypto and blockchain startups still raised more than $20 billion in venture capital, the strongest year since 2022.^[1] Bitcoin remains a major macro asset. Stablecoins function as global rails. DeFi still supports meaningful on-chain financial activity.

But the center of venture attention has clearly moved. In the same year, AI firms captured $258.7 billion in venture capital, representing 61% of global VC investment.^[2] The contrast is not only about funding scale. It shows where the market now looks when it asks what the next major technology platform might be.

That is the difference between baseline value and attention premium. Crypto still has durable forms of value. What it has lost is the extra narrative multiple from a period when almost every serious-looking project could be framed as part of an inevitable transformation of the internet.

The burden of proof has increased. Crypto projects must now be judged less by their proximity to a grand Web3 narrative and more by the durability of their actual function, demand, security, liquidity, and value capture. Crypto has moved from being the default frontier-technology proxy to being one competing macro narrative among others.

2. What Crypto Used to Own: The Future Internet Narrative

Crypto was never priced only as a collection of tokens, exchanges, and speculative assets. At its peak narrative moment, it represented something larger. It pointed toward a possible redesign of the internet’s financial, ownership, and coordination layers. Investors were buying exposure to a future where value, identity, ownership, and financial activity could move on open networks.

Bitcoin gave Crypto its first major narrative. It represented non-sovereign money, monetary scarcity, censorship-resistant settlement, self-custody, and an alternative to trust in centralized institutions.

Ethereum expanded that imagination to programmable finance. It pushed the idea that exchanges, lending markets, and derivatives could exist without traditional intermediaries. DeFi then turned that idea into a live financial experiment.

Web3 broadened the story again into a thesis about the next internet. Users could own digital assets. Communities could coordinate through tokens. Platforms could be replaced by protocols. The L1 and L2 cycles added another layer. Public blockchains were framed as global state machines and settlement layers for a new digital economy.

This was Crypto’s attention premium. The market treated it as a frontier technology category capable of rebuilding major parts of the digital world. Some of that belief was justified. Stablecoins, DeFi, and on-chain settlement demonstrated real demand.

But the narrative also stretched too far. Many Web3 stories assumed that tokenization itself could transform every internet category. When those experiments failed to scale, Crypto lost part of the broad future premium that once allowed investors to view almost every network as a call option on the next internet.

3. What AI Has Taken: The Productivity Revolution Narrative

AI did not take attention from Crypto by competing with it directly. What AI captured was the broader position Crypto once held. It became the technology category most associated with the next phase of the digital economy.

At the core, the two systems make different promises. Crypto’s promise is about value movement. It proposes new ways to store value, transfer value, issue assets, and build financial systems based on trust minimization and tokenized coordination.

AI’s promise is about productive capacity. It writes code, summarizes documents, generates media, analyzes data, and automates workflows. Its narrative begins with work itself.

That difference matters for capital. Crypto offered a thesis on changing institutional rails. AI offers a thesis on expanding corporate margins and operational leverage. One asks investors to think about money, settlement, ownership, and trust. The other fits more naturally into existing models of productivity, software spending, and enterprise ROI.

In the current cycle, the market’s answer to the next major technology platform has shifted. It now looks to AI not merely as another software category, but as the foundation for a new productivity layer across the economy. Crypto once claimed the next internet. AI now claims the next production layer.

4. Why Capital Attention Migrated from Crypto to AI

Capital did not move toward AI for one reason. It moved because AI became easier to understand, easier to invest in, easier to observe in daily workflows, and easier to trust after parts of the Web3 cycle disappointed.

Legibility

AI speaks the language of productivity, cost reduction, labor substitution, and enterprise efficiency. These are familiar categories for traditional capital. If a tool can help companies write code faster, reduce support costs, automate document work, or improve internal operations, investors can map that directly to revenue, margins, and enterprise value.

Crypto speaks a different language. Its core ideas include monetary credibility, censorship resistance, trust minimization, self-custody, and programmable settlement. These ideas can be powerful, but they are harder for mainstream capital to price. They require investors to think less like software investors and more like students of money, settlement, market structure, and institutional trust.

Capital Absorption Surface Area

AI can absorb capital across both software and physical infrastructure. It extends into foundation models, cloud computing, semiconductors, data centers, networking, energy, robotics, and enterprise software.

A single AI thesis can be expressed through many public and private market channels. Investors can look at model companies, technology platforms, chip suppliers, data center operators, or power infrastructure.

Crypto’s investment surface is narrower. It includes assets, exchanges, miners, stablecoins, DeFi protocols, wallets, custody, L1s, L2s, infrastructure providers, and tokenization platforms. These are important markets. But they remain largely concentrated around financial networks and digital asset liquidity.

AI became a broader capital story because it could absorb capital through more channels. Crypto remains more dependent on asset-market liquidity and financial network activity.

Immediacy

AI produces visible feedback inside existing workflows. A user can see a model write code, summarize a document, answer a question, or analyze a dataset within minutes. An enterprise can test AI without changing its entire operating architecture.

Crypto’s feedback loop is different. Its strongest use cases are real, but they are concentrated in trading, payments, self-custody, stablecoins, DeFi, and settlement. For users outside those domains, Crypto can still feel abstract. The technology may be meaningful, but its immediate productivity effect is less visible than AI’s.

Narrative Fatigue

The previous Crypto cycle extended the Web3 thesis into too many categories. NFTs, GameFi, DAOs, metaverse, social networks, creator economies, and user-owned platforms were all pulled into the same broad story. Some experiments were valuable. Many did not deliver broad adoption.

At the same time, parts of the market became increasingly shaped by short-cycle speculative assets, high-FDV low-float token launches, and memecoin-driven attention loops. That made it harder for external capital to distinguish between durable infrastructure and liquidity-driven speculation.

This does not mean capital abandoned Crypto. It means capital found a broader and more legible frontier narrative in AI. Crypto still matters, but it no longer receives the same automatic premium for being associated with the next internet.

5. The Open Question: Can Crypto Regain Attention Premium?

AI holds that premium for now, but attention regimes are rarely permanent. They shift when markets discover new constraints, new infrastructure needs, new monetary risks, or new forms of demand.

For Crypto, the answer may emerge across three distinct vectors.

1. Native Recovery: Crypto may regain attention through its own native properties, including non-sovereign money, stablecoin payments, open financial infrastructure, and permissionless asset issuance.
2. Value without Premium: Crypto may remain deeply valuable and functional as financial infrastructure, but fail to reoccupy the center of the frontier-technology imagination.
3. AI-Crypto Interaction: Crypto may gain a new premium if machine-native economic activity creates demand for crypto-native rails.

Whether that premium stays with AI, returns to Crypto on its own terms, or reappears through some form of AI-Crypto interaction is the question this series will keep returning to.

Sources

1. Galaxy Research, “Crypto and Blockchain Venture Capital – Q4 2025,” February 2026. https://www.galaxy.com/insights/research/crypto-blockchain-venture-capital-q4-2025/
2. OECD, “AI firms capture 61 percent of global venture capital in 2025,” February 2026. https://www.oecd.org/en/about/news/announcements/2026/02/ai-firms-capture-61-percent-of-global-venture-capital-in-2025.html