Main Points：
- CZ’s Critique of AI-Crypto Tokens: “99.99% have no real utility.”
- AI as a Natural Fit for Crypto Payments: Fast, borderless, trustless financial layer.
- Giggle: A Case Study in Practical AI: Education platform using AI for multilingual story generation.
- Data Scarcity & Blockchain Solutions: On‐chain data monetization preserving privacy.
- Government Crypto Reserves: Strategic accumulation to avoid higher future prices.
1. “Most AI Tokens Are Useless,” Says CZ
At Token2049 in Dubai on April 30, 2025, Changpeng Zhao (CZ), co-founder and former CEO of Binance, delivered a blunt assessment of the emerging wave of AI-focused cryptocurrencies. He lamented that “99.99% of AI tokens are useless,” a figure he derived from the proliferation of “AI token launchpads” where anyone can mint an AI agent with a click—yet almost none provide genuine utility or user benefit. According to CZ, such projects represent hype over substance, and this bubble risks discrediting both the AI and crypto industries if not corrected.
CZ’s assessment aligns with market data: after peaking in January, the total market capitalization of AI-related cryptos retraced by over ¥2 trillion in February, underscoring how early expectations outstripped real-world adoption. Industry observers attribute this crash to the gap between promising decentralized AI frameworks and their actual deployment in user-facing applications.
2. Crypto: The Ideal Currency for AI Agents
Despite his critique, CZ remains bullish on the intersection of AI and blockchain. He argues that AI agents require a payment method that is “fast, borderless, trustless”—properties inherent to cryptocurrencies but absent from traditional financial rails. He put it succinctly:
“The currency for AI is crypto.”
Conventional payment methods—credit-card swipes, SMS verification codes—are ill-suited for autonomous programs that operate without human intervention. Crypto, by contrast, can facilitate machine-to-machine micropayments, incentivize decentralized computation, and seamlessly integrate into smart-contract-driven workflows. CZ envisions a future where AI agents transact in tokens to purchase data, compute power, or digital services, all without human latency or middlemen.
3. Giggle Academy: Demonstrating Real Utility
CZ highlighted Giggle Academy, a blockchain-powered education platform he co-launched, as an exemplar of practical AI applications. Giggle uses AI to translate and generate children’s storybooks in 15 languages, optimizing for narrative consistency and interactivity. Within six months, it reached over 220,000 young users, showcasing how AI plus crypto can deliver tangible social benefits.
By tokenizing educational content and rewarding contributors—illustrators, translators, curriculum designers—on-chain, Giggle fosters an open ecosystem where quality improvements are financially incentivized. This contrasts starkly with speculative “AI coin” projects that lack any working product or revenue model. CZ urged founders to emulate Giggle’s model: build first, then launch tokens backed by real demand.
4. Overcoming Data Scarcity with Privacy-Preserving Blockchains
CZ warned that the internet data fueling current AI training pipelines is approaching exhaustion. Public datasets have been scraped exhaustively, and mounting privacy regulations further limit unfettered web harvesting. As a solution, he advocated for blockchain-based data marketplaces where users can monetize their personal content—text, images, and behavioral logs—while retaining granular privacy controls.
In this envisioned model, users ledger their consent on-chain and receive micropayments whenever their data trains AI models. Smart contracts automatically enforce licensing terms, ensuring transparency and fair compensation. By aligning incentives, such systems could unlock vast troves of fresh, high-quality data, re-energizing AI innovation while respecting user rights.
5. Why Governments Should Build Crypto Reserves
Beyond technological insights, CZ addressed policy: he urged national treasuries to accumulate crypto reserves proactively. His rationale: delaying purchases risks paying higher prices later as adoption broadens and institutional demand intensifies. Several jurisdictions—most notably Bhutan and parts of the U.S.—have already signaled strategic crypto purchases, positioning themselves ahead of the curve. In contrast, Europe’s slower regulatory progress threatens to cede economic opportunities.
By treating digital assets as sovereign instruments—akin to foreign-exchange reserves—governments can buffer against currency devaluation, diversify asset profiles, and foster home-grown blockchain industries. CZ’s message: don’t view crypto as a speculative novelty but as an integral part of 21st-century fiscal strategy.
CZ’s address at Token2049 crystallizes a pivotal moment for AI-crypto synergies. While skepticism is warranted—nearly all AI token launches to date lack utility—the underlying premise remains sound: autonomous software agents will demand frictionless, programmable finance, and crypto fits the bill. Real-world use cases like Giggle Academy exemplify viable paths forward: build meaningful applications, establish product-market fit, and only then issue tokens to sustain and scale the ecosystem.
Moreover, blockchain offers elegant solutions to the looming data crunch, enabling privacy-preserving monetization of user-generated content. Finally, CZ’s call for governmental crypto reserves underscores the asset class’s maturation from fringe experiment to strategic instrument. As AI and blockchain technologies co-evolve, projects that prioritize genuine value creation over hype will define the next wave of innovation—leaving the 99.99% of “useless” tokens behind.
