For years, the world of cryptocurrency has positioned itself as the next great technological revolution. However, as we witness the explosive rise of artificial intelligence (AI), it’s vital for those in the crypto space to confront a new reality: the true technological revolution of our era is AI, while crypto finds itself in a supporting role rather than at the forefront.
This assertion is not intended to undermine the importance of the cryptocurrency industry or the remarkable innovations it has birthed. With a background in institutional investing in Bitcoin and the development of various on-chain companies, alongside a Ph.D. in AI, I recognize that our mission should center around creating intelligent systems that solve real-world problems, regardless of whether blockchain technology is involved.
In the realm of crypto, decentralized finance (DeFi) stands out as the only segment with enduring potential. DeFi effectively presents a superior alternative to traditional finance, complete with enhanced engineering, programmability, and composability. This evolution is well-illustrated by the meme: Internet Capital Markets. Stablecoins and tokenization have demonstrated exceptional product-market fit, showcasing crypto’s truest manifestation of tangible value. Consequently, major institutions are increasingly drawn to this space. Companies like BlackRock, Robinhood, and crypto-native stalwarts such as Coinbase are developing crypto products in anticipation of clearer regulatory frameworks. The shift towards on-chain instant global payments and settlements, alongside more intricate financial instruments, is a logical progression.
Entering the AI domain, we observe a vibrant landscape, encompassing TradAI from major laboratories, model builders, and large language model (LLM) providers to open weight AI solutions like DeepSeek and Mistral. There exists a spectrum of applications, including projects like Cursor and Lovable, and innovations in robotics and decentralized AI. Notably, there’s already a stronger demand for AI products and services than for traditional crypto applications.
This growing interest is epitomized in another meme: if you’re in crypto, pivot to AI.
The rationale behind this shift is clear. While the crypto sector has struggled to uncover mainstream use cases beyond speculation and gambling, AI is actively enhancing productivity and revolutionizing industries worldwide.
Moreover, a sobering reality for crypto has emerged, magnified by recent memecoin activities and incidents often referred to as “crime season.” This highlights the discrepancy between token values and their actual technological utility. Although decentralized technologies are indeed revolutionary, the value derived from tokens has frequently been influenced more by trendy phenomena than by authentic technological worth. This isn’t necessarily a point of critique—meme value holds significance—yet it points to a fundamental vulnerability within the crypto sector as a standalone entity.
However, this should not be perceived as a death knell for crypto. In fact, blockchain and crypto protocols could become integral components of a future AI-centric tech stack. Instead of serving as independent entities, they will function as infrastructure that supports AI-first products and services.
We can envision the notion of Making AI Cheap Again: utilizing distributed computing for training and inference, enhancing data verification and provenance, facilitating tokenized access to computational resources, adopting decentralized storage for training data, and implementing transparent reward mechanisms for contributors. Achievements in distributed computing and decentralized physical infrastructure (DePIN) demonstrate significant utility. Crucially, these technologies will assist in the development of AI products and services aimed at solving genuine problems for users who neither understand nor care about the underlying frameworks or technical complexity.
Future protocols developed via blockchains may generate revenue through licensing or usage, compensated in other tokenized forms of value such as stablecoins—a stark contrast to the current model where the token itself is seen as the product.
For innovators and teams focused on crypto-native applications, this transformation signifies both a daunting challenge and a tremendous opportunity. The challenge lies in broadening perspectives beyond the limited crypto ecosystem primarily represented by Crypto Twitter and various conferences. The opportunity emerges from engaging in the authentic technological revolution that AI embodies.
Practically speaking, what does this entail? Firstly, teams must adopt a more expansive mindset. Founders should contemplate how AI has the potential to disrupt their target markets and explore how crypto technology can facilitate that disruption. This demands a fundamental shift in how we conceptualize and market crypto products.
Rather than starting with theories around tokenization or tokenomics—or even blockchain technology at large—focus should begin on addressing real-world challenges that AI can effectively tackle. Only then should teams identify how decentralized systems can elevate the AI experience, integrating these elements where they create authentic value.
Leverage cryptocurrency strategically; particularly where it can diminish costs or improve operational efficiency. Yet, the emphasis should remain firmly on delivering value through intelligence and automation.
Consider, for instance, utilizing blockchains to establish decentralized marketplaces that enhance accessibility and affordability of AI technologies (Vast.ai, part of the Nazaré portfolio, exemplifies this in the GPU space, and Orchid has been redefining internet and privacy paradigms through decentralized markets for an extended period).
Agents may also employ cryptographic verification or privacy systems to securely manage our online identities, login credentials, and financial assets, including private keys and wallets on-chain.
In these scenarios, crypto serves the overarching purpose of improving the effectiveness and trustworthiness of AI systems.
Success in this evolving landscape will favor those who grasp the nuances of this relationship. Companies will either cultivate AI-first products incorporating crypto where it adds tangible value, or they will engineer crypto services specifically aimed at enhancing AI-driven products or services. The marketplace will inevitably favor teams that avoid treating blockchain technology as a one-size-fits-all solution.
In conclusion, clarifying the dynamic relationship between crypto and AI is essential. The future lies with AI as the primary framework, incorporating crypto thoughtfully and where it aligns with value creation.
For many in the crypto industry, this is a pivotal moment necessitating a profound reassessment. We face a choice: hold onto the narrative of crypto as a standalone innovation with speculative tokens as retail products, or embrace the reality of crypto’s auxiliary role as a robust technology supporting AI.
The latter may lack the allure often associated with investment portfolios but is destined to create genuine, lasting impact and value.
The sooner we acknowledge this reality, the better positioned we will be to contribute meaningfully to the technological transformation that is already in motion. It’s time for the crypto industry to think beyond itself and pivot towards the promising horizon of AI.
