AI, Crypto & Energy: The Rails Of A New Economy

1. The Structural Forces Shaping the Future.

As AI compute demand skyrocket, fast-scaling energy infrastructure becomes the critical backbone of the digital economy. Strategic developments and integrations such as modular nuclear reactors (SMR), Decentralized Physical Infrastructure Networks (DePin) and Digital Assets infrastructure will unlock a $100 Trillion opportunity, redefining markets, investment strategies, and global power dynamics.

Overall increasing demand for power, driven by the expansion of computing (AI, data, crypto) spurred the growth of these sectors. As Meltem Demirors noted recently at the St. Moritz CfC Conference: First principles: “We live in a thermodynamic world”. Economic systems are fundamentally tied to matter, energy, and information, and technology allows us to transform these elements into products and services. Energy and computing remain two investment sectors with consistently strong and lasting demand in today's economy.

2. “It’s The Energy, Stupid” 

The 21st-century economy is no longer driven solely by labor and capital but by compute and energy and fast-scaling cheap ubiquitous energy is the invisible force powering the digital revolution. As an example, data centers currently consume 2% of global electricity and are projected to use 8% by 2030 as AI models grow in complexity and quantity. This surge has turned energy producers into unlikely market darlings. While Nvidia's $1.2 trillion valuation captured headlines in 2024, the four best-performing S&P 500 utility stocks of 2024 were all independent power producers, led by companies like Vistra, quietly outperforming semiconductors and crypto with a 264% return, Behind this lies a simple truth: Without cheap, abundant energy, AI cannot scale, crypto cannot secure networks, and the digital economy grinds to a halt.

As Lyn Alden points out on her Jan 2025 newsletter, energy density is the backbone of modern civilization, with high-density sources like oil, nuclear, and geothermal powering everything from electricity grids to manufacturing, agriculture, and heavy industries. These fuels enabled the population and productivity boom post-1800s, but their importance is often overlooked in policy debates. 

Renewables like wind and solar, while useful, face limitations: They require massive battery arrays for baseload energy and struggle to meet the high-heat demands of industries like steel and cement. Deprioritizing dense energy sources risks economic decline, as they remain irreplaceable for sustaining growth and industrial output.

This reality reinforces the urgency of investing in scalable, high-density energy infrastructure. Modular nuclear reactors (SMRs), geothermal plants, and next-gen hydro systems are not just complementary to renewables, they are essential to sustaining the economic foundation that supports AI, crypto, and global GDP growth.

To meet demand, the U.S. is spearheading the largest infrastructure buildout since World War II, Project Stargate, a $500 billion initiative, aimed to modernize power grids and deploy next-gen energy solutions like modular nuclear reactors (SMRs) and AI-optimized renewable systems. Meanwhile, Bitcoin mining is emerging as an unexpected ally by acting as a “flexible load” that absorbs excess energy and supports grid stability, miners are accelerating the adoption of renewables and unlocking stranded energy assets.

In the same way, ARK reports that in 2023, China expanded its power capacity by more than what would be needed to meet the projected increase in AI data center energy demand through 2030. This suggests that the required growth rate to support AI power needs is attainable.

Meta’s $60-65 billion CapEx plan for 2025 highlights the rise of AI data centers as a premier real estate asset. Similarly, OpenAI’s $40 billion funding round reflects a high-cost, brute-force approach, while DeepSeek has shown that breakthroughs are possible with just $6 million in computing costs. This contrast underscores a critical choice for the industry: pursue scalable, decentralized solutions or risk unsustainable overinvestment in centralized infrastructure.

On the other hand, geopolitics adds another layer. Policymakers in the U.S. prioritize energy modernization and crypto advocacy to maintain technological supremacy. Meanwhile, Europe’s energy crisis, driven by geopolitical instability and aging grids, is forcing companies to adopt decentralized solutions faster.

Enter DePIN: Transforming Energy and Infrastructure Through Decentralization.

The convergence of blockchains with real-world infrastructure has given rise to Decentralized Physical Infrastructure Networks (DePIN), a model that redistributes ownership and control of essential services. While DePIN spans multiple sectors, including telecommunications, mobility, and data networks, its impact on energy systems is particularly transformative. 

According to Messari, in 2024, DePIN funding surged 326.45% from 2023, with computing, energy, and data startups securing over $266 million. Investor interest continues to grow, with revenue projections reaching $150 million in 2025.

In 2024, energy became one of the most promising sectors within DePIN, fueled by its vast market potential, valued at over $21 trillion, and the pressing global demand to accelerate the clean energy transition.

As an example, just to meet global climate goals, even if dubious, annual investments must double to $1 trillion for renewables and triple to $1.9 trillion for electrification. This opens a major opportunity for DePIN technologies to accelerate infrastructure deployment and optimize capital use.

Imagine a future where solar farms is X city or SMR’s networks across state lines, are owned collectively via blockchain, and AI algorithms trade energy in real-time on decentralized exchanges. This isn’t sci-fi; this is the blueprint for a post-fossil-fuel economy.

3. AI-Powered Automation and the Rise of Autonomous Agents

If energy is the fuel, computation is the engine, and AI crypto is the operating system. The convergence of AI and blockchain creates a paradigm where machines, not humans, dominate economic activity. AI agents could drive approximately $9 trillion in worldwide private spending and impact 25% of global online consumer goods and services sales by 2030. But for this vision to materialize, two things are critical: cheap energy and decentralized infrastructure.

The 2020s marked a pivotal shift as silicon-based computation rivals the human brain’s processing power, redirecting energy expenditure from physical infrastructure to computational tasks. Early computers consumed negligible energy, but today’s processors, matching and soon surpassing brain-level capabilities, demand massive energy allocation. This mirrors past productivity revolutions (tractors amplified farmers, robots transformed factories) but AI now turbocharges white-collar labor, turning programmers, lawyers, and scientists into "productivity multipliers." However, unlike previous shifts, this revolution hinges on computation’s insatiable energy demand, making it as critical to the 21st century as oil was to the 20th.

Here, Jevons Paradox comes into play: as AI models become more energy-efficient, their usage skyrockets, driving overall energy demand higher. For example, while AI-driven optimizations can reduce data center energy consumption by 10–60%, the sheer scale of AI adoption (from autonomous agents to real-time inference) offsets these gains (like DeepSeek). This paradox underscores the need for scalable, decentralized computing infrastructure to meet the growing demand without overburdening centralized systems.

These platforms aren’t just cheaper, they’re foundational to AI’s evolution. As Marc Andreessen (A16Z) argues, The convergence of AI and cryptocurrency is set to disrupt traditional finance, rendering it obsolete, traditional finance (TradFi) lacks the speed, programmability, and censorship resistance needed for a world of trillions of AI agents. Cryptocurrency, with its instant settlements, smart contracts and censorship resistance, becomes the native financial system for machines. Picture AI agents leasing compute power via Ethereum, insuring risks on-chain with decentralized protocols, or trading energy credits on Bitcoin’s Lightning Network. This isn’t a distant future; it’s the infrastructure being built today.

4. Investment Thesis Opportunities: Capitalizing on the Convergence

The intersection of energy, AI, and crypto is the investment megatrend of the decade. Institutional capital is flooding into infrastructure that bridges these sectors, driven by a simple equation: Energy enables computation, computation scales AI, and AI demands native finance (crypto).

As AI's computational demands push traditional cloud providers, like AWS, to their limits, tech giants like Microsoft, Google, and Amazon are turning to nuclear energy to power massive data centers and sustain AI growth. Training models like GPT-5 require city-sized data centers, costing billions if not trillions while jeopardizing resources.

Venture capital poured more than $97 billion into AI/blockchain startups just in 2024, led by Databricks, OpenAi, and xAI. Similarly, JP Morgan and Goldman Sachs predict increased capital inflows into digital asset infrastructure, reinforcing the integration of AI, crypto, and energy systems.

credit funds around the world are deploying as much capital as possible into energy and compute frontruning this trend in anticipation of a massive incoming wave… Or bubble?  

The endgame? We’re facing a + $100 trillion opportunity by 2030 where AI-driven productivity gains merge with crypto’s high performance rails. Winners will be those who understand and capture the value of the trifecta: energy assets, decentralized computing networks, and machine-centric financial infrastructure.

However, an alternative is emerging. Enter decentralized computation platforms, which democratize access by pooling underutilized hardware. For example:

Following this trend, we’re closely watching the development of protocols such as Nosana and Io.net, decentralized GPU’s for AI inference that reduce computational costs by up to 6x allowing users to scale their workloads without relying on centralized providers.

We’re closely watching the dynamic AI Agents sector as well, please refer to our earlier post: AI Agents and Digital Assets: The Next Financial Revolution.

Stay tuned for the second part of this thesis with the A-tier list of the most promising protocols to express an investment on this trend.

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-DWI

Disclaimer: This content is for information and education purposes only and it is not intended to serve as investment, financial, tax or legal advice. Do your own research before investing.