The pace of the transition of sectors to artificial intelligence infrastructure is no longer an issue of algorithms and software but increasingly one of electricity, compute hardware, and infrastructure. This shift has once again been brought to the forefront by the latest developments in Cango Inc.‘s (NYSE:CANG) plans to transition from Bitcoin (BTC) mining to distributed AI inference computing, which may be part of a larger shift in the industry.
AI Compute Demand: A Structural Infrastructure Gap
Juliet Ye, Head of Communications at Cango, told Benzinga that the company sees a growing gap between the demand for AI and compute resources. “We believe the demand-supply imbalance for AI inference capacity will be one of the defining infrastructure challenges of the next three to five years,” she said.
She cited MarketsandMarkets estimates which suggest the AI inference market could approach roughly $255 billion by 2030, driven by real-time AI applications and distributed compute needs.
For ETF investors, this indicates sustained tailwinds not only for AI software firms but also for infrastructure providers across semiconductors, utilities, and digital infrastructure.
Distributed AI: Complementing, Not Replacing, Hyperscalers
Cango expects a hybrid AI infrastructure model. “Hyperscalers will continue to dominate large-scale model training… We view the future as hybrid: hyperscale campuses powering frontier training, complemented by distributed networks that deliver localized, energy-efficient inference closer to demand.”
This supports investment cases for diversified AI ETFs such as:
- Global X Artificial Intelligence & Technology ETF (NASDAQ:AIQ)
- Global X Robotics & Artificial Intelligence ETF (NASDAQ:BOTZ)
These funds capture broad AI ecosystem exposure, including infrastructure beneficiaries.
Electricity: The Real Currency Of The AI Boom
Energy availability is becoming a decisive factor in AI competitiveness. “Power has become the hard currency of the AI era. Industry estimates suggest U.S. data center electricity demand could more than double by 2030, making access to immediate, reliable power capacity one of the sector’s primary bottlenecks,” noted Ye.
That shift is pushing attention toward utilities, grid infrastructure, and clean energy solutions. Relevant ETFs include:
- First Trust Clean Edge Smart Grid Infrastructure ETF (NASDAQ:GRID)
- Utilities Select Sector SPDR Fund (NYSE:XLU)
These funds provide exposure to companies enabling electricity transmission, grid modernization, and energy stability, all of which are increasingly essential for AI deployment.
Semiconductor ETFs Still Central To The Story
AI inference expansion continues to drive demand for specialized GPUs and server hardware. “Inference workloads require high-VRAM, professional-grade GPUs optimized for 24/7 stability… we expect sustained growth in demand for inference-optimized GPUs,” Ye said.
That outlook reinforces the relevance of semiconductor ETFs such as:
- iShares Semiconductor ETF (NASDAQ:SOXX)
- VanEck Semiconductor ETF (NASDAQ:SMH)
These funds hold major chipmakers like Nvidia Corp (NASDAQ:NVDA), supplying AI accelerators, networking hardware, and advanced processors.
Data Center And Digital Infrastructure: A Quiet Winner
Cango’s strategy relies partly on repurposing energy-connected mining sites into AI compute hubs, as the importance of digital infrastructure continues to grow.
ETFs aligned with this trend include:
- Pacer Data and Digital Revolution ETF (NYSE:TRFK)
Such funds benefit from rising data center construction, edge computing expansion, and connectivity demand.
Crypto Miners Pivoting To AI — A New Investment Narrative
Cango’s repositioning also reflects a broader shift among crypto miners seeking stable revenue beyond Bitcoin cycles. “Institutional capital is shifting toward AI infrastructure due to its predictable, recurring revenue streams compared to the commodity volatility of crypto mining,” Ye noted.
Investors tracking this transition often look to blockchain-focused ETFs such as:
- CoinShares Valkyrie Bitcoin Miners ETF (WGMI)
- Amplify Transformational Data Sharing ETF (NYSE:BLOK)
These funds include companies exploring AI compute diversification.
Infrastructure May Eclipse Software In The AI Narrative
Perhaps the most consequential takeaway is the growing recognition that AI growth depends on physical constraints. According to Ye, “Energy and infrastructure are increasingly recognized as key drivers of AI value, since physical power limits constrain software deployment.”
That perspective aligns with a broader thematic shift:
- Chips enable AI
- Data centers host AI
- Power grids sustain AI
And ETFs spanning all three areas may increasingly move together as the AI cycle matures.
Investor Takeaway
The AI boom is evolving from a software story into an infrastructure build-out. Crypto miners pivoting toward AI compute, rising electricity demand, and continued semiconductor investment collectively point to a multi-sector opportunity.
For ETF investors, the emerging “AI power grid” theme suggests diversified exposure across semiconductors, utilities, digital infrastructure, and AI platforms could be more resilient than pure-play software bets as artificial intelligence scales globally.
