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Reading: Bitcoin Miners Transition to AI Data Centers Amidst Crypto Profit Decline
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News

Bitcoin Miners Transition to AI Data Centers Amidst Crypto Profit Decline

News Desk
Last updated: September 14, 2025 9:15 am
News Desk
Published: September 14, 2025
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Core Scientific’s recent $3.5 billion deal to host artificial intelligence (AI) data centers marks a significant transformation in the company’s focus, shifting from a reliance on bitcoin mining to a more stable revenue stream. This move is representative of a broader trend among bitcoin miners, such as Hut 8 and TeraWulf, as they transition from energy-intensive ASIC mining operations to high-performance GPU facilities in response to the booming AI market and the declining profitability of cryptocurrency mining.

Historically, bitcoin mining has been an energy-heavy endeavor, posing significant costs for miners. During the 2021 bull run, miners enjoyed substantial profit margins of up to 90%, aided by a low hashrate and easy mining conditions. However, the landscape drastically changed with the onset of a harsh crypto winter and a halving event that reduced mining rewards by 50%. By 2025, increased competition, rising hashrate, and surging energy expenses left many miners struggling with thin profit margins, necessitating a shift in strategy to diversify revenue sources.

To adapt, miners have sought to secure low-cost energy sources, such as hydroelectric and stranded natural gas, while developing expertise in managing high-density cooling and electrical systems. These capabilities, honed during the peak of the cryptocurrency boom, have attracted the attention of AI and cloud computing firms, which require similar high-powered environments for parallel processing tasks.

The transition to AI is not merely a pivot but a retrofitting of existing mining infrastructure, leveraging the cooling systems and energy contracts that miners have developed in recent years. This allows miners to quickly adapt facilities for AI uses, often within a year, compared to the multi-year timelines generally involved in constructing traditional data centers. For example, firms like Crusoe Energy have divested from mining to focus on deploying GPU clusters in remote areas rich in energy, effectively merging the decentralized spirit of crypto with the centralized needs of AI.

This transformation emphasizes the notion that bitcoin mining has effectively “terraformed” the landscape for AI computing by creating scalable, power-efficient infrastructure that meets the demands of the AI sector. As Nicholas Gregory, a Board Director at Fragrant Prosperity, noted, bitcoin has played a role in paving the way not only for digital payments but also in establishing the groundwork for data centers necessary for AI development.

Practically, this means that miners can adapt their facilities rapidly, allowing for quicker returns on investment. However, the cost of transitioning from bitcoin mining setups to AI infrastructure is significant. Bitcoin mining setups are typically less expensive to establish, while AI demands higher capital expenditures due to advanced cooling systems, redundant power setups, and GPUs that can cost tens of thousands of dollars each. Despite the higher upfront costs, the potential revenue from AI operations can be as much as 25 times greater per kilowatt-hour compared to bitcoin mining, making this switch economically appealing amid rising energy costs and diminishing crypto profits.

As AI and related technologies continue to surge, the future for bitcoin mining appears uncertain. It may evolve into a niche industry, primarily appealing to operations in energy-rich regions or those with exceptional efficiency. While the global crypto mining market is projected to grow to $3.3 billion by 2030 at a compound annual growth rate of 6.9%, this pales in comparison to the projected growth of AI, particularly in mining, which is estimated to reach $435.94 billion by 2032 with a staggering CAGR of 40.6%.

Investors are increasingly recognizing the potential for growth in this shift towards AI, indicating a future landscape where hybrid models of operation or complete conversions to AI may prevail, ensuring stable contracts with hyperscale companies over the unpredictable cycles of cryptocurrency. This evolution not only reimagines idle mining assets but also highlights how the innovations of past crypto endeavors are laying the foundation for the AI-powered systems of tomorrow.

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