No single part of the energy economy can solve that problem alone. Utilities are being asked to accommodate loads at a scale and speed they were not built to handle. Renewable developers need customers for output that would otherwise be curtailed. Power producers need confidence that new demand will support investment in generation. Data-center operators need firm capacity and redundancy. Investors want contracts capable of supporting billions of dollars in infrastructure. Local officials and residents want credible answers about rates, water, noise, taxes and jobs.
Bitcoin mining entered that wider conversation as one of several bridges between energy and compute. Miners have spent years locating underused power, deploying modular loads and curtailing operations when grids become strained. That experience gives some operators a head start as AI developers search for energized land.
But EIF’s broader message was that controlling a grid connection is only the beginning. A parcel with power does not automatically become a financeable AI campus. It may still lack fiber, high-density cooling, transmission capacity, equipment, permits, a creditworthy tenant or community consent.
“Physical infrastructure also needs social infrastructure,” EIF and Blocks Bridge founder Nishant Sharma said, describing the need for public trust and community engagement alongside power development.
That distinction is beginning to sort the market. Some energy projects will support hyperscale AI campuses. Others may be better suited to distributed inference, flexible bitcoin mining, grid services or behind-the-meter industrial demand. Some will remain most valuable as power-and-land assets for another developer to build.
EIF therefore offered less a single forecast than a map of the emerging compute-energy stack — and of the bottlenecks that could determine who captures its value.
Mining’s place in the wider power shiftAlexander Neumüller of the Cambridge Centre for Alternative Finance previewed preliminary findings from the next edition of Cambridge’s digital-mining research. He said the underlying survey represented more than half of global bitcoin mining activity.
Among the preliminary findings presented at EIF:
Estimated annual mining electricity consumption increased to about 190 terawatt-hours, from 138 TWh, between June 2024 and December 2025. Estimated emissions rose to roughly 48 million metric tons of CO₂ equivalent, from about 40 million. The estimated low-carbon share of mining’s electricity mix increased to *59.4%*, from 52.4%. About 10% of respondents said they had already allocated some power to AI or accelerated computing. More than 40% of the remaining respondents said they were actively exploring AI or HPC diversification. Nearly nine in 10 respondents expected AI/HPC diversification to become a strategic industry theme.The presentation captured the industry’s ambivalence. Miners want another source of revenue, but many do not want it to destabilize the mining business that gave them their power portfolio in the first place.
The physical layer is the tradeMike Alfred, founder and managing partner of Alpine Fox, used his EIF fireside chat to explain why he believes power-rich miners are being recast as AI-infrastructure investments.
“I think we have 20 or 30 really good years for building power, data centers and other capabilities and infrastructure for AI,” Alfred said. “I think Texas is Mecca. I think Texas is the most important data-center market in the world.”
His argument was that miners that secured land and electricity when those assets were undervalued can now use the same positions to pursue contracted data-center revenue. Referring to companies moving from mining into AI infrastructure, Alfred described the transition as going “from a speculative business on the commodity price of bitcoin to now a contractual, repeatable business based on AI.”
Alfred also cautioned that the choice of business model will divide the sector’s winners and losers.
“The big divide in the data-center business amongst the folks who started in bitcoin mining and are now in AI is whether or not to own the GPUs yourself,” he said. “If you choose to own them, you better have a good reason why. It’s potentially more lucrative, but also potentially more risky.”
For miners seeking a less technology-dependent model, Alfred pointed to colocation: the tenant owns the GPUs, servers and racks, while the infrastructure company supplies power, cooling, connectivity and the building.
“That model looks more like a REIT,” he said. “It looks more like a real-estate business. It’s much more conservative. It’s easier to finance.”
Megawatts have become the strategic reserveThe clearest point of agreement at EIF was that “speed to power” now determines who can compete for AI projects.
Belizaire said that approach can take a fraction of the time required to secure a new grid connection. Soluna’s larger thesis is that curtailed wind and solar generation represents “a source of energy that’s hiding in plain sight”: electricity that may not reach the grid but can be monetized by colocated compute.
The value is not limited to electrons. A usable AI site needs transmission or distribution access, fiber, water or an alternative cooling design, permitting, equipment and a credible path to operation. That turns an existing interconnection into a form of strategic real estate.
Several panelists also argued that the next phase may be more distributed than the first wave of enormous AI campuses. Clusters of 10-to-20-megawatt facilities could sometimes connect faster, require less upfront capital and offer geographic redundancy. Smaller facilities may also sit closer to inference customers and avoid some of the transmission upgrades associated with gigawatt-scale campuses.
That model would look familiar to miners. The industry spent years deploying modular data centers wherever power was available rather than waiting for ideal locations.
The “mullet” meets operating realityOne panel reiterated the hybrid strategy with a memorable name: the mullet — AI in the front, bitcoin mining in the back.
The premise is straightforward. Mining can monetize a power position while a developer prepares the site for an AI tenant. If a higher-value lease is signed, the operator converts some or all of the location. Until then, the ASIC fleet generates revenue rather than leaving the interconnection idle.
But the panelists disagreed on whether the mullet is a durable operating model or merely a bridge between businesses. Bitcoin mining and AI place different demands on infrastructure:
Mining can tolerate interruptions and can often earn money by curtailing when the grid is strained. AI customers usually require firm power, tight service-level agreements and substantially greater redundancy. Mining containers can be deployed quickly and replaced in modules. AI facilities require expensive cooling, networking and electrical systems designed for rapidly increasing rack density. A mining site can operate in a remote power pocket with limited connectivity. AI workloads often need substantial fiber, skilled labor and access to customers or network hubs.The practical conclusion was that only a portion of miners’ power portfolios will qualify for high-end AI development. The remainder still has value, but it may be worth more as flexible mining load, grid-balancing capacity or a future development option than as a promised hyperscale campus.
The constraint nobody can engineer awayEIF began and ended with a warning about community acceptance.
Data center projects are encountering questions about electricity prices, water, noise, local hiring, tax incentives and the number of permanent jobs they create. Speakers said developers often arrive too late — after residents have encountered a project through social media or a public-hearing notice.
Curtis Harris of Compass Mining argued that developers should show up in communities “early and often,” well before a formal hearing. “It’s not you, it’s us,” Harris said, directing the criticism at the industry. “We’re the ones who need to be better.”
He cited a company outreach effort at an Iowa county fair that emphasized three claims residents could evaluate directly: the operation curtails when requested by the local utility, its mining machines use no water, and it hires local contractors and technicians.
Texas state Rep. Jared Patterson similarly argued that lobbying in Austin is not a substitute for local support. Industry participants need to explain the tax base, school funding, grid relationship and actual water design of a project in terms relevant to residents, he said.
The message was uncomfortable but consistent: the industry cannot assume that a technically sound project will receive political approval. Community engagement is not a communications exercise attached at the end. It is part of development.
That lesson applies equally to mining and AI. Residents may distinguish between the two technologies, but they often experience them in the same way — as large industrial loads seeking land, power and public consent.
What we took away from EIFThe forum did not produce a single blueprint for the mining industry’s next phase. It produced a set of tests.
Power is valuable, but only if it can be delivered on a commercially useful timetable. A mining site can become an AI site, but only if its cooling, connectivity, redundancy and location meet a much higher standard. AI contracts can stabilize revenue, but their financeability depends on the customer. Renewable generation can support compute, but intermittency and curtailment must be designed into the operating model. Texas can remain a compute center, but only if generation, transmission, permitting and local consent keep pace.
The miners best positioned for the next cycle may not be those that declare the largest AI pipeline. They may be the ones that classify their megawatts most honestly:
which sites should remain mines; which can support flexible or distributed compute; which justify full AI conversion; and which are most valuable as power-and-land assets sold or leased to someone else.That is a less dramatic story than every miner becoming an AI company. It is also a more investable one.
