Jill Ford didn’t come to Bitcoin mining for speculation—she came to it for sovereignty. After discovering the economic power of Bitcoin, she founded BitFord Digital to prove that mining could be both profitable and principled.
Today, Ford is a vocal advocate for financial literacy and access, using her platform to educate marginalized communities on cryptocurrency’s potential to break cycles of economic disenfranchisement, while also championing diversity and women’s leadership in tech.
In this Q&A, she offers a clear-eyed view on mining economics, the growing overlap between Bitcoin and AI infrastructure, and why not every trend is worth chasing.
With Bitcoin prices and mining rewards fluctuating, do you see Bitcoin mining becoming less profitable, and how are miners adjusting to these market pressures?
Ford: Mining has always been cyclical. Anyone who’s been in the crypto space for any amount of time knows volatility isn’t new, but the margin structure is. As difficulty rises and halvings compress rewards, inefficient operators get squeezed faster. What we’re seeing now is a sharper divide between miners who treat this as a short-term trade and those who build for long-term resilience.
The adjustment requires sophistication. Miners are optimizing firmware, locking in smarter power contracts, deploying behind-the-meter strategies, and increasingly monetizing flexibility. The days of “plug in and hope” are over.
Several prominent Bitcoin mining companies are leveraging their existing power infrastructure, including Core Scientific, CleanSpark, Bitfarms, Riot Platforms, Iren, Hut 8, TeraWulf, and Marathon Digital, to meet the massive demand for high-performance computing (HPC) for AI workloads, often signing large contracts with AI firms like CoreWeave. Could Bitcoin mining expertise in hashpower optimization translate effectively to AI computing operations, or are these fundamentally different skill sets and is this something BitFord is exploring?
Ford: I think what you’re seeing with companies like those makes sense for them. They already control massive power infrastructure, they have the balance sheets to absorb risk, and they can sign long-term contracts with AI firms that want certainty and scale.
But Bitcoin mining and AI computing aren’t the same business even though we share some hardware DNA.
Mining teaches you a lot about power, cooling, and running infrastructure efficiently at scale. That part absolutely translates. Where it stops translating is on the compute side. AI workloads care about latency, uptime guarantees, orchestration, security, and SLAs in a way mining just doesn’t. Miners think in megawatts. AI customers think in milliseconds.
At BitFord, we’re pretty clear-eyed about that. We’re not chasing AI just to “save” mining margins. Repurposing infrastructure only works if the workload actually fits the site and the operating model. Forcing mining facilities into AI data centers because it looks good on a slide deck is a recipe for getting burned.
Bitcoin mining is still our core because it’s incredibly flexible. It can turn on and off, respond to grid conditions, and operate without long-term dependency on a single customer. AI compute is the opposite. It wants permanence and priority. There may be places where the two overlap, but we see AI as a selective opportunity, not a pivot.
What challenges or advantages does your existing infrastructure—cooling systems, power contracts, and data centers—offer when supporting AI workloads?
Ford: It’s pretty straightforward. Miners are very good at managing large amounts of power. They know how to source it, move it, and use it efficiently.
The challenge is that most mining sites were designed to turn on and off as needed. AI doesn’t work that way. It needs steady, always-on power and more advanced cooling. You can upgrade mining sites to handle that, but it’s expensive and doesn’t make sense everywhere.
The bottom line is that while some mining facilities can support AI not all can. You need to be clear eyed about your capabilities and not chase after AI for the sake of the chase.
As Bitcoin miners shift toward higher-power computing for AI, how does BitFord maintain its commitment to sustainability and ethical energy use?
Ford: For us, the concept of sustainability is just how we decide whether something makes sense or not. We look at where the power comes from, how it affects the local grid, and whether the community actually benefits.
If a project puts strain on the grid or drives up electricity costs for the people who live there, that’s not progress. That’s just shifting the burden onto someone else and it’s not something we’re very interested in doing.
How do you balance increased energy demand for AI workloads with local grid capacities, and do you foresee any risks of blackouts or rising electricity costs for consumers?
Ford: When compute growth isn’t thought through, it creates real problems. It goes beyond blackouts because it can translate into higher electricity bills showing up month after month for people who had nothing to do with the decision.
The responsible way to build is pretty straightforward. Be flexible with load. Use behind-the-meter power where it makes sense. Work with utilities instead of surprising them. Compute infrastructure should soak up excess energy when it’s available, not fight communities for power they need.
When that balance gets ignored, regulators step in. That’s something we should all be looking to avoid.
Can you share updates on the Hash Over Cash initiative—how it’s evolving and what real-world outcomes you’ve seen for workforce reentry programs?
Ford: Hash Over Cash was an exploratory initiative intended to test how mining-enabled incentives could support workforce reentry and transitional employment programs. While the concept resonated and sparked valuable conversations, it hasn’t yet advanced into a sustained implementation phase.
Right now, the focus has shifted to other priorities, but the core idea of using infrastructure-driven models to create real economic pathways for reentry populations continues to inform how I think about impact-led innovation. I’d absolutely be open to revisiting or evolving the concept in the future under the right conditions.
Do you see potential for programs like Hash Over Cash to be applied in AI infrastructure development, bridging technical training with new technology demand?
Ford: I do see real potential there. The demand being created by AI infrastructure across data centers, energy systems, and technical operations creates a natural opportunity to pair skills training with real-world deployment.
That said, programs like this require strong ecosystem support to move from concept to execution. It takes committed partners, clear operational backing, and long-term alignment to bridge training with emerging technology demand in a meaningful way. With the right level of collaboration and investment, models like this could absolutely play a role in the AI infrastructure build-out.
Looking forward, do you see the Bitcoin mining industry and AI infrastructure sector converging, or will miners remain primarily crypto-focused with AI as a secondary application?
Ford: It’s an interesting question. I think there will be convergence at the infrastructure layer but not at the business model layer. Bitcoin mining remains uniquely valuable because it’s permissionless, flexible, and financially sovereign. AI infrastructure is centralized, contract-driven, and capital-intensive. Some operators will straddle both, but I think in the end most will specialize.
Do you anticipate an AI bubble bursting in 2026?
Ford: Unfortunately, yes. Parts of the AI market are clearly overheated. Compute demand is real, but expectations aren’t always grounded in revenue. We’ve seen that movie before and we’ll likely see a correction in 2026. My hope is that when it happens, it is not an out-and-out collapse with all sorts of secondary, macro-economic impact, but more of a culling. As we’ve seen in the past, the companies that survive will be the ones that built fundamentals, not narratives.
Source: https://crypto.news/bitcoin-mining-ai-jill-ford-margins/
