In the fast-evolving world of artificial intelligence and cryptocurrency, a new kind of power struggle is emerging—one that's not just about market share or regulatory control, but about the literal engines keeping the digital revolution running. As AI-driven crypto investing surges and data centers multiply at breakneck speed, the demand for energy and the technology that supplies it is reaching historic highs, exposing bottlenecks and raising new questions about sustainability, infrastructure, and the future of digital finance.
At the heart of this transformation is the convergence of AI with digital asset management. Investors—both institutional giants and nimble startups—are leveraging advanced analytics to navigate the notoriously volatile cryptocurrency markets. BigBear.ai Holdings (NYSE: BBAI) stands as a prime example of this trend. According to Bloomberg, the company has seen its stock rocket by 314% over the past year, thanks to a series of lucrative AI contracts in defense and airport biometric projects. The excitement peaked in October 2025 when shares hit $9.39, before settling back to $7.05—a testament to the sector's wild swings.
BigBear.ai isn't just riding a wave of hype. The company boasts $390 million in cash and $380 million in pending contracts, offering a measure of stability. Yet, as The Block highlights, its 13× forward sales multiple signals sky-high expectations that may be tough to meet. C3.ai, another industry heavyweight, faces its own hurdles: a forward price-to-sales ratio of 7.8X and projected losses of $1.33 per share for fiscal 2026. These figures underscore a central dilemma: while AI is fueling innovation and optimism, sustainable growth remains elusive for many players, especially as competition from the likes of Palantir intensifies.
But the AI and crypto boom isn't just a story of financial metrics and stock charts. It's also about the physical infrastructure powering these digital dreams. As Tom's Hardware reports, the greatest threat to AI datacenter expansion in 2026 might not be a shortage of compute chips or capital, but jet engines—specifically, aeroderivative gas turbines repurposed from retired airliners. These turbines, now the backbone of mobile generator trailers, are being snapped up by data center developers desperate for fast-start, reliable power as they face years-long delays in securing traditional grid connections.
General Electric's LM6000 and LM2500 series turbines, both descendants of the legendary CF6 jet engine family, have become the default choice for hyperscale AI clusters. OpenAI's infrastructure partner, Crusoe Energy, recently ordered 29 LM2500XPRESS units to supply roughly one gigawatt of temporary generation for its Stargate project in West Texas—a mobile, jet-fueled grid in a field. ProEnergy, another major player, has delivered over a gigawatt of its PE6000 turbine systems to just two data center clients, repurposing engines once strapped to Boeing 767s to keep AI inference moving at full throttle.
Siemens Energy told Tom's Hardware that over 60% of its U.S. gas turbine orders are now linked to AI data centers, reflecting the sector's insatiable appetite for power. In states like Ohio and Georgia, regulators are greenlighting multi-gigawatt gas buildouts tied directly to hyperscale campuses, complete with new pipelines and phased interconnects designed for private-generation. Yet, the supply of turbines is running dangerously thin. Manufacturers are quoting lead times stretching into 2028 and beyond, with some developers reportedly paying $25 million just to reserve a future delivery slot. GE Vernova's CEO, Scott Strazik, warned in March that "by the end of the summer, we will be largely sold out through the end of '28 with this equipment."
Even as GE Vernova and Mitsubishi scramble to expand production, relief won't come before 2028 at the earliest. Unlike GPUs, turbines are massive, complex machines requiring high-alloy castings, precision heat treatment, and thousands of hand-assembled parts. Final testing can take weeks, and key components like blades and combustors have lead times measured in years. This bottleneck isn't just a headache for the tech sector—defense, petrochemical, utility, and offshore energy industries are all competing for the same finite supply.
The environmental impact of this power grab is also coming under scrutiny. While newer turbines are equipped with selective catalytic reduction and oxidation systems to scrub nitrous oxide and carbon monoxide, regulators remain skeptical. In Tennessee, Elon Musk's xAI supercomputer project—powered by dozens of methane turbines—has sparked community backlash and legal appeals. The Shelby County Health Department issued a permit for 15 turbines in July 2025 amid accusations that many more were already running without proper authorization. Mobile turbine units often escape pollution thresholds unless they operate beyond a 12-month "temporary" window, but with AI demand showing no signs of abating, many expect these engines to run for years, potentially outlasting their own useful lives and the public's patience.
There are broader implications for the energy grid, too. As data centers increasingly generate their own on-site power, they reduce reliance on public utilities—potentially shifting infrastructure upgrade costs onto other users and complicating long-term grid planning. While the U.S. government has earmarked billions for grid modernization and clean energy incentives, there's been little federal coordination around the turbine supply chain, a gap that now threatens to limit growth across multiple sectors.
Meanwhile, the crypto world faces its own set of challenges. Market volatility persists, with Bitcoin recently dipping below $110,000 due to ETF withdrawals and global tensions, despite the Federal Reserve's $7.4 trillion in liquidity support. South Africa's inflation-linked bonds are luring international investors amid economic reforms and 30% export tariffs imposed by President Donald Trump. On the regulatory front, Michael Selig's appointment to head the Commodity Futures Trading Commission (CFTC) marks a significant step toward unified oversight of digital assets, as reported by Bloomberg and The Block. IBM's Digital Asset Haven platform, meanwhile, exemplifies the growing institutional adoption of blockchain technology.
For traders, the risks and rewards remain as stark as ever. As covered by The Block, a major whale recently deposited $5 million USDC into Hyperliquid and shorted ETH with 10x leverage, highlighting both the opportunities and dangers of leveraged trading in the crypto markets. Platforms like Hyperliquid and Bybit offer leverage up to 40x and 500x, respectively—raising the stakes and the risks of liquidation, especially during periods of high volatility. Recent flash crashes have exposed system outages and failed stop-loss orders, compounding losses for traders and underscoring the fragility of leveraged strategies.
Despite these headwinds, the sector shows no sign of slowing down. Several gigawatts of new AI data center capacity are expected to come online in the U.S. soon, even as turbine shortages persist. Long-term solutions like small modular nuclear reactors and hydrogen turbines are being discussed, but for now, the future of AI—and by extension, much of the crypto infrastructure—is running on loud, dirty, and increasingly scarce repurposed jet engines.
As innovation and ambition continue to collide with the practical realities of supply chains, energy needs, and environmental concerns, the digital economy finds itself at a crossroads. Whether the industry can successfully balance rapid growth with sustainable execution remains an open question, but one thing is clear: the engines driving the AI and crypto revolutions are being pushed to their limits, and the world is watching to see what happens next.
