Power, Permits, and Pitfalls: Challenges in U.S. Hyperscale Data Center Development

Power Plant

Rapid growth in AI computing is driving unprecedented demand for hyperscale data center capacity, but this boom comes with significant strains on infrastructure and logistics.

The United States is experiencing a data center construction boom fueled by surging demand for cloud services and artificial intelligence (AI) workloads. Hyperscale data centers – massive server campuses often built for tech giants or colocation providers – are being planned and built at a record pace. Real estate investors and lenders have taken note of the attractive opportunities in this sector. However, beneath the optimism lies a complex web of risks and structural challenges that could undermine the success of these projects. From strained power grids and regulatory hurdles to rising costs and uncertain returns, developing large-scale data centers today requires navigating a multitude of pitfalls. This in-depth analysis examines the key risk areas and evolving challenges that lenders underwriting hyperscale data center infrastructure should carefully consider.

Surging Power Demand Strains the Grid

The electric power infrastructure has become a critical linchpin (and potential choke point) for new data center projects. The latest wave of AI-driven development is adding unprecedented load to the power grid, to the point where data centers are emerging as one of the largest drivers of new electricity demand in the U.S. In fact, recent industry projections suggest that data center facilities could account for up to 60% of all new power load growth in the United States through 2030, far outpacing demand growth from other sectors like electric vehicles or heavy industry. This stunning figure from Boston Consulting Group underscores how quickly digital infrastructure is scaling relative to legacy power capacity.

High-profile projects highlight the sheer scale of power needs for next-generation data centers. For example, Nvidia’s recently announced partnership with OpenAI – a $100 billion deal – aims to build at least 10 gigawatts (GW) of new AI-centric data centers. To put that into perspective, 10 GW could continuously power roughly 7–8 million U.S. homes, and it rivals the total generating capacity of some state electric grids. This single AI initiative exemplifies the outsized energy appetite of modern hyperscale developments. Many of today’s data center campuses plan for 100+ megawatts each, and future AI-focused facilities will house extremely power-dense server racks that draw far more electricity than traditional enterprise data centers ever did.

The strain on the grid is not just a future concern – it is already being felt. Goldman Sachs analysts have projected a 165% increase in data center power consumption globally by 2030 due to AI, and U.S. government forecasts indicate that data centers’ share of total national electricity usage could triple from roughly 4% in 2023 to as much as 12% of all U.S. power demand within the decade. Such growth represents the largest expansion of power requirements by a single sector in modern history. For utilities and grid operators, this surge creates immense pressure to deliver reliable power on time, and for data center developers and their financiers, it raises the stakes around securing energy supply.

Grid Bottlenecks and Mismatched Timelines

Hand-in-hand with soaring demand comes the challenge of grid bottlenecks and timing mismatches. Building a hyperscale data center is typically a two- to three-year endeavor from planning to completion. In contrast, upgrading regional power infrastructure – whether constructing new power plants, expanding transmission lines, or adding substation capacity – can take eight years or more from planning to execution. This fundamental disconnect in timelines has become a critical bottleneck for the industry. A data center might be ready to go live, but if the local grid can’t deliver the promised megawatts due to delays or capacity limits, that facility cannot ramp up its operations (or revenue) as scheduled.

This issue is already playing out in major data center hubs. Developers in regions like Northern Virginia (the country’s largest data center market) have encountered significant wait times to get adequate power hookups, because utilities must undertake multi-year grid expansions to support the new load. The result is often costly delays or limits on a center’s initial capacity. The mismatch also complicates planning: data center operators find themselves needing to secure power agreements and initiate electrical infrastructure upgrades years in advance of breaking ground on a new campus. If they don’t, they risk having a brand-new facility that sits partially idle, awaiting additional power feed.

For lenders, these power-related delays can translate to construction loans sitting longer in limbo and postponed cash flows once operational. Underwriting therefore must account for the risk of protracted power infrastructure projects and the potential need for bridge solutions (such as on-site generation or battery backups) to mitigate downtime. In some cases, developers are even coordinating directly with energy companies to co-develop solutions – for instance, by funding new substation work or entering into agreements to draw power from distant generation via dedicated transmission. The key point remains: the pace of grid improvement is not keeping up with the breakneck speed of data center demand, and that imbalance poses a structural challenge to timely project completion.

Site Selection and Regulatory Friction

In the rush to secure sites for new data centers, location has become a double-edged sword. On one hand, ideal sites need access to abundant power, fiber connectivity, and land. On the other hand, communities and regulators across the country are increasingly scrutinizing where and how these massive facilities get built. Local opposition and regulatory friction have emerged as significant risks in the site selection process, sometimes derailing projects entirely.

Community opposition to new data centers is on the rise, as local groups organize to block projects over environmental and quality-of-life concerns.

According to the MMCG database tracking industry trends, the number of community and activist groups opposing data center developments has surged dramatically in the past two years. By 2025, at least 142 grassroots advocacy groups across 24 states were actively mobilizing to block, delay, or impose stricter regulations on proposed data centers. This rising tide of resistance has had material impact: an estimated $64 billion worth of U.S. data center projects have been canceled or delayed since 2023 due to local pushback and permitting battles. In some cases, community objections have led to outright moratoriums or zoning changes that scuttle projects even after significant capital was spent on development plans.

The reasons behind the opposition vary, but several themes are common. Residents and local officials often raise concerns about noise pollution (from large-scale backup generators and cooling equipment), increased water usage (many data centers consume millions of gallons for cooling), strains on the electric grid (fearing that huge data center loads could lead to higher utility bills or outages for locals), and loss of open land or changes to neighborhood character (especially when farms or suburban tracts are converted to industrial tech use). Environmental groups point to the energy intensity of these facilities and their carbon footprint, while taxpayer advocates sometimes bristle at the tax incentives and abatements offered to data center developers as a cost to the community.

Notably, resistance is bipartisan and spreading to regions once considered data-center-friendly. Even in traditionally pro-business states like Texas and Virginia, there have been instances of county boards and state legislators pressing pause on unfettered data center growth. For example, parts of Northern Virginia – which for years welcomed data centers for their economic benefits – have seen residents organize to oppose further expansion citing quality-of-life impacts. In Texas, lawmakers have debated whether generous tax breaks for data centers are yielding enough public benefit. This patchwork of local politics means developers must perform careful due diligence on community sentiment and regulatory climate when choosing sites. Engaging early with local stakeholders and planning mitigation for issues like noise and water use are now essential steps in the development process.

For investors and lenders, regulatory and community risks translate to entitlement and timeline risks. A project might face protracted public hearings, legal appeals, or additional environmental reviews, all of which can delay construction starts or halt them altogether. Underwriting a data center project today requires an assessment of local permitting hurdles: Is the site zoned appropriately? Are there active community groups or recent controversies in the area? What is the stance of city or county officials toward data centers? These factors can heavily influence whether a project proceeds on schedule or at all.

Rising Capital Costs and Speculative Overbuild Concerns

Even as demand for data center space is sky-high, the economics of development have become more challenging in recent years. One major factor is the rise in capital costs. With the U.S. Federal Reserve’s interest rate hikes, the cost of borrowing money to finance large construction projects has jumped significantly. Data centers are extremely capital-intensive – a single hyperscale campus can cost several hundred million dollars (or more) to build – so higher interest rates directly increase debt service burdens. Higher cost of capital, coupled with general construction cost inflation, is squeezing project budgets and can threaten the feasibility of marginal projects. Lenders need to scrutinize pro formas with an eye to interest rate sensitivity: a build that made sense at 3–4% interest rates may look far less attractive at today’s higher rates, unless rents or other revenue have risen in tandem.

Compounding the issue, material and equipment costs have escalated. The specialized gear that goes into data centers – from advanced cooling systems to backup generators and, crucially, thousands of high-end computer servers – has seen price increases due to supply chain constraints and surging demand. Developers and tenants alike are experiencing “sticker shock” when budgeting for new AI-oriented facilities. According to industry reports aggregated in the MMCG database, market rents for wholesale data center space have climbed over 50% in the past five years in major markets. While this reflects robust demand (and helps offset higher costs), it also means tenants with expiring leases are facing steep rent hikes, and new entrants must be prepared for significantly larger up-front commitments to secure space.

Paradoxically, the current undersupply of data center capacity – as evidenced by record-low vacancy rates compressing below 5% and even touching ~2% in some prime markets – is encouraging a wave of speculative construction. Developers see that virtually everything built in the past few years has been quickly absorbed by hungry cloud and AI tenants. Industry forecasts from firms like JLL predict as much as $1 trillion in new data center investments by 2030 globally to meet demand. However, this exuberance raises the specter of a potential overbuild or “AI bubble.” If companies overestimate how quickly AI workloads will translate into revenue, or if cloud adoption temporarily slows, the result could be an excess of capacity a few years from now.

There are already cautionary signs: Some analysts have noted that the big cloud providers (hyperscalers like Amazon, Microsoft, Google) might scale back capital expenditures after the current build cycle, especially if economic growth moderates. A sudden pullback by one or two major tenants could leave developers holding empty (or less-utilized) facilities that were constructed on the assumption of ever-expanding demand. For lenders, the risk of speculative overbuilding means underwriting should include scenario analyses for slower lease-up or lower occupancy than the base-case. It may be prudent to favor projects that have anchor tenants committed or those in the most supply-constrained metros, while being cautious on purely speculative builds in secondary markets. In short, the data center sector’s boom is real, but history has shown that even high-tech real estate is not immune to cycles – prudent investors will remember the telecom/data center glut of the early 2000s and look to avoid financing the next wave of underutilized infrastructure if the AI frenzy cools.

Operational Risks: Cybersecurity and Cooling Infrastructure

Building a data center is only part of the challenge; operating it reliably and securely for decades is another. Hyperscale facilities concentrate enormous computing power and serve as critical hubs for business and society – which means the operational risks are significant if things go wrong. Two areas in particular stand out: cybersecurity threats and the demands on cooling infrastructure.

Cybersecurity is a growing concern for all digital infrastructure, and large data centers are prime targets. While the facilities themselves are usually not internet-facing, they house the servers that store and process valuable data for countless clients. A successful cyberattack on a major data center could lead to data breaches, service outages across multiple companies, or even physical damage (in the case of attacks targeting control systems). In recent years, the industry has seen a rise in complex attacks like distributed denial-of-service (DDoS) campaigns and ransomware that can indirectly impact data center operations or the customers within them. Moreover, because many data centers provide cloud and colocation services for multiple enterprises, they are part of a critical supply chain – if one is compromised, it can have ripple effects.

To manage these risks, operators are investing heavily in security measures. This includes both digital defenses (advanced firewalls, AI-driven network monitoring, encryption of data at rest and in transit) and physical security (24/7 onsite security staff, biometric access controls, hardened facility perimeters). Compliance frameworks such as FISMA, SOC 2, and ISO 27001 set baseline standards that many data centers must meet, especially when hosting government or sensitive corporate data. For lenders, a key takeaway is that robust cybersecurity and resilience investments are not optional – they are necessary operating expenses. When underwriting, it may be wise to evaluate an operator’s track record on uptime and security, and whether sufficient budget is allocated for ongoing security upgrades. A major breach or prolonged outage due to insufficient safeguards could lead to client departures and reputational damage, impacting the facility’s long-term cash flow.

Another operational minefield is cooling and thermal management. High-performance computing hardware (such as the GPUs used for AI training) generates intense heat in a compact footprint. Today’s AI data halls might support power densities of 30, 50, even 100+ kilowatts per rack, levels that far exceed what traditional air-cooled server rooms handled. Ensuring stable temperatures for this equipment is absolutely critical – overheating can result in automatic shutdowns or permanent hardware failures. Thus, data centers must deploy advanced cooling solutions, ranging from expanded HVAC systems and chillers, to new techniques like liquid cooling and immersion cooling where servers are cooled by liquids more efficiently than air.

The stakes for cooling infrastructure are high: if cooling systems fail, the data center can’t operate (servers will overheat within minutes). Additionally, cooling constitutes a major portion of a facility’s energy consumption. Efficient thermal designs (hot aisle/cold aisle containment, heat exchangers, etc.) are important to keep operating costs down and to avoid straining backup power during emergencies. There’s also a water usage aspect – many large data centers use water in cooling towers or evaporative cooling systems. In water-scarce regions, this has become a point of contention (as noted, some localities worry data centers will deplete water resources). Newer facilities are moving toward water-free cooling designs (using refrigerant-based systems or dry coolers) in response, but those can be more expensive to implement.

From an underwriting perspective, thoroughly evaluating a project’s cooling plan and redundancy is key. Does the design support the heat loads of tomorrow’s equipment? Is there N+1 or better redundancy on chillers and power for cooling? How will extreme weather (heat waves) be handled? Additionally, the operator’s plan for regular maintenance and upgrades to cooling systems should be considered – these systems can degrade over time, and an operator that reinvests proactively will preserve uptime better than one who defers capex. In sum, cybersecurity and cooling may not grab headlines like power and costs do, but they are foundational to a data center’s reliable operation and thus to the security of the investment.

Fragmentation, Power Partnerships, and Policy Patchwork

The data center industry’s rapid growth has also highlighted structural and regional inconsistencies that can pose challenges. The sector remains quite fragmented, with a mix of major players and numerous smaller operators, and a division between public hyperscale cloud firms and private colocation providers. This fragmentation means that market practices and capabilities vary widely across different operators. For instance, the largest tech companies – think of Amazon, Microsoft, Google, Meta – often build their own hyperscale facilities or lease entire buildings, and they have the capital and expertise to pursue innovative solutions (such as investing directly in power generation). In contrast, smaller and mid-sized data center developers may only operate a handful of sites and rely on more traditional approaches with local utilities and standard designs. Lenders should recognize that not all “data centers” are created equal in terms of backing and resilience: a project backed by a deep-pocketed sponsor with operational experience may carry less execution risk than one by a new entrant in this booming field.

One notable trend is the rise of public-private power partnerships in the data center world. To overcome the power infrastructure challenges discussed earlier, many hyperscale operators have begun striking deals directly with energy companies or investing in dedicated power sources. For example, some cloud providers have signed long-term power purchase agreements (PPAs) with renewable energy farms to ensure a supply of green power for their data centers. Others are going even further – a recent notable case saw a data center operator partner with a utility to restart a dormant nuclear reactor in Pennsylvania, solely to secure a large block of carbon-free electricity for its facilities. Companies like Microsoft and Google are exploring small modular reactors and advanced energy storage to support their future data center clusters. These arrangements can benefit developers by locking in power availability and price stability over decades, effectively de-risking a key input for data center operations. However, only the largest players can arrange such deals; smaller operators may not have the balance sheet or credit rating to negotiate similar partnerships. This dynamic could widen the competitive gap in the industry, as those with assured power supply can build with confidence, while others might struggle to obtain power on the same favorable terms.

Finally, the regulatory and permitting environment for data centers is highly uneven across U.S. states and localities. Some states actively court data center investments with tax incentives, streamlined permits, and supportive policies. For instance, states like Virginia, Arizona, and Texas have offered sales and property tax exemptions on data center equipment and expedited reviews, helping these areas become major data center hubs. The federal government has also signaled support – in 2025, an Executive Order was signed to accelerate federal permitting for data center infrastructure, aiming to cut red tape for these projects nationwide.

On the other hand, certain states and cities are introducing new regulations or oversight specifically targeting data centers. In states like Oregon and California, legislators have proposed requiring public utility commissions to study how large data centers affect residential electric bills and grid reliability. California has gone further in considering bills that would mandate data centers disclose their anticipated water usage and meet specific energy efficiency standards before approval. These emerging rules reflect growing public interest in the environmental footprint of data centers, but they also create potential compliance costs and uncertainties for developers. A design that easily met requirements in one state might need modification (or face delays) in another with stricter rules.

For lenders and investors, assessing the policy landscape is now a critical part of due diligence. A project in an “easy” jurisdiction with government incentives and community support will face fewer external hurdles than one in a jurisdiction with new environmental rules or organized opposition. The lack of a unified national approach means data center development outcomes can vary dramatically by location. In practice, this may entail adjusting financing terms (e.g. higher contingency reserves, longer construction loan periods) for projects in tougher regulatory environments, or even steering capital toward regions with more predictable conditions. Additionally, as the industry matures, we may see a push for more standardized best practices (perhaps through industry coalitions or federal guidelines) to smooth out some of these disparities. But until then, the motto for data center development must be “know your jurisdiction.”

Economic Outlook and ROI Uncertainties

Amid the technical and logistical challenges, there is a more fundamental question lingering over the current data center boom: Will the massive investment in AI and cloud infrastructure pay off as expected? The economic outlook for these projects is clouded by a degree of uncertainty, and recent studies suggest that many AI initiatives have yet to yield tangible returns. Lenders focusing on real estate tied to hyperscale data centers must therefore weigh not just the construction and lease-up risks, but also the end-user demand risk – essentially, are the tenants and end-clients going to profit from these AI endeavors, or could disappointment lead to cutbacks?

A widely discussed report from MIT in 2025 found that an astounding 95% of enterprise AI projects produced no measurable return on investment. In other words, despite companies pouring an estimated $30–40 billion into pilot AI programs (ranging from advanced analytics to generative AI deployments), the vast majority failed to significantly improve the bottom line or operations of those businesses. This “AI productivity paradox” doesn’t mean AI won’t eventually deliver value – many experts liken it to the early days of the internet, where transformational benefits took years to materialize – but it does serve as a warning. If companies large and small cannot monetize their AI experiments in the near term, they may slow their spending on AI cloud services or infrastructure. Since hyperscale data centers are being built largely to support exactly those AI and cloud services, a pullback in AI investment could translate to lower-than-projected utilization of new data centers.

Weighing against that pessimistic scenario is the fact that tech giants and cloud providers are still all-in on AI for the long run, and they have the deep pockets to weather some failed experiments. The current pipeline of data centers under development often has anchor tenants (like cloud operators or social media firms) with multi-year contracts, so in the short term many facilities will see stable cash flows. Yet, even some of those firms have faced pressure from Wall Street to justify the enormous capital outlays. Analysts have cautioned that if revenue from AI-driven services doesn’t ramp up soon, we could see an “investment pause” or more selective approach to new data center projects toward the end of the decade.

From a financing standpoint, the ROI uncertainty reinforces the need for prudent underwriting and risk sharing. Strategies might include requiring higher pre-leasing thresholds before funding construction (to ensure there are committed tenants, not just speculative demand), shorter lease structures with strong sponsors that can backstop performance, or even incorporating kick-out clauses in loans if certain milestones (like achieving a target occupancy or debt service coverage) aren’t met by a deadline. Essentially, lenders will want to avoid being left holding the bag if a data center goes unfilled or underutilized because the AI “boom” underperforms expectations.

It’s also worth noting the broader economic cycle: data center demand has some insulation from typical recessions (since internet usage and cloud services are fairly inelastic), but no asset class is completely recession-proof. An economic downturn could hit smaller tech firms or enterprise tenants and cause them to scale back expansion plans, indirectly affecting data center uptake. Additionally, higher interest rates (if they persist long-term) could dampen the appetite of even big players to keep spending at 2023–2025 levels. In summary, while the growth projections for hyperscale data centers are impressive, the path to monetizing those investments is not guaranteed. Lenders should adopt a healthy skepticism and build in cushions when evaluating the long-term viability and exit strategy for these projects.

Conclusion: Balancing Opportunity and Risk

The development of hyperscale data centers in the U.S. presents a classic high-risk, high-reward scenario for real estate stakeholders. On one hand, demand drivers like AI, cloud computing, and digital transformation are megatrends that point to strong need for more data infrastructure. Modern society’s dependence on data and connectivity suggests that well-located, well-run data centers will remain valuable assets for years to come. On the other hand, this analysis makes clear that the road to delivering these projects is fraught with challenges – from securing enough power in time, to managing community relations, to controlling costs in a heated construction market, and ensuring the end uses actually deliver economic value.

For U.S.-based real estate investors and lenders, the priority should be an analytical, eyes-wide-open approach to underwriting hyperscale data centers. That means rigorously vetting power agreements and capacity (a data center without power is just an empty shell), building in extra time and budget for potential delays, understanding the regulatory context of the chosen site, and requiring that operators have solid plans for security and operations. It also means structuring deals conservatively – for instance, not over-leveraging based on rosy occupancy assumptions, and perhaps pricing debt to reflect the construction and operational risks unique to this asset type.

The evolving challenges outlined – power grid strain, timing mismatches, activist pressures, rising capital costs, operational complexities, fragmentation, and ROI uncertainties – are not insurmountable. In fact, each challenge is prompting innovations and adaptations: utilities are exploring faster ways to add capacity (and even reviving nuclear plants for data center loads), developers are engaging communities earlier to find win-win outcomes, new cooling and energy technologies are coming online to improve efficiency, and investors are learning to be more discerning amid the hype.

In the end, successful navigation of these issues will separate the winners from the also-rans in the data center real estate boom. Lenders who grasp the nuances of hyperscale infrastructure and underwrite with discipline will be better positioned to capture the upside of this digital revolution while mitigating downside exposure. The opportunity is vast – but so are the pitfalls, and only a well-informed, balanced strategy will ensure that investments in this space achieve their promised potential.

October 02, 2025, by a collective authors of MMCG Invest, LLC, (retail/hospitality/multi family/sba) feasibility study consultants.

Sources:

• MMCG database – Utilities & grid capacity: IBISWorld, Utilities in the US (Mar-2025)

• MMCG database – Colocation market structure, margins, cost stack: IBISWorld, Data Center Colocation Services in the US (Sep-2025)

• MMCG database – Power demand & grid bottlenecks: Boston Consulting Group analysis on data-center power demand growth and upgrade lead-time mismatches (power upgrades ~8+ years vs. 2–3 years build cycles).

• MMCG database – Vacancy, rents, $1T pipeline & planning windows: JLL North America Data Center Outlook (2024–2025 editions): ultra-low vacancy (~2–3%), 50%+ rent growth since 2019/20, tenants securing capacity 18–24 months in advance, and cumulative capex outlook approaching ~$1T by 2030.

• MMCG database – AI power trajectory: Goldman Sachs research (2024–2025) on data-center electricity demand rising ~165% by 2030; U.S. DOE estimates of data centers’ share of total U.S. electricity use potentially reaching ~12% this decade.

• MMCG database – Anchor transactions / power procurement:

  • Microsoft–Constellation arrangement to restart a Three Mile Island unit for ~835 MW dedicated to data-center load.

  • Meta–Entergy Louisiana power arrangement supporting a ~4 MSF campus.

  • Hyperscaler PPAs and emerging nuclear/SMR strategies for long-term price/availability hedging.

• MMCG database – Project scale & financing: Coverage of the Nvidia–OpenAI development partnership (~10 GW ambition) and the Abilene, TX “Stargate” initiative (OpenAI/Oracle/SoftBank) including reported multibillion-phase financing.

• MMCG database – Construction surge: Associated General Contractors (AGC) indicators showing data-center construction growth outpacing U.S. nonresidential peers (2023–2025).

• MMCG database – Community opposition & permitting risk: Data Center Watch (10a Labs) compilation indicating ~$64 B of projects blocked or delayed over ~two years; mapping of 142+ activist groups across 24 states and 40+ campaigns in Northern Virginia.

• MMCG database – Cyber risk:

  • Cloudflare DDoS Threat Reports (2024–2025) detailing triple-digit YoY growth in attacks.

  • Continent 8 quarterly incident stats (e.g., “carpet-bombing” events).

  • Regulatory/compliance frameworks referenced (FISMA, SOC 2, ISO-27001, HIPAA, PCI-DSS).

• MMCG database – ROI uncertainty in enterprise AI: MIT/Sloan research (2025) reviewing 300+ public AI initiatives; ~95% reporting no measurable ROI despite $30–40 B in spend.

• MMCG database – Policy landscape:

  • Federal actions to accelerate data-center permitting (2025 EO).

  • State-level measures (e.g., CA/OR/OH) on water-use disclosure, energy-efficiency and rate-impact studies; incentive regimes in VA/TX/AZ for sales/property tax relief on qualifying equipment.