The drop in the unemployment rate was not because more people found new employment but because over 200,000 unemployed people left the labor force last month and stopped looking for work.

The labor market remains lukewarm as job openings, layoffs and resignations remained largely unchanged in May according to BLS’ data. While the rate of unemployment remains low overall, the slow labor market is affecting one group in particular: new college graduates.

As college graduation season ends, many graduates are struggling to enter the workforce. Their topline unemployment rate, officially called the U-3 rate, rose to  5.3% in April, an increase from the January 2025 rate of  4.7%. The U-3 rate is the percentage of the labor force that is unemployed. 

The U-6 rate, commonly called the underemployment rate, includes unemployed workers plus involuntary part-time workers and discouraged workers. The U-6 rate for new college graduates has risen faster than their U-3 rate. Since January 2025, the U-6 rate increased from 8.2% to a high of 10% in April.

The chart below shows both the U-3 and U-6 rates by race:

The increase in the U-6 rate suggests that a portion of new college graduates are turning to part-time and gig work as suitable full-time work becomes harder to find. Fortune Magazine reported on new college graduates turning to gig and entrepreneurial work as entry-level job openings have declined while the number of applicants for the remaining jobs has increased. This has led some to pursue work outside of their formal areas of study. According to data from the Federal Reserve Bank of New York, 41.5% of recent college graduates work in a job that doesn’t require a college degree. 

Breaking down the data by race reveals a couple of interesting trends. First, both the U-3 and U-6 rates are higher for Black and Hispanic graduates compared to White graduates. The unemployment rate for Black graduates peaked at 12.3% in November of last year and then declined by over 5 percentage points (pp) to 6.9%, while the underemployment rate declined only 2 pp over the same period. Despite this decline, Black underemployment remains elevated compared to the beginning of 2025. Similarly, the U-6 rate for Hispanic college graduates has been steadily increasing since mid-2022.

A second important finding from the data is that not only are Black and Hispanic college graduates’ unemployment rates rising, but they are substantially higher relative to White graduates. The Black grads U-3 rate reached a low of 3.3% in March of 2024 and then experienced a spike to 6.9% in April, a 110% increase. For Hispanic grads, their U-3 rate increased by 80% from a low of 4.1% in January of 2025 to 7.3% in April. For White grads, their U-3 rate increased by only 36% from an October 2022 low of 3.18%.

While media attention has focused on unemployment among new college graduates, and rightfully so, it is more endemic for Black and Hispanic graduates. For college graduates overall, the reason for their employment woes has been broadly attributed to a combination of broader labor market weakness and AI changing the hiring decisions of companies. 

Firms facing higher costs, due in part to tariffs, are hiring fewer workers, including recent college graduates. Some of the layoffs result from poor management decisions in the past. For example, some companies over-hired in the post-pandemic boom and have now begun layoffs. These experienced unemployed workers are sometimes competing for jobs alongside new college graduates. These broader labor market trends are negatively impacting job hiring for all workers, including for recent college graduates.

While companies, particularly tech firms, have announced tens of thousands of layoffs this year, the biggest challenge for new entrants to the labor market is the drop in entry-level hiring. Firms are adopting a wait-and-see approach to AI by holding off on hiring junior workers until they better understand the capabilities of AI systems and who they can replace. Additionally, companies that are leaning into AI investments are letting workers go to free up capital for AI spending.

For recent Black and Hispanic college graduates, AI introduces another challenge – algorithmic discrimination. A study from Stanford University found that AI screening tools systematically discriminate against Black applicants. Research from the University of Washington has found that AI resume screening tools can show bias based on an applicant’s name. The tools they reviewed recommended applicants with White-associated names 85% of the time compared to only 9% for applicants with Black-associated names. 

When an AI underwriting algorithm is primarily trained on data from a pool of mostly White applicants, it can favor white candidates to the detriment of Black and Hispanic qualified applicants. A dataset of interactions between biased bank branch loan officers and applicants seeking a small business loan might produce an algorithm that reflects biases of the loan officers. Thus, AI can amplify existing systems of discrimination.

The labor market for recent college graduates is weak not only because of structural reasons like high costs and post-pandemic over-hiring but because of the AI shock. Declining entry-level job hiring is fueled by this dynamic. For non-White college graduates, potential discrimination from AI algorithms, in addition to the AI-related job hiring freezes, is directly affecting their ability to enter the workforce. The labor market is bad for recent college graduates. For Black and Hispanic grads, it’s even worse. 

Joseph Dean is the Racial Economic Research Specialist with NCRC’s Research team.

Photo credit: Safari Consoler via Pexels.

Despite the positives in the April jobs report released by the Bureau of Labor Statistics (BLS), closer scrutiny of the data reveals ongoing weaknesses in the labor market. An examination of the employment situation facing Black men helps elucidate these negative trends, including their falling labor force participation rates, sluggish job growth and rising long-term unemployment. 

The BLS defines a worker as unemployed if they have actively looked for a job within the previous four weeks. A more expansive definition of unemployment includes part-time workers who seek but can’t find full-time work and those who want a job but have not actively looked for work because they believe no quality positions exist. The BLS also tracks this expanded definition of unemployment, formerly called the U-6 rate or underemployment rate. 

The chart below shows the underemployment rate by race and sex from 2022 to the present:

The underemployment rate increased throughout the first 3 quarters of 2025, then declined during the 4th quarter of 2025 and during the 1st quarter of 2026. One would assume that more people are moving from underemployment to employment. 

Unfortunately, this assumption is not true for Black men, with the labor force participation rate shown below explaining the reasons behind this trend:

While the number of unemployed Black men declined, so did the number of Black men in the labor force. We can see this in the chart above which shows that their labor force participation rate also declined over this same period. This suggests that, rather than more Black men finding employment, many are simply leaving the labor market entirely.

Given that these were working-age men, one could assume they are not leaving the labor force due to retirement but rather due to feelings of discouragement or an inability to find work. In fact, the number of employed Black men over 20 years old has declined by roughly 650,000 since November 2025.

This pattern of declining labor force participation and underemployment is unique among Black men. The labor force participation rate for all other groups held constant or increased, while the Black male labor force participation rate declined over 2025 and early 2026.

One explanation for why increasing numbers of working age Black men are leaving the labor force could be that their largest sectoral employer, logistics, is experiencing a multi-year slump. Due to changes in freight demand, tariffs and rising costs, the logistics sector has seen virtually no job growth since the summer of 2022. Furthermore, just one year since President Trump announced his tariff/trade war, the transportation and warehousing sector has lost almost 90,000 jobs, including 22,000 truck drivers and 50,000 warehouse positions.

These job losses will only worsen as the energy crunch from the Iran war continues to spike fuel prices globally. The jet fuel shortage has already led to the closure of Spirit Airlines. The transportation sector will experience more job losses and bankruptcies if the situation doesn’t change, with many of the losses impacting Black men. 

One area where these job losses are showing up is in the rise of the long-term unemployed as shown in the chart below: 

The share of the unemployed who have been jobless for longer than 27 weeks is now over 26% and continues to rise as illustrated by the chart above. This has pushed the average number of weeks people are unemployed to roughly 25 weeks. Among the number of unemployed Black men, 30% have been jobless for longer than 27 weeks, the highest of any racial/ethnic group.

The employment situation of Black men highlights several growing issues facing workers overall, such as rising long-term unemployment rates and heavy job losses across multiple sectors. While policies that uplift Black men specifically have become politically toxic, measures like ending the tariff/trade war and expanding unemployment benefits (which was done during the COVID-19 pandemic) can help all workers, including Black men.

Joseph Dean is the Racial Economic Research Specialist with NCRC’s Research team.

Photo credit: Mukhtar Stuaib Mukhtar via Pexels.

Furthermore, in each of the last 13 months, job numbers have been revised down, totaling over 700,000 jobs lost. This past December alone, job gains were revised downward by over 60,000 to -17,000 jobs. This means that the jobs market contracted in 5 out of the last 9 months – hardly a sign that a turnaround is imminent.

With hiring at a virtual standstill, less than 16% of workers plan on leaving their jobs for greener pastures. Pay growth for those who decided to change jobs fell to its lowest rate since 2021. One could say that the grass isn’t as green as it once was on the other side.

The unemployment rates for Black and Asian workers also rose 7.7% and 4.8%, respectively. For Asian workers, this represents a multi-year high. Despite these increases, the overall unemployment rate has stayed below 4.5% for over 2 years, largely due to the low but stable unemployment rate for White Americans.

A new report from AI company Anthropic analyzed the impact of AI on jobs and its automation of certain tasks. It found that the profile of the worker most exposed to AI displacement are often older, highly educated, well-paid women. The report adds to the growing research showing that women are significantly more at risk of AI-driven job displacement than men. Beyond the implications for gender equality, the report finds that for young workers slow hiring rather than layoffs is the biggest problem they face. 

Despite predictions from AI leaders about the technology’s existential impact on employment, especially for entry-level jobs, most companies have not seen a demonstrable impact from AI. According to a survey of 6,000 CEOs of US and European companies, over 80% reported no positive impact on employment or productivity via the emergent technology. Bridgewater Associates has made a similar point that AI capital expenditures will have little impact on the labor market. Nevertheless, unemployment among new college graduates shows no signs of decreasing, as internship opportunities and entry-level work dry up in some cities, with whispers of AI as the culprit. 

On the last day of February, the United States, in collaboration with Israel, launched a series of airstrikes on Iran. In response, Iran effectively closed the Strait of Hormuz, a narrow passage of water that 20% of the world’s oil passes through. As a result, crude oil prices jumped by 25%, with gasoline prices rising 17% in the United States alone. Though the war has no clear end in sight (nor a clear rationale), the consequences for ordinary Americans could be severe. Beyond oil prices, food and airline fares could rise as fuel costs increase. Additionally, the war has put a drag on the stock market, in which tens of millions of people’s retirement accounts are invested. 

So far, the labor market remains frozen, with low unemployment rates being the only saving grace. Only time will tell if this will be the new normal or a prequel to an impending horror show. One indicator to watch though is the direction of job openings, with the next release of that data coming in a few weeks. In the meantime, all eyes will be on consumer prices as the war with Iran and the President’s 15% global tariffs collide, potentially putting a tremendous strain on ordinary people’s wallets.

Joseph Dean is the Racial Economic Research Specialist with NCRC’s Research team.

Photo credit: RDNE Stock project via Pexels.

While the diffusion index increased, it only reflects industries that gained at least one job. In January, as with all of 2025, the healthcare sector accounted for the bulk of the job gains. Additionally, the unemployment rate declined last month, with both the average duration of unemployment (23.9 weeks) and the percentage of people who have been unemployed for 6 months or longer (25% of all total unemployed) remaining elevated.

BLS’s most recent jobs report featured an updated methodology resulting in 11 out of 12 months in 2025 having revised job gains that were less than previously published. We can expect January’s job gains to be revised downward, possibly below 100,000. Additionally, job openings dropped precipitously in December and were down by over 1 million openings from September.

The slowing job market has been devastating for new college graduates. According to Goldman Sachs, previously high-demand industries, such as the information technology and finance sectors, that have historically employed the largest number of college graduates lost about 9,000 jobs per month between 2023 and 2025. Before the COVID-19 pandemic, those industries were adding about 44,000 jobs a month.

While new college graduates are facing a difficult time, so too are Black women with college degrees. In 2025, Black women had the largest drop in their employment-to-population ratio compared to other racial groups. However, among Black women, those with bachelor’s degrees had the steepest declines. The largest losses came from the public sector, including the federal government, where over 270,000 Black women lost their jobs. Black women bore the brunt of the DOGE cuts last year as well. 

Whether last month’s BLS job reports numbers are a fluke or a sign that the labor market is experiencing a turnaround still remains unclear. Both job openings and consumer spending declined in December, thus the answer is likely closer to the former. Nevertheless, next month’s jobs report will provide clues as to what direction the economy will take in the coming months.

Joseph Dean is the Racial Economic Research Specialist with NCRC’s Research team.

Photo credit: nappy via Pexels.

As the race for artificial intelligence (AI) has accelerated, communities – particularly those in rural and disadvantaged areas – find themselves at the center of the technology’s future. On the one hand, data centers potentially offer an influx of capital investment, demand for labor and additional tax revenue to help revitalize local and regional economies. 

However, data centers also come with distinct costs, namely rising water and energy costs, increased strain on utilities infrastructure and environmental degradation and pollution that can have significant ramifications for public health. With capital expenditures on data centers expected to continue to increase this year after unprecedented levels of investment in 2025, it is critical that community-based organizations, local governments and residents understand the tradeoffs of data centers as well as the levers at their disposal to ensure construction happens (or doesn’t) on their own terms. 

In the following article, we will provide an overview of what data centers are, explain what’s driving the rush to build them and analyze what geographical areas tend to be most vulnerable to the rapid expansion of data centers. We will also discuss strategies and policy levers community leaders have to ensure data center projects lead to equitable community development. 

What is a data center? 

Data centers are physical buildings housing file servers and networking equipment that can store, process and analyze various data sources including text, images, code and other information. Data centers house the infrastructure needed to run the computer algorithms behind programs like ChatGPT. While more recent advances have been driven by AI, data centers have been an important part of the modern digital economy for many years, helping to support internet connectivity and large software systems often referred to as the “cloud”.

Most data centers house servers (connected computers) and storage systems capable of vast numbers of calculations and computing applications. There are several general categories of data centers to be aware of: 

• Micro data center: The smallest recognized data center is generally used by single companies or for remote offices. Micro data centers usually exhibit a capacity of 10 server racks or less, which equates to a total capacity of approximately 140 servers. Micro data centers typically occupy less than 5,000 square feet of space and draw on no more than 100 – 150kW of energy.
• Small data center: Small data centers typically require between 5,000 – 20,000 square feet of space and may host anywhere from 500 to 2,000 servers, drawing on around 1 – 5 MW of energy.
• Average data center: The average onsite data center typically has between 2,000 and 5,000 servers. Its square footage could vary from between 20,000 square feet and 100,000 square feet with an energy draw of around 100 MW.
• Hyperscale data centers: The International Data Corporation (IDC)’s definition of a true hyperscale data center states that the facility should contain at least 5,000 servers, occupy at least 10,000 square feet of physical space, and draw on over 100 MW of energy.

The recent drive in construction has primarily focused on hyperscale data centers because they have enough capacity to run energy-intensive AI services and training processes. As such, our focus in the remainder of the article will be on hyperscale data centers. 

What’s driving the rush for hyperscale data center construction? 

In November 2022, ChatGPT took the world by storm, followed closely by a slew of similar products all driven by a new form of AI called large language models (LLMs). With remarkable speed and novelty, ChatGPT and its peers (i.e., Anthropic’s Claude, Google’s Gemini, etc.) are able to handle more complex inquiries from users and respond with personalized answers in a matter of seconds. Over the last couple of years, the models driving these tools have become more efficient and accurate while also expanding to new features like image and video generation. The resulting scramble to innovate and create the dominant AI product is expected to involve trillions of dollars of global investment. 

As tech companies compete for users and investors, their executives are not shy about their ambitions to reshape society via the new technology. From curing cancer to solving climate change, it would appear as though AI is the silver bullet to all the world’s problems according to the executives leading the charge. The most ambitious objective is the pursuit of artificial general intelligence (AGI), or superintelligence, models that would either rival or exceed human capabilities. While progress toward a technology of this caliber remains unrealized and overhyped for the time being, the AI arms race has exploded in earnest.

To improve and service current AI models, tech companies have three key constraints: data, compute and energy. Data is what allows software engineers to improve AI models through a process called training. Training AI involves feeding data into a model to “teach” it to respond to different stimuli. The actual mechanics of this process are less important than the main takeaway: tech companies need a solid infrastructure and ample energy as well as the data to continue improving AI. 

Data

In the digital age, data is abundant and widely available to Big Tech companies. From ordering a product on Amazon to liking a post on Instagram, all of our interactions online contribute to our digital footprints. For behemoths like Microsoft, Amazon and Google – the companies that are largely driving the investment in AI – data is easy to come by for two main reasons. First, they own many of the most dominant apps we all use on a daily basis. Second, any data these companies want but do not have direct access to can often be purchased. 

An entire sector of so-called “data-brokers” have created markets for the buying and selling of data. Due to the lax digital privacy laws in the United States, the companies who develop and own the websites we visit, the apps we scroll on and the streaming services we watch not only collect our information but often have a right to sell that data to other firms. Furthermore, using published works to train AI models has revealed grey areas in copyright law. All this amounts to an abundance of data that tech companies can use to train and improve their AI models. 

Compute

However, training AI models requires more than just data. It also requires the computational infrastructure needed to process it, often referred to as compute. Data centers house that equipment as well as the systems needed to ensure they run safely and properly. AI models also need compute power to maintain their current services. Every query into ChatGPT requires the digital infrastructure in a data center to execute the request of the user. 

As companies push to increase the number of users, their computational demands have increased exponentially in order to fulfill all of the search queries and other tasks AI models have become tasked with. As the race to innovate hastens, Big Tech companies’ quest for AI innovation and expansion hinges on their ability to construct data centers. As a result, they have invested heavily to build large, high capacity hyperscale data centers across the country as quickly as possible.

Energy

The final piece of the puzzle is obtaining the energy required to run a data center. Because they are basically warehouses filled with computers that are running all day every day, data centers consume vast amounts of energy. Federal researchers project American data centers could double, or even triple, their electricity usage by the end of this decade, going from roughly 4.4% of national electricity sales to upwards of 9-12%. 

By 2030, the US may consume more electricity for data processing than it does to manufacture all its steel, aluminum, cement and other energy-intensive goods combined, demonstrating the sheer amount of energy needed to meet the demand. The cost of electricity and the current state of grid infrastructure has become one of the top considerations for tech companies when deciding where to build a data center. Communities who will be impacted by data center construction are similarly on alert for how data centers will impact their electricity bills as well as their pollution-related health and environmental impacts.

Location, Location, Location: Where Are Data Centers Built and Who Is Most Affected? 

Where data centers are built matters. Hyperscale data centers house the compute power needed to build the future of AI, but their presence does not come without consequences. Community advocates and residents resisting data center construction in their backyards raise a number of issues with the potential and realized effects data centers can have, including rising electricity bills, environmental pollution and large tax incentives for firms without an economic benefit to community members. This raises important questions about what areas of the country are most vulnerable to data center construction proposals. Based on data from the FracTracker Alliance and the American Community Survey, we found that there are certain areas of the country where data center construction tends to occur. 

Figure 1 shows the states where small and medium-sized data centers tend to be concentrated in. Virginia, Texas, Georgia and Pennsylvania are among the states with the greatest number of data centers currently operating. Similarly, Figure 2 shows that these four states are also among the leading locations for hyperscale data center operations. However, Texas and Georgia appear to be leading in hyperscale data center development, surpassing Virginia. 

The hyperscale data center construction trends bear both similarities and differences to data center construction more broadly. States like Texas and Georgia are represented at the top in both categories, whereas Michigan has a greater focus on hyperscale data centers. This could represent the changing policy environment for data centers more broadly. Some states are making an intentional effort to attract hyperscale data centers and compete with states that have historically been friendly to data center development. 

It is important to note that the publicly-available, crowdsourced data from FracTracker Alliance is incomplete and under-representative in several areas of the country compared to other maps based on private data, such as California and various states throughout the midwest. Companies go to extensive lengths to mask the locations of data centers and the names of the operators, and the availability of comprehensive data locating data center builds remains a key limitation of efforts to analyze construction and operation trends. 

What We Know About Data Centers and Community Benefits

When data centers are proposed, companies often tout their community benefits: increased property taxes for local schools, short and long-term job growth, improvements to local infrastructure and economic activity that supports small local businesses. However, it is important for community members to remain vigilant when faced with such promises. The impacts of the most recent push for hyperscale data centers have not always lived up to the promises made before construction was approved. These failures to deliver for residents are especially clear when accounting for costs to taxpayers in the form of tax breaks and energy bills. 

Data centers are often pitched as boons to local labor markets, creating well-paying long-term jobs in high-demand industries such as security, operations and information technology (IT). They also provide short to medium-term job opportunities for construction workers, electricians, plumbers and other skilled tradespeople who are needed to build them. However, the long-term benefits beyond the construction phase are less clear. 

Generally, as more data centers have gone online, there has been a corresponding increase in people working in them. At a national level, employment in data centers increased more than 60% from 2016 to 2023, growing from 306,000 to 501,000 jobs. A  2017 report sponsored by the US Chamber of Commerce Technology Engagement Center estimated that a typical data center employs around 1,700 local workers during the construction phase but only about 150 in the years following. Even so, data centers may have downstream effects supporting jobs at other firms. The Data Center Coalition, the trade association representing the data center industry, commissioned a report showing that from 2017 to 2021, each direct job in the data center industry supports more than 6 jobs elsewhere in the US economy. 

However, these estimates involve both the economic impact of income earned in the data center industry as well as spending across the entire supply chain. This means that those 6 added jobs are probably not in the area where the data center was built and, therefore, do not provide a direct community benefit. Moreover, the jobs that data centers do create locally are typically low-wage, term-limited, non-technical positions, such as security, maintenance and janitorial roles. These roles are often filled by contractors rather than full-time employees, meaning they lack union protections, health benefits and job security.

The disparity between short and long-term job growth as well as the quality of long-term employment opportunities highlights the issue with characterizing data centers as beneficial for workers. Unlike manufacturing or distribution facilities of comparable size that produce or store goods and require human labor to function, most of the “work” in a data center is being done by the computer systems and servers housed within them. In this sense, data centers are more akin to traditional infrastructure projects like highways or bridges that have large upfront costs and provide value through their presence rather than the jobs they create in the long run. 

Although data centers do not create much job opportunity for local communities, the handful of long-term jobs they do offer could make a big difference in small towns. In these cases, the question becomes whether or not the benefits of those local jobs outweigh the costs of making the project happen in the first place. Increasingly, state and local governments are favoring subsidies in the form of tax breaks or exemptions to encourage AI companies to build in their communities. 

This approach is misguided and provides limited return on investment for taxpayers as evidenced by reporting from ProPublica on the effect of a tax break for data centers in the state of Washington. Trends in Alabama show that the amount of taxpayer funding per local job created can range from about $205,000 to over $1 million with little if any oversight or enforcement mechanisms to ensure that the tech companies deliver on promised benefits. Similarly, a 2016 analysis from Good Jobs First found that data center subsidies cost governments nationwide about $2 million per job created. 

More recently, researchers have questioned whether tax breaks even change firms’ choices about where to build. A study from Rice Business and Harvard Business School professors found that other factors such as construction costs, network connectivity and access to reliable, affordable electricity are more important to companies building hyperscale centers. So, not only are tax breaks a bad use of public funds because they produce poor return on investment, but they may not even have their intended effect.

Further complicating the cost-benefit analysis, energy rates for consumers in the areas surrounding data centers often see increases in monthly energy costs. Utility commissions are typically organized such that the costs of repairing and creating new power lines and power plants is socialized across the entire user base. 

Because data centers require large amounts of additional grid infrastructure to receive the electricity they need to keep their systems running, all consumers in the market see an increase in their bills to pay for those upgrades. Additionally, due to the energy demands of large data centers rivaling those of entire cities, the sheer volume of demand without a corresponding increase in energy supply unsurprisingly leads to higher utility prices. 

Data centers can in fact create jobs for a local economy, but the impact is often small and transitive with most being temporary positions for constructing the facility. Even so, many communities are investing taxpayer money in subsidies to attract data center development. Not only is it unclear whether such public investments provide a positive return on investment for taxpayers, but they also do not appear to impact firms’ decisions about where to build hyperscale data centers. 

Community Strategies for Taking on Data Center Development

Communities who could benefit from what data centers have to offer must ensure they protect themselves and their neighbors before approving construction plans. Data centers can be a net benefit to communities, but only if local leaders and community members organize to ensure that costs are minimized while retaining maximum benefit. Doing so requires coordination and an understanding of the tools residents have to gain leverage on data center developers who are backed by some of the most wealthy and powerful companies in the world. Local leaders can take a proactive approach to planning data center development by addressing sustainability, zoning and infrastructure concerns to ensure data centers are designed to operate in the best interests of communities. 

Local governments have several policy options and tools to shape data center construction and operations. The first is through zoning and permitting reforms. Older zoning codes do not explicitly address data centers so they often fall into grey areas between different zoning classifications. The expectations associated with development and overall length and speed of the permitting process depend on how a data center project is classified. 

Amending zoning codes can help to alleviate uncertainty during the classification process by explicitly defining data center parameters and making clear demands in terms of what the community expects as far as where and how data centers are built. This can include but is not limited to noise, aesthetics and environmental impacts. In addition to zoning reforms, some local governments have passed other local ordinances to increase data center transparency around resource usage, ensuring accountability for delivering on promised benefits and advancing other place-based priorities for communities. 

Perhaps most importantly, local governments must exercise caution in offering local tax incentives. As described earlier, unconditional tax subsidies for data centers are poor public investments. Instead of seeing data centers as default positives, local leaders need to make a more calculated analysis of the impact on the local infrastructure, utility rates and capacity and the equitable distribution of economic benefits.

One of the most promising approaches is to mold data centers into opportunities to enhance local infrastructure, expand digital access and build renewable energy capacity. When tax breaks are offered, they should be targeted to the construction phase and tied to clear community demands. These can include requiring local hiring and contracting firms to ensure data centers pay local property taxes as well as requiring data center companies to cover the costs of building or expanding utility infrastructure.

State and local leaders should not shy away from simply pressing pause on any new data centers until they have taken the necessary time to weigh all of these considerations, listen to their communities, and clearly define how data centers will be zones. Recently, both state and local governments are adopting time-limited moratoriums or outright bans on data center facilities. Multiple councils across Georgia, Illinois, Kentucky, Kansas, Ohio, Tennessee, Missouri, Idaho and Pennsylvania have all introduced moratoria of different restrictions against data center development or denied ordinance changes that would allow them to be built.

Conclusion

Data centers are the key to the future of AI. Regardless of whatever beliefs one may have about AI, most of the decisions about how this technology is created and to what ends are being made by a few executives at Big Tech companies and their shareholders. Data center construction sites may be one of the only opportunities for the rest of society to leverage our perspectives and ideas to our overall benefit.

Simon Wang is the Economic Mobility Specialist with NCRC’s Economic Mobility team.

Joseph Dean is the Racial Economic Research Specialist with NCRC’s Research team.

Photo credit: Google DeepMind via Pexels.

• Congressional and administrative actions, the tax cut provisions of the One Big Beautiful Bill Act of 2025, the dismantling of the Consumer Financial Protection Bureau (CFPB) and the mass firing of federal employees will negatively impact the economic advancement of Black Americans.
• The CFPB’s proposed change to Regulation B of the Equal Credit Opportunity Act would eliminate disparate impact, which may exacerbate the financial exclusion of historically disadvantaged groups. It would also limit the implementation of Special Purpose Credit Programs, which are a powerful tool for channeling credit on favorable terms to underserved communities without violating anti-discrimination laws. 
• The expansion of the Low-Income Housing Tax Credit, the permanent extension of the New Market Tax Credit and the passage of the HOME Investment Partnerships Program’s final rule will help expand financing for affordable housing developments.

Photo Credit: NPS/volunteer Bill Shugarts

February 20 , 8:00 am EST – 5:00 pm EST

Join Joseph Dean, NCRC’s Racial Economic Equity Junior Research Specialist, at the Penn BLSA 38th Annual Dr. Sadie T. M. Alexander Commemorative Conference.

Hosted at the University of Pennsylvania Law School on February 21, 2026, this conference will feature a full day of insightful discussions and valuable networking opportunities.

The event honors the legacy of Dr. Sadie T. M. Alexander, a trailblazing leader in law and social justice. Whether you are a seasoned professional or just beginning your career, this conference is ideal for anyone interested in legal studies, equity, and social justice.

Last year saw a tremendous slowdown in job gains, with over 600,000 Black women leaving the workforce. While the Black unemployment rate receded from its multi-year high of 8.2% last November, it remains elevated relative to its level at the beginning of 2025. The Hispanic unemployment rate reached its highest point in 4 years (5.5%), led by a surge in joblessness for Hispanic women.

The major theme of the 2025 labor market was the unwillingness of companies to hire applicants and the relatively low number of layoffs. Dubbed the low-hire/low-fire jobs market, it was also marked by the dominance of just one industry: healthcare. Without the healthcare industry, the economy would have lost a staggering 129,000 jobs last year.

The chart below details the fact that the economy added a net (gains minus losses) 584,000 jobs last year, while healthcare added a net 713,000 jobs:

The increase in the aging population in the US has led to a greater demand for healthcare workers and social service providers, two industries that comprise around 77% and 84% women in their ranks, respectively. While the healthcare sector is known for relatively high-paying careers, Black women tend to be confined to lower-paying roles. Of all major industries, healthcare support occupations have the lowest yearly wages, which comprise the bulk of healthcare and social assistance sector jobs. This likely means that the majority of the employment growth seen last year was due to increases in these low-paying healthcare jobs. 

The stagnant labor market can be broadly attributed to the uncertainties stemming from the tariffs. No industry epitomizes the destructive nature of this more than the manufacturing sector, the sector the President stated would benefit the most from his protectionist tariffs. Since tariffs were announced in April of last year, the manufacturing sector has experienced eight consecutive months of job losses totaling 72,000 jobs.

Layoffs were at their highest level since 2008 (excluding 2020) and, even worse, planned hiring rates were at their lowest since 2010. “Negative market conditions” was the most cited reason for the layoffs. These figures were compiled by the outplacement firm Challenger given that possibly biased government data sources maintain that overall layoffs remain low. 

In addition to the high probability that we’re in a low-fire/low-hire labor market, the broader economy resembles what is commonly described as a “K” shaped economy. This moniker denotes an economy where higher-income households buoyed by rising asset prices contribute to an increasing share of consumer spending, while low and middle-income households end up cutting back on consumer spending. This phenomenon is evident in Delta Airlines’ 2025 record earnings, where, despite a 7% decline in revenue from economy cabin tickets, premium seating ticket revenue increased by 9%.

Despite comprising a greater share of consumer spending, higher-income households were consistently more pessimistic about the state of the labor market and future unemployment trends than their lower and middle-income counterparts throughout 2025. In fact, higher-income households recorded their lowest index score since the depths of the Great Recession in the latest Survey of Consumers released last November. 

Recently, new tariffs on several European countries were announced, with the European Union threatening to deploy a “trade bazooka” in response. Formerly known as the “Anti-Coercion Instrument,” it is a multi-layered retaliatory strategy that could involve steep tariffs, customs restrictions and, perhaps most severe, the full closure of the European market to US companies.

If the trade war between Europe and the United States escalates, many of the goods that low- to moderate-income households buy could increase drastically in price. Because lower-income households spend more of their income on items like food, they experience greater impacts of inflation than higher-income households. A US-Europe trade war would only add to their inflation worries and further depress an already stagnant job market.

It also illustrates the three core issues facing the US economy: a potentially devastating trade war, a worsening job market and increasing disparities between lower-income and higher-income households. For the sake of those least responsible but most vulnerable to these headwinds, let us hope disaster can be averted.

Joseph Dean is the Jr. Racial Economic Research Specialist with NCRC’s Research team.

Photo credit: Kelly via Pexels.

The latest ADP Employment Report found that the US economy lost 32,000 jobs in November. Three out of the last four months have seen declines in employment (-29,000 in September and -3,000 in August). This year has seen the most months of negative monthly job growth since the ADP began publishing its report in 2010. Small businesses shed 140,000 jobs last month while nearly all sectors except for leisure and healthcare lost jobs. 

The National Federation of Retailers’ estimated rates of seasonal hiring were ultimately down by 40% this season compared to last year. While holiday sales were up 4% compared to last year, this year’s rate of real spending growth could end up being flat. Even though Black Friday prices increased by 7%, the volume of overall holiday shopping decreased by 1%. 

In other words, not only did consumers pay more for a smaller amount of holiday gifts, but there were fewer store associates to help with their shopping needs. Even before the onset of the winter holiday season, freight demand, a major indicator of where the economy is headed, has been down significantly this season.

On the labor side, many workers face a slowing labor market, while consumers’ willingness or ability to spend has also been limited. This produces what many economists are calling the “k-shaped economy,” a visual metaphor in which the two diagonal lines in the letter ‘K’ denote the two diverging paths of households of differing economic levels. In the case of the larger consumer economy, high income earners buoyed by stock gains and rising earnings have continued to spend while low- to moderate-income (LMI) earners have cut back on their spending. 

LMI households are facing a debt crunch as delinquencies on automobile loans and student loans rise alongside tariff-induced consumer price increases. The headwinds facing LMI households have only increased over this year across the labor and financial markets spectrum.

With only the leisure and healthcare industries reliably adding jobs, the labor market is bad for anyone not looking to be a nurse or a bartender. It is why households are reporting concerns about the future trajectory of both the labor market and wider economy. So far this year, the number of newly unemployed individuals has been stable while the pool of those already jobless remains elevated. Thus, no one is getting hired or fired – yet.

Joseph Dean is the Jr. Racial Economic Research Specialist with NCRC’s Research team.

Photo credit: Karola G. from Pexels.

Revelio Labs found that the labor market lost 9,000 jobs last month as the government sector and the retail industry in particular continued to shed jobs. In the latter sector, seasonal hiring has been unusually slow as retailers cite concerns about slowing consumer spending and increased costs from tariffs. 

In contrast to this, ADP’s employment report found that 42,000 jobs were added in October, with the logistics and healthcare sectors adding sizable gains. This was the first month of positive jobs growth since July and a modest one compared to gains made earlier this year. October also saw over 150,000 job cuts, the most in an October since 2003.

Artificial intelligence (AI) was the top reason for job cuts in October, accounting for a fifth of all staffing reductions. The debate over whether AI is leading to negative outcomes for workers has intensified. The chairman of the Federal Reserve, Jerome Powell, believes that it has shrunk employment opportunities for job seekers. However, economists aren’t so sure. Nevertheless, the types of jobs that are most vulnerable to elimination by way of AI and automation developments tend to employ large numbers of Black workers.

The AI boom has taken the stock market to record highs and ushered in hundreds of billions of dollars in capital expenditures into data centers. The data centers are seen as a necessity in the global AI arms race and are seen by some as a means of economic development for local communities. While touted as investments that will reap transformative future benefits to local economies, they remain controversial for the communities in which they are located or plan to be built.

Sentiments towards data centers can be summarized best by Davante Lewis, a local Louisiana official who voted against a data center power project in the notorious “Cancer Alley” region: “Not all economic development is good economic development.” 

Data centers use an enormous amount of electricity, which has meant a 257% increase in electricity prices for communities near data centers since 2020. Additionally, recent research has shown that AI data centers create relatively few permanent jobs. Building what are essentially warehouses of computer servers is a labor-intensive endeavor, employing a thousand or more temporary construction, engineering and logistical positions. Once constructed, they employ a much smaller and more specialized workforce, typically consisting of imported talent rather than existing workers from the local area.

In addition to electricity usage, concerns about high water consumption and increasing levels of air pollution have led to intense pushback from communities. Data centers are typically built in rural areas and more economically disadvantaged communities. In places where economic development is hard to come by, a data center promising 100 jobs is an enticing prospect for a rural town with a declining population. However, in practice, claims about job creation and economic development made by data center builders are frequently overstated.

In addition to little to no tangible economic benefit for impacted communities and higher monthly utility bills, there is a troubling racial component to data center construction as well. Many are built in what is called “the Black Belt” of the country, an area that stretches from Texas to Virginia with large concentrations of Black residents. Historically, Black communities have been treated as zones of extraction for agricultural and industrial operators and have been left with the effects of environmental waste and pollution as a result. Given this ignominious history, some of the stiffest opposition to data center construction has come from Black communities.

Artificial intelligence, the data centers that power AI and the corporations that own and are expanding both are affecting the lives of Americans on all sides of the AI debate. Workers and job seekers have experienced the negative labor impacts of this fast-growing technology. For communities, it could mean another form of resource extraction that benefits shareholders and not locals. 

Data center proliferation has not reversed the slowdown in the labor market going into the final months of 2025. With seasonal hiring down and consumer spending decreasing, the chances of a Christmas miracle remain slim.

Joseph Dean is the Jr. Racial Economic Research Specialist with NCRC’s Research team.

Photo credit: Geoffrey Moffett via Upsplash.