A growing number of companies are cutting workers as they reorganize around artificial intelligence, adding momentum to a wave of layoffs in 2026.
The trend is fueling new concerns not only about job security, but also about what this rapid tech expansion could mean for communities, the broader economy, and an already-strained energy system.
What's happening?
In early May, several major companies announced new rounds of layoffs while explicitly tying their future plans to AI adoption and automation, BeInCrypto reported.
Cloudflare, for example, said that it planned to eliminate more than 1,100 roles worldwide, representing roughly one-fifth of its staff. The company also said that internal AI activity jumped by over 600% over three months.
"We have to be intentional in how we architect our company for the agentic AI era in order to supercharge the value we deliver to our customers and to honor our mission to help build a better Internet for everyone, everywhere," Cloudflare wrote in a message to staff.
That same day, payments company BILL said that it could cut nearly 30% of staff, per BeInCrypto. Upwork, a marketplace to hire freelancers, also told employees that roughly one in four roles would be cut, with CEO Hayden Brown saying the company believes it can move faster with smaller teams and needs to meet profitability targets in a difficult business environment.
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Elsewhere, Ticketmaster reportedly reduced its global workforce by 8%, which BeInCrypto said came to around 350 employees across 25 countries.
PayPal and Coinbase are just a couple more companies looking to significantly reduce staff as part of a broader shift toward smaller teams supported by AI tools.
Taken together, the announcements underscore how quickly AI is becoming central to corporate restructuring. At the same time, researchers say there is still limited evidence that AI alone has already caused economy-wide job disruption. Still, economists expect larger labor shifts ahead as companies continue testing what automation can replace.
Why is this concerning?
The most immediate concern is simple: Thousands of people are losing paychecks while companies cite AI as a reason to slim down. Those losses can ripple outward, affecting families, local businesses, and regional economies.
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But another layer to the story is AI's deep connection to the energy grid.
Training and running AI systems requires massive computing power, which means data centers consume enormous amounts of electricity and, in many cases, large volumes of water for cooling.
As AI use grows, utilities and grid operators may have to meet rising demand quickly. If that demand is met with dirtier energy sources instead of wind, solar, battery storage, and grid upgrades, it could increase planet-warming pollution and keep older power plants online longer. In some places, that pressure could also push electric bills higher.
That does not mean AI is purely harmful. The same technology can support building efficiency, accelerate scientific research, and identify equipment failures before they trigger outages. But those potential benefits do not erase the risks. Alongside heavy energy and water use, experts have warned about AI misuse, biased decision-making, and the social consequences of replacing workers faster than economies can adapt.
What's being done about AI-driven layoffs?
There is still time to shape how this transition unfolds.
Some economists point out that broad AI-driven job losses have not yet fully materialized across the economy, suggesting policymakers, companies, and workers still have a window to put guardrails in place before disruption spreads further.
That could mean stronger severance protections, retraining programs, better transparency around when layoffs are tied to automation, and public investment in workforce development for jobs that are harder to automate.
On the energy side, regulators, utilities, and tech companies can push for cleaner ways to power AI growth. That includes building more renewable energy, modernizing transmission, improving efficiency standards for chips and data centers, and cutting water waste at computing facilities. Requiring major AI operators to disclose their energy and water use could also help communities better understand local impacts.
For everyday people, the most meaningful responses are both civic and practical: Support policies that expand renewable energy and grid upgrades, pay attention to how employers are using AI, and back worker protections that ensure productivity gains are shared more fairly.
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