Amazon hikes wages for contract delivery drivers as union pressures grow
In an aerial view, Amazon delivery trucks sit parked at an Amazon distribution center in Richmond, California, on July 16, 2024.
Justin Sullivan | Getty Images
Amazon is bumping its average national pay for contracted delivery drivers to roughly $22 an hour, up from $20.50 an hour, the company said Thursday.
The wage increase is part of Amazon’s $2.1 billion investment this year into its delivery service partner program, which are the legions of contracted firms that handle last-mile delivery of packages from the company’s warehouses to shoppers’ doorsteps.
The company’s announcement comes as it faces a renewed unionization effort among its contracted delivery workers.
Beryl Tomay, Amazon’s vice president of transportation, wrote in a blog post that many DSPs are “already paying well above” $22 an hour. The increased rates will continue to support DSPs “in their efforts to recruit and retain high-performing teams.”
Amazon announced the pay bump at the same time that it is hosting an annual, closed-door conference for those delivery contractors, called Ignite Live, in Las Vegas. The company made a similar announcement at last year’s event. Amazon has said it has added more than 3,500 DSPs to the program since it launched in 2018.
The Teamsters Union has led several strikes at Amazon delivery facilities in the past year, and it has made organizing Amazon employees a key focus after launching a division dedicated to the online retail giant in 2021.
The National Labor Relations Board has also been scrutinizing the company’s relationship with its contracted delivery workforce. Since August, the federal labor agency has issued two determinations finding that Amazon should be deemed a “joint employer” of employees at two subcontracted delivery companies. The NLRB’s determination could compel Amazon to bargain with employees seeking to unionize.
Amazon has fought to avoid being designated as a joint employer of its contracted delivery drivers, arguing that the workers are employed by third-party firms. Lawmakers and labor groups have disputed the company’s characterization, saying drivers wear Amazon-branded uniforms, drive Amazon-branded vans and have their schedules and performance expectations set by Amazon.
The company has previously said it disagrees with the NLRB’s findings.
Jensen Huang, chief executive officer of Nvidia Corp., during the US-Saudi Investment Forum at the Kennedy Center in Washington, DC, US, on Wednesday, Nov. 19, 2025.
Stefani Reynolds | Bloomberg | Getty Images
In the weeks leading up to Nvidia’s third-quarter earnings report, investors debated whether the markets were in an AI bubble, fretting over the massive sums being committed to building data centers and whether they could provide a long-term return on investment.
During Wednesday’s earnings call with analysts, Nvidia CEO Jensen Huang began his comments by rejecting that premise.
“There’s been a lot of talk about an AI bubble,” Huang said. “From our vantage point we see something very different.”
In many respects, Huang’s remarks are to be expected. He’s leading the company at the heart of the artificial intelligence boom, and has built its market cap to $4.5 trillion because of soaring demand for Nvidia’s graphics processing units.
Huang’s smackdown of bubble talk matters because Nvidia counts every major cloud provider — Amazon, Microsoft, Google, and Oracle — as a customer. Most of the major AI model developers, including OpenAI, Anthropic, xAI and Meta, are also big buyers of Nvidia GPUs.
Huang has deep visibility into the market, and on the call he offered a three-pronged argument for why we’re not in a bubble.
First, he said that areas like data processing, ad recommendations, search systems, and engineering, are turning to GPUs because they need the AI. That means older computing infrastructure based around the central processor will transition to new systems running on Nvidia’s chips.
Second, Huang said, AI isn’t just being integrated into current applications, but it will enable entirely new ones.
Finally, according to Huang, “agentic AI,” or applications that can run without significant input from the user, will be able to reason and plan, and will require even more computing power.
In making the case of Nvidia, Huang said it’s the only company that can address the three use cases.
“As you consider infrastructure investments, consider these three fundamental dynamics,” Huang said. “Each will contribute to infrastructure growth in the coming years.”
Reversing the slide
In its earnings release, Nvidia reported revenue and profit that sailed past estimates and issued better-than-expected guidance. Last month, Huang provided a $500 billion forecast for sales of the company’s AI chips over calendar 2025 and 2026.
The company said on Wednesday that its order backlog didn’t even include a few recent deals, like an agreement with Anthropic that was announced this week or the expansion of a deal with Saudi Arabia.
“The number will grow,” CFO Colette Kress said on the call, saying the company was on track to hit the forecast.
Prior to Wednesday’s results, Nvidia shares were down about 8% this month. Other stocks tied to the AI have gotten hit even harder, with CoreWeave plunging 44% in November, Oracle dropping 14% and Palantir falling 17%.
Some of the worry on Wall Street has been tied to the debt that certain companies have used to finance their infrastructure buildouts.
“Our customers’ financing is up to them,” Huang said.
Specific to Nvidia, investors have raised concerns in recent weeks about how much of the company’s sales were going to a small number of hyperscalers.
Last month, Microsoft, Meta, Amazon and Alphabet all lifted their forecasts for capital expenditures due to their AI buildouts, and now collectively expect to spend more than $380 billion this year.
Huang said that even without a new business model, Nvidia’s chips boost hyperscaler revenue, because they power recommendation systems for short videos, books, and ads.
People will soon start appreciating what’s happening underneath the surface of the AI boom, Huang said, versus “the simplistic view of what’s happening to capex and investment.”
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