Apple Sued by Employees Alleging Unequal Pay for Women
Lawsuit says company’s hiring and performance-review practices routinely slant toward men
3 min
Two female Apple employees filed a proposed class-action lawsuit Thursday alleging the company pays women lower salaries than men for similar work.
The suit, filed in a San Francisco state court, targets Apple’s hiring practices used to set compensation, as well as the company’s performance-review policies. It is the latest in a series of pay equity lawsuits against major corporations, including large tech giants, that allege they underpay women and minorities .
The lawsuit seeks to represent a class of 12,000 women employed at Apple across several departments who have worked there since 2020. The plaintiffs allege that the company is violating the California equal pay, employment and unfair business practice laws. The business practice law limits claims to a four-year period.
An Apple spokesman said the company has achieved and maintained gender pay equity since 2017. Apple works with an independent third-party expert to examine team members’ total compensation and makes adjustments where necessary, he said.
Google and Oracle settled similar claims in California in recent years, pushing similar arguments about pay policies for new hires. Google agreed to pay 15,500 women $118 million to settle its case in 2022 and Oracle agreed to pay $25 million for 4,000 female workers earlier this year. The companies didn’t admit wrongdoing.
One of the lead attorneys on those cases is also representing the plaintiffs against Apple.
Central to the new lawsuit is how Apple sets a new hire’s compensation. Before 2018, Apple asked applicants to provide their previous salaries to determine pay, the suit says.
When California passed a 2018 law that banned employers from considering prior pay to set compensation, Apple asked applicants about pay expectations instead, the suit says. The plaintiffs’ lawyers argue that the practice of asking about pay expectations perpetuates gender discrimination because women have historically been paid less than men.
“If you do pay women less, you can’t defend it by saying they were willing to take less money,” said James Finberg , one of the plaintiffs’ attorneys.
One of the plaintiffs, Justina Jong, said she discovered a male co-worker’s W2 left behind on a printer in Apple’s Sunnyvale, Calif., branch. Though she had the same responsibilities as her male co-worker, she saw his base salary in the tax filing was $10,000 more than what she made, she said. She discovered the discrepancy several years ago, about midway through her decade-plus career at Apple, where she held several roles in sales, training and marketing.
“I felt terrible and was shocked as well. I saw myself as a hardworking person, and collaborative, providing a lot of solutions for the team,” Jong said in an interview. “I thought to myself, ‘Maybe if I work harder, they will see that I’m worth just as much or more.’”
The lawsuit alleges that when Apple hired Jong in 2013, it paid her the same base salary she earned at her previous job. In the years following, the company never gave her the kind of raise that put her on equal footing with her male peers, the suit says.
Jong said it took her years to decide to challenge the discrepancy and sign onto the lawsuit. She said she was spurred by stories about unequal pay from other women at the company.
During the Covid-19 pandemic, Apple faced a rise in employee activism. Apple workers organized to form a group called Apple Too to mirror the #MeToo movement, which gathered stories of discrimination and pushed the company to change its pay practices. The movement led to some retail stores forming unions.
“At Apple we are deeply committed to inclusion and we have a longstanding commitment to pay equity, which is embedded in our approach to compensating our valued team members,” a spokesman for Apple said.
The other named plaintiff, Amina Salgado, has worked at Apple since 2012 in various roles, including as a manager in the AppleCare division in the company’s office near Sacramento. She discovered she was paid less than men in similar roles, and she complained several times about the discrepancy, according to the lawsuit. Apple hired a third party to investigate, and after the report concluded she was right, the company increased her pay. She didn’t get back pay, the lawsuit says.
The suit also claims that Apple uses biased criteria in its performance-review system. Men routinely receive higher ratings for the discretionary categories of leadership and teamwork, leading to better reviews for men, the plaintiffs’ lawyers argue.
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
The debt behind the AI build-out
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
Inflation changes the calculation
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
China adds another source of pressure
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
A reset rather than the end of the boom
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Fact box
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
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