The news: Amazon cut 14,000 corporate roles on Tuesday, calling the cuts an effort toward “reducing bureaucracy, removing layers, and shifting resources to ensure we’re investing in our biggest bets,” per Bloomberg.

CEO Andy Jassy said in June that staff numbers would likely shrink due to AI efficiencies. Last week, Amazon announced plans to replace more than 500,000 jobs with robots.

Reports from Reuters stated that Amazon’s cuts could reach 30,000, but increased hiring in some places will partially offset those losses. Affected divisions include gaming, cloud computing, logistics, and others, per Bloomberg.

The trend: It’s been a challenging year for the workforce with rising inflation and a softening labor market—to say nothing of AI, which Accenture and Salesforce explicitly called out when making cuts. But in most cases, creating a leaner, flatter (i.e., fewer middle-management roles) organization was named as the reason.

Notable layoffs so far in 2025 include:

• Intel: Over 27,000
• Microsoft: Over 15,000
• Accenture: Over 11,000
• Salesforce: Over 5,000
• Meta: Around 4,300
• Workday: 1,750
• Cruise: 1,000

For Big Tech companies or those building generative AI models, most will stick with hiring AI engineers or replacing critical roles lost to attrition. Other jobs may be sacrificed to hire the top AI minds.

What’s next: There are two ways the future of tech employment can go outside of Big Tech firms.

• AI pilots fail: If genAI experimentation doesn’t go how a company plans or doesn’t lead to efficiencies, those that have implemented layoffs will need to rehire. Companies that haven’t trained employees on AI or those that lack AI governance are most at risk.
• AI pilots take off: In this case, we can expect further layoffs, though the scale of those cuts will vary depending on the tools the companies adopt and how automated they become.

What brands should do: Whether a company is looking to avoid layoffs or streamline operations, they should experiment with multiple AI tools to find the right solutions for specific roles and companies, even if that means learning that AI isn’t right for them.