Scale AI Lays Off 14% of Workforce Amid Restructuring

Scale AI Lays Off 14% of Workforce Amid Restructuring

Scale AI has announced layoffs affecting 14% of its workforce, primarily in its data-labeling business, as it restructures to focus on enterprise and government sales.

Scale AI has announced a significant reduction in its workforce, laying off 200 employees, which accounts for approximately 14% of its staff. The layoffs primarily impact the company's data-labeling business, a core area that has been rapidly expanded in recent years.

The decision to downsize comes as the company reassesses its business strategy following a major investment from Meta Platforms. Interim CEO Jason Droege indicated that the company had overextended its hiring in the generative AI division, leading to inefficiencies and redundancies. As a result, Scale AI plans to streamline its operations and focus on higher-growth areas, particularly in enterprise and government sales.

In addition to the layoffs, Scale AI is also cutting ties with 500 global contractors. The company remains well-funded and intends to hire in areas that promise higher growth potential. This restructuring aims to enhance the company's ability to deliver data solutions more efficiently to its generative AI customers.

We hope you enjoyed this article.

Consider subscribing to one of several newsletters we publish. For example, in the Daily AI Brief you can read the most up to date AI news round-up 6 days per week.

Also, consider following us on social media:

Subscribe to Daily AI Brief

Daily report covering major AI developments and industry news, with both top stories and complete market updates

Market report

AI’s Time-to-Market Quagmire: Why Enterprises Struggle to Scale AI Innovation

ModelOp

The 2025 AI Governance Benchmark Report by ModelOp provides insights from 100 senior AI and data leaders across various industries, highlighting the challenges enterprises face in scaling AI initiatives. The report emphasizes the importance of AI governance and automation in overcoming fragmented systems and inconsistent practices, showcasing how early adoption correlates with faster deployment and stronger ROI.

Read more