Scale AI explains layoffs and cites luxury and unprofitability

AI For Business


Jason Droege, interim Scale AI CEO, emailed staff members saying they had made a major layoff due to overhardening for the Genai unit.

Scale AI cut its 1,400 workforce by 14% on Wednesday, impacting 200 employees who will help major tech clients like Google and Meta improve their AI chatbots.

Droege has expanded the capacity of “too fast in the past year over the past year” written in an email viewed by Business Insider, saying “too fast in the past year” and “too fast” and “not resources.”

“It felt like the right decision at the time, but it's clear that this approach created inefficiency and redundancy,” writes Droge. “We've created too many layers, too much bureaucracy and useless confusion about the mission of our team.”

The email also confirmed that Scale AI is not profitable and states that startups have an ongoing “willingness to profitability.” As part of that drive, Scale AI will reject Genai projects that have a low revenue driver or are unlikely to grow, says Droege's email.

Droege cited the market shift in layoffs, writing, “A change in market demand requires a rethinking of plans and improving approaches.”

According to Droege's email, as part of the reorganization, Scale AI will streamline the Genai Division from 16 “pods” to five key areas, consolidating the various teams into a single demand generation team.

The investment in the scale of Meta's blockbuster blockbuster and the hiring of former CEO Alexandre Wang has caused great disruption to the startup's large tech customer base that competes with AI's meta. Google, Xai and others have suddenly stopped their projects on scale after their investments.

Scale AI previously told BI it was well funded and plans to hire hundreds more staff in various regions.

“We are helping to streamline our data business, move faster and deliver even better data solutions to Genai customers,” said Joe Osborne, AI spokesperson. “We also plan to invest heavily and hire large amounts of money across corporate and government AI companies.”





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