Who are Scale AI's decision-makers?

Scale was co-founded in 2016 by Alexandr Wang, an MIT dropout, and Lucy Guo, a Carnegie Mellon dropout. Wang led the company as CEO for nearly a decade and became the public face of the AI-data industry; Guo departed in 2018 but retained roughly a 5% stake worth ~$1.25B at the Meta valuation, which Forbes credited as making her the world's youngest self-made woman billionaire.

Since June 2025 the CEO is Jason Droege, who joined as Chief Strategy Officer in August 2024 and had previously founded Uber Eats and held an executive role at Axon. Droege still carries the interim title into 2026. Wang moved to Meta to run its Superintelligence Labs as Chief AI Officer but stays on Scale's board, and Dennis Cinelli serves as Chief Financial Officer, owning capital structure and the approval process for large purchases.

Strategy and the largest deals run through the CEO and CFO, but day-to-day purchasing authority sits with the leaders of Scale's three businesses — Build AI (data engine), Apply AI (the GenAI platform and Donovan defense product), and Evaluate AI (model evaluation) — plus the public-sector organization that manages government contracts. Each owns its own tooling, infrastructure, and vendor budgets.

If you sell software or services, map to the specific business unit you serve rather than to 'Scale' in the abstract. Government and defense buyers (Donovan, DoD work) follow security- and compliance-heavy procurement; enterprise GenAI and evaluation teams move faster but still route security review through IT and the CFO's office for anything material.

After the Meta investment, Droege restructured the company to be 'more nimble', consolidating the generative-AI business from sixteen pods down to five priorities (code, languages, experts, experimental, and audio) and cutting 14% of staff in July 2025, mostly in data labeling. By 2026 he framed the company around a 'reliability' mantra to its 1,300+ employees, arguing AI is still too unreliable for mission-critical business, military, and government use.

The practical implication for sellers is that Scale is shifting weight away from commodity labeling and toward higher-margin government, enterprise applied-AI, and evaluation work. Budgets and headcount are growing in those areas and shrinking in others — so the org chart you sell into in 2026 looks materially different from the pre-Meta company.