Crypto.com trims workforce 12% to scale operations with artificial intelligence

Crypto.com will lay off about 12% of staff, around 180 based on prior headcount, as it rolls out company-wide AI, CEO Kris Marszalek announced on March 19. It is the crypto exchange’s third staff reduction since 2022.
Marszalek disclosed the cuts in an X post, linking them to an “enterprise-wide AI” program. The reductions center on functions that, in his words, “do not adapt” as new tools are introduced. According to the post, affected workers have been notified and are receiving transition support. With a reported employee base of more than 1,500, the plan equates to around 180 positions. Based on our Crypto.com review, the exchange was founded in Hong Kong and lists offices in Singapore, France and the United States.
“Companies that do not make this pivot immediately will fail. Companies that move slowly will be left behind. Companies that move immediately and pair the best AI tools with top performers will achieve a level of scale and precision that was previously impossible,” he wrote.
The company cut about 5% of staff in 2022, around 260 roles from a team of more than 5,000, citing a weaker macro environment. After FTX’s collapse later that year, Crypto.com reduced headcount again in 2023 by about 20%.
Other crypto and fintech firms have announced reductions in recent weeks. Gemini said in February it expects to eliminate up to 200 roles, or about a quarter of its staff, to lower expenses and speed its path to profitability. Block trimmed its workforce by roughly 40% last month as CEO Jack Dorsey outlined a smaller, flatter structure focused on AI; a limited number of employees were later rehired. Crypto data firm Messari disclosed leadership changes and job cuts this month, with CTO Diran Li becoming CEO and describing a plan to become an “AI-first” company. The Algorand Foundation reported a 25% cut, pointing to a weak macro backdrop and a broader downturn in crypto markets.
CEO Kris Marszalek described the restructuring as aimed at efficiency and scale as AI tools are deployed across departments. No breakdown of teams was provided beyond an emphasis on roles not adapting to the new operating model.
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