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Crypto Industry Hit by Wave of Layoffs as Major Firms Downsize and Embrace AI

5 reports · First detected 2026-03-21 · Last active 2026-03-23

The crypto industry cut jobs sharply in 2022–2023 after token prices collapsed, FTX failed and companies unwound excessive hiring during the bull market. In 2026, macroeconomic uncertainty and weaker trading have again weighed on the sector, with Bitcoin falling 21% in the first quarter. This time, firms are also citing AI automation and flatter management structures as reasons for downsizing, suggesting the latest cuts may not be solely about surviving a downturn but could reshape exchanges’ staffing and cost structures.

Gemini announced in February that it would cut about 200 jobs, or 25% of its workforce, with the reduction rising to 30% by mid-March. Algorand Foundation cut 25% of its workforce on March 18, followed by Crypto.com cutting another 180 jobs, or 12%, on March 19. Coinbase cut about 700 jobs on May 5 and estimated severance and restructuring charges of up to $60 million. On May 7, it reported first-quarter revenue of $1.41 billion and a net loss of $1.49 per share.

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Crypto.com Cuts 12% of Staff, Integrates AI Across Business to Boost Efficiency2026-03-19 · 4 reports · similarity 0.83

Singapore-based cryptocurrency exchange Crypto.com is making AI central to its companywide operations. It launched the AI agent platform ai.com on February 9, 2026, and obtained ISO/IEC 42001:2023 certification for its AI management system that same month. The move shows how the crypto industry is using automation to reshape its workforce and cost structure, intensifying scrutiny of AI's impact on employment.

Crypto.com announced on March 19, 2026, that it would cut about 12% of its workforce. Based on the company's previous disclosure that it employed more than 1,500 people, about 180 positions are expected to be affected. The company said it would focus resources on key growth areas and use enterprise-grade AI to improve efficiency. CEO Kris Marszalek said companies that fail to pivot immediately to AI risk failure, while slow movers will fall behind.

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