But when trading volume cools down and valuations come under pressure, is this a precursor to an efficiency revolution, or is it a periodic contraction packaged as artificial intelligence?

Written by: Zhao Ying

Source: Wall Street Insights

Artificial intelligence is becoming the core narrative of a new wave of layoffs in the cryptocurrency and fintech sectors. Coinbase, PayPal, Gemini, and Crypto.com have successively reduced their workforce, citing automation and efficiency improvement as primary drivers. However, critics point out that some companies may use AI as a facade to mask the real costs of declining business and overexpansion.

According to Bloomberg, Coinbase CEO Brian Armstrong characterized the layoffs in strong terms on Tuesday, warning that "the biggest risk now is not taking action," and stated that the company is committed to becoming a "streamlined, fast, AI-native" organization. This statement marks a new height in the public discourse around AI restructuring by executives in the cryptocurrency industry.

The direct impact of this wave of layoffs on the market is that the hiring logic of cryptocurrency and fintech companies is being restructured, with technology and operational positions facing continued compression, while the trend of flattening management levels is also accelerating. Investors need to determine whether this is a precursor to a leap in industry efficiency or a periodic contraction packaged as AI.

Block takes the lead, industry follows

According to Bloomberg, the momentum of this wave of layoffs significantly accelerated after Block announced large-scale job cuts. Block is the parent company of Square and Cash App, and it announced major layoffs earlier this year, including AI as part of a broader restructuring plan. Subsequently, several industry peers adopted similar language, characterizing layoffs as proactive preparation for an AI-driven future.

Coinbase has been particularly proactive in this process. In addition to cutting staff, the company is also flattening management levels, requiring managers to operate in a "player-coach" model, balancing execution and management functions. Blockchain infrastructure company 0G Labs stated that after internal AI tools significantly improved productivity, it has reduced its workforce by 25%.

Concerns over "AI whitewashing"

Critics are not entirely convinced by this narrative. Many companies are facing more direct business pressures: trading activity in cryptocurrency assets has cooled noticeably, digital asset prices remain below recent highs, and payment companies are struggling under the dual pressures of slowing growth and intensified competition.

Some companies also have their own internal dilemmas. Block aggressively expanded during the pandemic boom, accumulating substantial redundancy; PayPal is still undergoing a comprehensive transformation led by its new management. This context has led to accusations of "AI whitewashing" — that companies are using artificial intelligence as a more palatable excuse to cover layoffs caused by weak demand or overhiring.

Needham & Company analyst John Todaro directly questioned this: "Whenever I see these layoffs with AI cited as one of the reasons, I take a step back and ask: have we seen this in companies during a market boom?" He added, "I'm not sure I believe the AI narrative."

Two logics coexist, proportions are debated

Some observers believe that both explanations can simultaneously hold true. Raman Shalupau, founder of the crypto job platform CryptoJobsList, estimates that the current layoffs are "approximately distributed at an 80/20 ratio across the industry — 80% are genuine AI efficiency improvements, while 20% are cuts of redundancies from the last bull market."

This assessment implies that a substantial restructuring of job functions around AI is indeed occurring, but its scale and speed vary by company. Even in companies that have not made large-scale layoffs, job functions are being rapidly restructured around automation tools, with some repetitive tasks being replaced by systems rather than taken on by new hires.