AI is key driver behind layoffs at fintech company Block

Block (the parent of Square, Cash App, Afterpay, and Tidal) is cutting roughly 40% of its workforce—more than 4,000 of about 10,000 employees—and its CEO Jack Dorsey is explicitly framing advances in AI and “intelligence tools” as the central reason.

What Block announced

• Headcount will fall from just over 10,000 to “just under 6,000,” implying more than 4,000 job cuts, or about 40% of staff.

• Dorsey has told shareholders and staff that new AI “intelligence tools” change what it means to build and run a company and allow “significantly smaller teams” to do more work, more efficiently.

• He has emphasized that the decision is not driven by weak performance; Block reported a strong 2025 with rising gross profit, customer growth, and improving profitability.

AI as the “key driver”

• In public statements, Dorsey has directly linked the layoffs to AI, saying that intelligence tools are enabling “a new way of working” and are advancing so quickly that Block can operate with fewer people.

• Company messaging and press coverage consistently describe AI as the primary driver or key factor behind the reduction, in contrast to the usual cost-cutting or demand-slump narratives.

• Analysts note that investors appear to accept this AI-productivity justification: Block’s shares jumped more than 20%–26% after the announcement.

How unusual is this?

• Many big tech firms (Amazon, Meta, Microsoft, Verizon, others) have laid off workers while investing heavily in AI, but have often framed cuts around “efficiency,” restructuring, or post-pandemic normalization.

• Block is one of the clearest early examples of a large, profitable firm explicitly attributing a large percentage layoff directly to AI and positioning it as a deliberate redesign of the operating model rather than a cyclical belt-tightening.

Implications for AI and fintech jobs

• If Block’s thesis holds—that AI lets fintech infrastructure (payments, risk, servicing, operations) run with dramatically smaller teams—similar firms may face pressure from markets to follow suit.

• The cuts will likely fall heavily on operational, support, and some engineering roles whose work can be automated or leveraged by AI tools, while demand for highly skilled AI, data, and product roles may persist or grow.