Jack Dorsey’s Block to cut half of staff amid AI shift

You are watching company org charts change in real time. Jack Dorsey says artificial intelligence now changes how firms are built and run. In a letter to shareholders, he confirmed Block will shrink headcount from roughly 10,000 to fewer than 6,000, framing it as a reset of how work gets done rather than a routine cost trim.

Block owns Square, Cash App and Tidal, and has been through several rounds of job cuts since 2024. This is the first time the company has cited AI as the reason for redundancies, as reported by the BBC. Dorsey, who previously co‑founded Twitter (now X), is pushing Block towards a smaller, faster model.

He also told investors that many companies will reach a similar conclusion within the next year, adding that plenty are arriving late to the change. In his view, the shift is structural: fewer layers, broader roles, and more tasks handled by software agents that can draft, analyse and monitor at speed.

The announcement arrived alongside upbeat numbers. Block reported strong demand for its products and said it expects up to $500m (£370m) in restructuring costs as it pivots to the new set‑up. Investors seemed to approve, with the share price rising by more than 20% in extended trading after the news.

This is part of a wider pattern across big tech. At the end of January, Amazon cut 16,000 jobs, on top of 14,000 roles a few months earlier. On the results call, chief financial officer Brian Olsavsky said the company was seeking savings elsewhere even as it ramps up spending on AI.

Meta, Microsoft and Google have also shed workers while pouring billions into AI infrastructure and research. Meta’s Mark Zuckerberg has said he expects 2026 to be the year AI changes the way we work, with projects that once needed large teams now possible for a single, very capable person.

A key driver is the rise of code‑writing assistants. Tools such as Anthropic’s Claude Code and OpenAI’s Codex can generate scaffolding, tests and routine functions, which means engineers spend more time on design, debugging and review. These systems still make mistakes, so human checks, security assessments and clear evaluation remain essential.

For learners and early‑career developers, the signal is practical. Keep building small, end‑to‑end products, show how you pair an assistant with strong unit tests, document your prompts, and explain the guardrails you add for privacy and safety. Your value sits in judgement, not just keystrokes.

For managers, the trade‑offs demand care. AI can compress timelines and widen each person’s remit, but it can also introduce errors at speed. Expect leaner structures, new spending on data quality and model evaluation, and pressure to prove that job cuts do not come at the expense of reliability or trust.

There is also a media‑literacy lesson here. Some analysts argue the immediate threat to jobs has been overstated by executives keen to look ahead of the curve. Both views can be true at once: automation trims specific tasks today while the wider labour market adjusts over years. As readers, we should keep asking who benefits, what is being automated, and how success is being measured.