Block, the payments and financial services company led by Jack Dorsey, is cutting more than 4,000 jobs, nearly half its workforce, because AI tools have made a leaner organisation not just possible, but strategically preferable, Dorsey said in a letter to its shareholders.
The Scale of the Cuts
The cuts will reduce Block’s headcount from over 10,000 to just under 6,000. The company is not cutting from a position of weakness. Block posted gross profit of $10.36 billion in fiscal year 2025, up 17% year over year, and is raising its 2026 gross profit guidance to $12.20 billion. In Q4 2025 alone, gross profit grew 24%, the company said in its earnings call.
“Intelligence tools have changed what it means to build and run a company,” Dorsey wrote in the latter. “A significantly smaller team, using the tools we’re building, can do more and do it better. And intelligence tool capabilities are compounding faster every week.”
He added a prediction that will be hard for enterprise leaders to ignore: “Within the next year, I believe the majority of companies will reach the same conclusion and make similar structural changes. I’d rather get there honestly and on our own terms than be forced into it reactively.”
Block is Not the First — and It Won't Be the Last
Block is not alone. Earlier this week, WiseTech Global, the Australian logistics software company behind the CargoWise platform, cut around 2,000 roles, citing comparable AI efficiency gains. Like Block, WiseTech was profitable at the time. Companies, including Amazon, Microsoft, Workday, and Salesforce, have all cited AI in recent workforce reductions.
Similarly, Data analysis vendor C3 AI on Thursday slashed its workforce by 26%, citing agentic efficiencies as a critical factor.
The scale of disruption ahead is significant. A Forrester forecast published in January predicts AI and automation will eliminate 6.1% of US jobs by 2030, equivalent to 10.4 million positions. To put that in context, the US lost 8.7 million jobs during the Great Recession. Unlike recession-driven losses, Forrester notes, AI-driven displacement is structural and permanent. Notably, genAI now accounts for 50% of projected US job losses to automation, up from 29% in Forrester’s earlier forecast, as agentic AI solutions compound the effect.
But Forrester adds a pointed caveat. Nine out of ten times, the firm said, when a CEO announces workforce reductions citing AI, the company does not yet have a mature, vetted AI application ready to fill those roles.
Restructuring from Strength, Not Distress
The context of Block’s cuts is what makes them significant, said Sanchit Vir Gogia, chief analyst at Greyhound Research. “This is not about trimming fat. It is about redefining muscle,” he said. “When a financially healthy company decides to remove nearly half its workforce and openly attributes that to AI capability, it is not reacting. It is repositioning.”
Gogia drew a clear distinction from previous restructuring cycles. “In previous cycles, layoffs followed weakness. This time the order is reversed. Cutting during strength signals belief — it says leadership is convinced that waiting would be riskier than moving early.”
On Dorsey’s prediction that most companies will follow within a year, however, Gogia threw caution. “The structural shift is real. The one-year synchronised wave is not,” he said. Regulatory intensity, labour frameworks, legacy integration complexity, and governance maturity will slow adoption in heavily regulated sectors such as financial services, healthcare, and public infrastructure, he argued. “Predictions of universal twelve-month adoption underestimate institutional friction.”
Speed Without Architecture is a Risk, Not a Strategy
For IT leaders, the implications run deeper than headcount. Gogia warned that speed without architectural discipline creates risk. “Aggressive compression without escalation redesign creates brittle systems that only reveal weakness during stress.”
He added that workforce planning can no longer operate at the level of job titles. “Planning must move to task clusters, identifying which cognitive workflows are substitution-feasible and which remain human-critical because escalation authority or regulatory accountability demand it.”
Dorsey described Block’s destination as becoming a “smaller, faster, intelligence-native company.” Gogia’s framing offers a useful corrective for enterprise leaders processing that signal: the organisations that navigate this transition well, he said, “will not be those that cut fastest. They will be those who redesign deliberately.”
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