Block co-founder says less people can now do more work – and do it better
Jack Dorsey has eliminated about 40% of Block’s workforce and told investors that artificial intelligence allows “a significantly smaller team” to do better work. He believes the majority of companies will now follow suit.
For most executives, this won’t come as a surprise. But the scale of Dorsey’s cuts and his clear-eyed prediction may have a few people spluttering into their morning coffee. The next stage of the AI era, according to Dorsey, isn’t just about reskilling and redeployment; it’s about intentional strategies to run profitable companies with far fewer people.
Block, the fintech company behind Square and Cash App, is cutting more than 4,000 roles, taking staff from more than 10,000 to just under 6,000. The company isn’t in a classic crisis—its gross profit is growing and its customer base is expanding. Dorsey’s message is that AI and automation have changed the equation on how many people are needed to build and run a modern financial-technology platform.
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In his communication to investors, as reported by The Wall Street Journal, Dorsey wrote: “The core thesis is simple. Intelligence tools have changed what it means to build and run a company.” He added that “a significantly smaller team, using the tools we’re building, can do more and do it better.” This statement suggests that workforce size itself is now a deliberate design choice in the AI age, not a legacy constraint.
Markets have endorsed that thesis. Block’s stock price surged after the announcement, adding billions in market value as investors embraced the plan to compress head count while leaning hard into AI. For HR executives, that response matters. It signals that public markets are prepared to reward companies that explicitly tie layoffs to AI-enabled efficiency.
A blueprint for ‘AI-native’ restructuring
Dorsey has framed Block’s layoffs as a structural reset after years of expansion. Head count swelled in the late-pandemic boom as the company pushed into new products and markets. Now, AI agents and automation tools are being used to justify a return to a leaner operating model, with far higher output expected from each remaining employee.
He has also suggested Block is an early mover, not an outlier. Dorsey argued that companies mirroring the head-count levels of the past decade without matching them to AI capabilities are “late,” and he has predicted that many will reach similar conclusions over the next year. The implication is that more CEOs will point to AI as they rationalize staff numbers.
Historically, HR has often responded to automation with incremental changes—targeted cuts, selective redeployment, gradual hiring freezes. What Block is doing looks different: a large step change in head count, expressly justified by AI and framed as a permanent shift in how work is organized.
From protecting jobs to redesigning the workforce
In this environment, companies have to move from defending existing jobs to actively re-architecting the workforce. Instead of simply layering tools onto existing roles, companies will be expected to help design smaller, cross-functional teams in which AI handles routine analysis, drafting, coordination and basic decision support, while people focus on judgment, creativity, relationships and oversight.
Should companies prepare for “one-and-done” restructurings rather than rolling waves of cuts? Dorsey thinks so and has suggested that drawn-out job reductions are worse for morale than a single decisive reset. That is likely to appeal to CEOs under pressure from investors.
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Block has been rolling out its own AI agents internally, and the company says engineers are already saving material amounts of time with these tools. That kind of concrete productivity story is what CEOs will now demand from HR and learning functions. Generic “AI literacy” programs won’t be enough.
Dorsey has spoken... what next?
First, conduct an AI-exposure audit by role and process. HR should partner with technology and operations leaders to build a clear catalog of AI and automation already in use. Then, at the team level, leaders should identify which tasks are already being partly automated, which could be, and what that means for staffing over the next 12 to 24 months.
Second, put governance around AI and workforce decisions. An “AI and workforce” council that brings together HR, legal, risk, technology and business leaders can evaluate the people impact of major AI deployments before they scale. Such a group can set principles for when automation should lead to redeployment versus reduction, and can ensure that the company doesn’t take on undue operational or reputational risk in pursuit of rapid efficiency gains.
Finally, take control of the narrative. When a CEO publicly argues that “intelligence tools” allow “a significantly smaller team” to do more, employees, candidates and customers will fill in the blanks. Clear communication is essential about where AI is likely to change work, where human roles remain central, what the time horizon looks like, and how the company will treat people if restructuring becomes necessary.
The Block story stands out because it is a clear signal that AI will increasingly be used as a rationale for doing more with fewer people. Dorsey’s claim that a smaller, AI-enabled staff can outperform a larger one will be tested in the quarters ahead, and the outcome will vary from company to company and industry to industry. For now, executives have a narrow window to prepare their organizations for a potential future in which leaner, AI-native operating models become the norm rather than the exception.
