When the fintech Block recently announced it was cutting nearly half its workforce, many questioned whether it was another tech company cleaning up a pandemic-era hiring binge. But CFO and COO Amrita Ahuja offered a data point to consider.
Block generated roughly $500,000 in gross profit per employee in 2019—a figure that barely budged even as headcount ballooned from a few thousand to around 13,000 during the hyper-growth years, Ahuja noted in a recent interview with Fortune. Then something changed.
As AI tools embedded more deeply into the company’s workflows, that metric began climbing: $750,000 per employee in 2024, $1 million in 2025. And if Block hits the targets the targets in its 2026 outlook—now expecting gross profit to grow 18% year over year and profits to climb 54%—gross profit per employee will reach approximately $2 million in 2026, double last year’s level.
“I don’t think this is about bloat,” Ahuja said. “This is about empowering our teams with the most world-class and powerful tools.”
Central to that shift is Block’s internally built AI agent, code-named Goose, which has been running in production for 18 months. Since September, developer productivity has jumped 40% per engineer. One risk underwriting model that previously took a full quarter to build was completed in a fraction of the time. The productivity math is what gave leadership confidence to cut 4,000 jobs from a position of strength, Ahuja said. The decision was part of a longer transformation. “This is a two-year journey for us,” she said. “This was not an overnight decision.” Even with potential productivity gains from AI, research finds that AI adoption alone doesn’t automatically translate to higher profits per employee—it demands a reimagining of how work gets done. In addition, broader market conditions, product expansion, and strategic cost management all play a role. But Block’s case illustrates how targeted AI implementation can significantly amplify human output.
The post Why Block’s COO is tracking ‘gross profit per employee’—and how AI is on track to double it to $2 million appeared first on Fortune.
