Block, Amazon, Synopsys and Cloudflare Executives on Rethinking Work in the Age of AI Agents

At a recent Fortune Most Powerful Women panel, executives from Block, Amazon, Synopsys and Cloudflare described how artificial intelligence is reshaping not just individual workflows but the structure of their organizations.

Block CFO and COO Amrita Ahuja said the payments company set out to fundamentally refactor how it operates, cutting its workforce by 40% earlier in 2026 while pushing AI deeper into engineering. Code review speed has improved 150% among engineers and 60% among employees outside engineering, and roughly 15% of code changes now move through the pipeline nearly fully automated. Even with those changes, Ahuja said Block remains convinced that a company built around AI still needs a human at the center, and she expects most organizational charts going forward to include AI agents sitting alongside human employees rather than replacing the chart entirely.

Synopsys CFO Shelagh Glaser offered a more cautionary note, saying AI spending inside the company "was pretty reasonable until it wasn't," which pushed Synopsys to build its own internal metering system to keep usage and cost under control as adoption spread across teams.

Cloudflare co-founder, president and co-chair Michelle Zatlyn said the roughly 5,000 person company now hires both employees and AI agents, and that Cloudflare has committed to bringing on more than 1,000 interns in 2026 specifically to build AI-native teams from the ground up. As one example, she pointed to a finance director who successfully deployed AI agents within the finance function and has since moved into leading Cloudflare's broader AI transformation effort.

Amazon vice president Heather Zorn, who oversees customer experience, products and services, said her team's approach is to build something that wins for the customer first, then work out how it also wins for the business, tracking returns through adoption, engagement and efficiency metrics rather than any single number. That gap between adoption and proven payoff shows up more broadly in the data too: a OneStream survey found that 74% of finance leaders say AI is cutting manual work, but only 14% say their AI investments have delivered real enterprise wide value, and just 6% of finance organizations qualify as full AI leaders across every metric the survey tracked.