
What happened
Dropbox CTO Ali Dasdan says he raised AI tool adoption among engineering, product, and design teams from under 40% to full adoption using training, hackathons, and AI superusers.
Why it matters
Dasdan's bottom-up approach lets departments choose their own AI tools rather than having IT mandate them. Hundreds of custom apps have been created by non-technical employees.
What to watch
The test is whether this decentralized model scales. Dasdan notes token spending is a budget item all departments must track as AI usage grows.
WHO IT HITSEnterprise IT leaders and department heads at large companies can look to Dropbox's approach as a case study for driving AI adoption: leadership sets support, removes barriers, and employees choose their own tools.
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Ali Dasdan joined Dropbox as CTO in March 2025, coming from ZoomInfo with plans to start his own agentic AI company before Dropbox CEO Drew Houston convinced him to join. At the time, less than 40% of Dropbox's engineering, product, and design teams were using AI tools. Dasdan achieved full adoption across that population by focusing on training, hackathons, AI superusers, and clear metrics on how tools like Claude, Codex, and Cursor speed up work.
The approach Dasdan describes is deliberately bottom-up: leadership removes barriers, and employees experiment on their own. Beyond engineering, Dropbox made ChatGPT Enterprise widely available and approved AI features in Workday, Slack, and Zoom. Non-technical workers have used Lovable to build their own applications, and the company created Nova, an internal platform for coding agents that non-developers can also access in a monitored environment. This reflects a broader pattern where AI spending is moving outside IT budgets, though Dasdan acknowledges token costs are a budget item every department must measure as usage grows.
The stakes for Dropbox hinge on whether this decentralized model produces sustained efficiency gains in customer support and security work without creating cost or compliance problems. For other companies watching, the question is whether letting employees pick their own AI tools at scale delivers results or creates unmanaged risk.
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