Atlassian CEO: Only 4 of 13,000 Employees Could Use Our AI Tool When We First Bought It
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Atlassian CEO: Only 4 of 13,000 Employees Could Use Our AI Tool When We First Bought It
"“4 people at Atlassian were allowed to use it out of 13,000.” Today, after months of post-acquisition security work, all 13,000 employees use it. The bottleneck was security infrastructure. “The security of the AI in the browser is too much,” Cannon-Brookes said of the lag between buying a tool and being able to deploy it across a regulated workforce."
"“The talent changes you require are quite high. The business process re-engineering you require is difficult,” he said. He admitted that an AI talent bench simply doesn't exist yet: “It's not like we have people with 10 years worth of AI deployment experience inside the organization. They don't exist in the world.”"
"“Some of our customers take 6 months of queries to turn on our AI platform. Some turn it on in a day,” Cannon-Brookes said. The variance maps directly to a customer's pre-existing security, governance, and data posture."
"Atlassian's answer is its Rovo platform, which surpassed 5 million monthly active users in Q2 FY26. Rovo is built around the enterprise controls that typically gate AI rollouts: data residency, private model choice, customer-managed keys, and compliance controls. Inside Jira, work items can be routed to coding agents like Cursor or Claude Code, or to business agents from Salesforce's Agentforce."
Before acquisition, only a small fraction of employees could use an AI browser due to security constraints. After months of security work, all employees gained access, showing that security infrastructure can be the main deployment bottleneck. AI rollout also requires significant organizational changes, including new talent and business process re-engineering. A lack of experienced internal AI deployment teams limits speed. Customer readiness varies, with some organizations taking months to enable AI platforms while others enable quickly. The Rovo platform targets these constraints by providing enterprise controls such as data residency, private model selection, customer-managed keys, and compliance features, enabling safer deployment within existing governance frameworks.
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