This episode of the Techzine TV Podcast comes to you from Atlassian Team Europe, Atlassian's annual event in Barcelona. Sander and Atlassian CTO Rajeev Rajan discuss the company's pragmatic approach to AI. A key part of that is that Atlassian maintains strict data privacy principles. That is, it doesn't train its AI on customer data. Still, it aims to deliver powerful AI capabilities through Rovo.
Rajan explains how the Teamwork Graph technology connects work data across 80+ applications, enabling permission-aware search and intelligent agents. He addresses the reality that only 4% of companies see company-wide AI benefits today, emphasizing the need for both C-level commitment and grassroots experimentation. The conversation covers AI model selection, data sovereignty, automation strategies, and why Atlassian focuses on end-user scenarios rather than building LLMs.
Key takeaways:
• Atlassian doesn't train AI on customer data - they're custodians, not owners
• The Teamwork Graph connects data across 80+ apps with permission-aware access
• Rovo offers three capabilities: search, chat, and autonomous agents
• AI adoption requires both top-down goals and bottom-up experimentation
• Only 4% of companies currently see broad AI benefits
• Atlassian uses multiple models (OpenAI, Claude, open source) for different use cases
• Data residency available in 11 regions for sovereignty requirements
Chapters:
0:09 - Introduction to Atlassian's AI Strategy
1:06 - Rovo AI Platform Overview
2:16 - Data Privacy and Responsible AI
3:09 - The Teamwork Graph Technology
9:04 - AI Adoption Challenges in Enterprises
11:16 - Top-Down vs Bottom-Up AI Strategy
15:17 - The Future Impact of AI
17:00 - Background and Building World-Class Teams