As AI shifts to becoming an embedded teammate in your system of work, enterprises are learning a hard truth: AI isn’t failing because it's not smart enough, it stumbles because the data it relies on lacks shared context and meaning across the organization.

In this session, we’ll explore how you can unlock context-rich, “AI-ready” data with Atlassian. By leveraging data that’s connected, governed, and grounded in a common ontology, humans and agents can work better together, unlocking new opportunities for your organization.

We’ll show how a unified metadata layer, cross-system lineage, data quality metrics, and policy-driven access controls create the semantic context your organization needs to make high‑stakes decisions with confidence.

We’ll also take a practical look at how this can accelerate decision-making across your teams — shifting from the “service desk” model for analytics to enabling agents to act as reasoning engines, helping your teams innovate faster. 

Key takeaways

• Identify ways to audit critical metrics and definitions and close gaps in your organization's shared context.
• Build a foundation for AI-ready data, mapping lineage, data quality, and establish policy-aware access.
• Empower teams to use AI agents for routine analytics and decision support, reducing bottlenecks.