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