For many organizations, the initial excitement of deploying Atlassian Rovo has been replaced by a quiet trust crisis. Employees get outdated, irrelevant, or conflicting answers and slowly stop using the tool altogether. The problem isn't the AI. It's the knowledge it's reading from.
In this on-demand session, George Elshamaa, Senior Technical Consultant at ServiceRocket, and Dan Tombs, Senior Solutions Architect at AppFire, make the case that AI reliability is above all a knowledge management challenge, and share what leaders, admins, and operations teams can do about it today.
In this session, we covered:
- How poor content hygiene translates into wasted AI cycles and real business cost, including research showing employees spend up to 30% of their week just looking for information
- A practical framework to audit your Confluence spaces, identify stale and duplicated content, and use native automation to archive inactive pages without disrupting the business
- How to make knowledge accessible to Rovo while keeping the governance controls that prevent it from surfacing what it shouldn't, and why that balance starts with people, not settings
- The metrics that signal whether your organization is genuinely AI-ready: adoption, content freshness, knowledge deflection, domain coverage, and time to productivity for new joiners
- What to do the moment Rovo gives a wrong answer, and why a hallucination is actually a real-time signal pointing you to the knowledge that needs fixing
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