Most companies pilot AI with a small technical team and hope it spreads. SpotOn took the opposite approach, scaling Rovo from a single team experiment to over 1,000 employees spanning Sales, IT, Marketing, Finance, and Operations. Facing tool sprawl, manual work, and fragmented knowledge, SpotOn's team built Rovo agents across the business, logging nearly 50,000 interactions in the first five months.

In this session, SpotOn shares how they embedded AI directly into the workflows teams already run in Jira Service Management, Confluence, Jira and Slack, turning Rovo into the "connective tissue" of the business. You'll see the agents delivering real impact today: cutting drafting time from days to hours, deflecting 55% of questions and saving hundreds of hours a month on manual work. More importantly, you'll learn how SpotOn did it: the adoption framework, the governance model, and the hard won lessons, so you can take the same playbook back to your organization.

Key takeaways:

• A phased adoption framework for scaling Rovo agents from IT into Sales, Marketing, Finance, and Operations, without a dedicated AI team or a custom platform

• Real, quantified outcomes from five production agents (PRD drafting, idea scoring, sales deflection, receipt OCR, and compliance audits) with the decision criteria SpotOn used to identify each use case

• A governance and change management model for sustaining AI adoption at 1,000+ users, including how to build internal champions and keep quality high as agent count scales