Launching and Monitoring Your AI Employee

These steps apply to both first-time and improvement launches.

Determine Launch Phases

1. Start with a limited first launch.

   • Target a smaller group of users to effectively manage feedback and scale.
   • Focus on a smaller set of high-impact test cases so customers can start realizing gains quickly.

2. Create a clear set of phases with the audience, timelines, and exit criteria for each.

Enable Your Workflow

1. Remove testing artifacts.

   • Switch app connections to actual production instances if you were using sandbox environments.
   • Confirm the AI Employee's name and description are appropriate for your current users.

2. Enable your workflow. If you have any pending issues, Ema will prevent you from enabling the workflow until they are resolved.

Add Relevant Users

1. Invite additional admins as AI Employee-level admins.

2. Add regular users as guests.

   • For chat AI Employees being embedded elsewhere, skip this step. Simply embed the chat as required.
   • For project-based AI Employees (such as Document Writer), nominate some users as "Project-level admins." These users can create new projects and invite new users without having admin-level editing privileges.

Create and Share Launch Material

Launch Announcements

Publish launch announcements to each tranche of users via their preferred communication channel.

Onboarding Webinar

Prepare a deck and an end-to-end demo. Set up a launch webinar and walk users through the product. We recommend a hands-on format where users follow along and try the product during the session.

Share the training deck and webinar recordings with users for future reference.

Office Hours

Schedule office hours in the 2-4 weeks following launch so users can drop in and seek help.

Feedback and Bug Tracking

Share a feedback form or spreadsheet that users can use to report bugs and feature requests. Ensure the form:

• Clearly differentiates between bugs and feature requests.
• Captures screenshots and additional details.
• Indicates urgency or priority.

Set up a process to review and address submissions periodically.

Monitoring Adoption and Impact

All AI Employees include out-of-the-box metrics to track usage.

Chat AI Employees

Track:

• Number of chat sessions
• Number of queries
• Number of active users
• Feedback trends (positive and negative)

For detailed chat metrics, see Chat Metrics.

Dashboard AI Employees

Track:

• Total triggers of the dashboard
• Success rates

Additional dashboard metrics are expected to be available soon.

Upcoming Metrics for GWE Workflows

For all GWE-based workflows, the following metrics are being added:

• Total agentic triggers -- Count across agents.
• External tool calling metrics -- Track which tools and apps are triggered most often.
• Workflow success and failure counts.