Is the Dashboard Dead?

AI isn't just changing what data teams build. It's changing what they should spend time on. In part one of this series, we talked about why data teams are at risk and what makes them irreplaceable. In part two, we get practical.

The biggest barrier to becoming a high-value, proactive data team isn't skill. It's capacity. Most data professionals are already at full stretch, and proactive work sounds like more work on top of an already full plate. It isn't, if you remove the right things first.

You'll leave with a practical framework for auditing your current workload, a simple method for proactive investigation, and a clear challenge to take into the week ahead.

What we’ll cover

• A framework for auditing your current workload: and deciding what deserves human time in 2026
• What automation is actually for: freeing up human time for higher-value tasks, not replacing people
• What proactive analysis looks like in practice: a simple workflow you can start using this week
• How to measure and communicate your impact in business terms, not data terms
• How modern collaborative tools like Count unlock this way of working at scale

Who should attend

Data analysts, BI developers, data engineers, and data team leads who are ready to stop defending their seat at the table and start owning it.