Signal to decision: AI-native planning through any disruption

You know the drill. A big order comes in and you can only fill half of it. The plant emails to say a line is down until Thursday. Your carrier drops a lane the same week as your promo. You find out about a competitor’s promo after it’s already running in your region. Somehow it all lands on one planner’s desk, usually at 4:45 on a Friday.

AI agents are everywhere right now, and the promise is real: an always-on agent that spots each exception and its root cause the moment the signal lands. But like any new hire, it has to earn its place in that Friday pileup. Give it a solver fast enough to keep up with the day, and it works out the fix while there’s still time to act. Give it clear approvals, and it acts on its own wherever your team allows. Give it a way to learn from your planners, and the next time that exception shows up, it’s already handled.

Join Stijn-Pieter van Houten and Sara Hoormann as they walk through an AI-native decision journey in Lyric Studio, from the first signal to the final call, including:

• Why most planning stops at “do we have the stock?”, and everything after that eats up someone’s afternoon.
• Where Lyric Studio’s fast solver pays off, and why “we’ll rerun it tonight” doesn’t cut it anymore.
• How a planner’s fix becomes the agent’s playbook.
• What to look for when you evaluate agents that act on your behalf.