As AI capabilities expand, most organisations are trying to scale automation across DAM, PIM, and downstream systems.
But scaling isn’t always the problem.
Many environments already have tools, integrations, and automation in place.
What breaks is how those pieces behave together under real conditions.
Across teams, the pattern is consistent: automation works in isolated use cases – but breaks when extended across systems, handoffs, and decisions. Not because the technology fails but because the system doesn’t hold.
This session focuses on where that breakdown happens:
- Where handoffs between systems fail under volume.
- Where governance arrives too late to shape outcomes.
- Where human review becomes a bottleneck instead of a control.
- Where outputs scale – but decisions don’t.
These are the points where scale breaks.
Attendees will leave with a simple lens to see what will hold, what will break, and what to address before scaling further. Because adding more AI doesn’t fix this. It shows you exactly where it breaks.