AI tools are becoming more capable, but they still don’t understand how work actually happens.
Over the past while I’ve been spending time inside a business, focusing on how day-to-day operations are supported by systems and processes.
The work involves stepping back from the noise, breaking down complex or frustrating workflows, and helping teams make better use of the tools they already have — whether that’s simplifying forms, removing repetitive steps, or introducing small automations that save time and reduce stress.
What’s struck me most is how often the real issues aren’t technical at all. They’re caused by mismatches between how work is assumed to happen and how it actually happens on the floor.
When those assumptions are wrong, systems tend to add friction rather than remove it — even when the technology itself is sound.
It’s hands-on, practical work, and I’ve enjoyed seeing how relatively small changes can make a real difference to how people experience their day.
AI tools are becoming increasingly capable, and they can absolutely help with implementation. But they still depend on someone first taking the time to understand the work itself.
For now, at least, clarity still comes before automation.