Will AI Take My Job?

It feels like hardly a week goes by without another clickbait headline asking, "Will AI take my job?"

While it no doubt sparks conversation around the water cooler, I don't care much for the question. Not because I'm special, or because my job can only be done by me, but because I think it asks the wrong thing.

To me, AI is a tool for replacing tasks, not professions.

Given my role is to generate evidence that helps make places better, I prefer to ask a different question:

Can AI help me generate better evidence?

Sometimes, the answer is yes.

AI is an extraordinary tool if you need continuous pedestrian counts, cycle volumes, movement patterns or near real-time monitoring. It collects huge volumes of consistent data that would have been impractical—or prohibitively expensive—to gather only a few years ago.

It can now identify pedestrians, cyclists, scooters and vehicles, measure movement and generate continuous data around the clock—all without relying on facial recognition or storing identifiable imagery.

But cities are complex, and not every question can be answered by detecting movement.

If a town centre is underperforming, the important question often isn't how many people visited. It's why.

Why do people avoid one side of the street? Why do they linger in one public space but not another? Why do two places with similar pedestrian numbers produce completely different economic outcomes?

Those questions require more than detection. They require an understanding of behaviour.

Do people feel comfortable staying? Do public spaces invite interaction? Do streets work well for people of different ages and abilities? Where do conflicts occur between different users? These are the kinds of observations that help explain the numbers.

This doesn't mean AI and technology aren't valuable. They absolutely are. The opportunity lies in combining the strengths of both approaches: collecting large volumes of consistent data over long periods while also understanding the context, behaviour and stories behind the numbers.

In that sense, the future isn't AI versus traditional surveying. It's about using the right tool for the right question.

A transport project may need continuous movement data. A town centre revitalisation project may need to understand why people stay, interact and return. A public space evaluation may require both.

Good decisions don't always come from collecting more data. They come from collecting the right data—and understanding what it means.

Of course, I could be wrong.

In which case, I may need help finding a new job.