Azeem Azhar

And all of that explains why perhaps the direct translation of the very, very rapid rollout and deployment of these technologies is for now going a bit more slowly.

I mean, another fascinating data point I saw from an academic paper that came out of, actually, I don't know where it came out.

I'm so sorry about that, but the academics were Hosseini and Lichtinger.

They were looking at the number of firms posting the job category of AI integrator.

And of course, that number has jumped significantly since 2023.

The point being that there is a recognition that you need somebody who understands how to put these systems in place.

And an AI integrator is exactly the kind of job you'd expect a general purpose technology to create.

Remember, general purpose technologies are complex.

generally useful across the economy.

They lend themselves to persistent and perpetual improvement and they generate complimentary services, which in this case could be new types of jobs.

Is all of this fast or slow?

Perhaps the question is really, is this fast enough considering the investment that's going into AI within companies and across the economy in general?

For lots of people, this story is slow.

You know, there are roadblocks, there are problems.

It is difficult.

It's proving to be difficult.

But in truth, this isn't a case of not ever.

It's a case of not yet for most, I'd say virtually all of these companies.

You know, what they're doing is something that's new.

It's something that's complicated.