Compilation Episode (Part 5): Will AI Take My Job?

And why does it feel like AI's forcing companies to rethink how work is organized and not just what tools we're using? So it feels like it's not just like, "Oh, I'll pull this in." It's changing much more.

Well, I would actually argue that companies aren't doing that enough.

Hmm.

Okay.

Uh, that co- companies don't have any experience in adopting general purpose technologies.

They, they've, they haven't-- n- no one here lived through moving from steam power to electricity, and very few senior management teams really, uh, were senior leaders during the launch of the internet, which is probably the closest analogy, although I think the real innovation at that period of time that, uh, caused me to sit up and take notice about the internet was when the Mosaic browser that, that could move th-the internet from alphanumeric only to have images and photography, and that was just my jaw dropped, and I said, "The world's gonna change now." Um, what-- but so what companies have been doing too much is saying, "How do I append AI, particularly generative AI, to my existing process?" Almost like it's just another big new SaaS system.

Hmm.

And in fact, because it's a general purpose technology, th-that's the wrong question.

The, the, the right question is: How do I reconfigure my process around the a- this general purpose technology, around the AI? And yes, you're seeing companies, um, I would p-point to companies like Procter & Gamble and Coca-Cola and consumer goods, uh, JPMorgan Chase, um, who are being really pretty aggressive in the way they're deploying AI.

S- use Google obviously as a, uh, a, as a, a core AI innovator.

But what those companies are doing is taking very important processes and reconfiguring them around the AI, and that's what this calls for.

Hmm.

Um, and, and, uh, I think a lot of the numbers we see about the failure of AI experiments are, yeah, badly configured experiments fail.

You'd be surprised.

And when they're putting together through successful experiments, um, and pushing, what part of the org chart is the pressure hitting the most?

Yep.

Right now, it's hitting entry-level and lower managerial jobs, and the reason for that is those jobs often have, um, tasks that are heavily what I'm gonna call rules-based.

A good example is a credit analyst.

If you're, you get hired out, out of an undergraduate business program to be a credit analyst at a bank or, or for a company that does what's called vendor financing, I will lend my customer the money to buy my goods.

Y- when you start off, you're basically just applying a set of rules.

You've been told companies of this size, of this history with us, of this volume with us, um, you know, not more than X dollars, you know, here are terms, here are the interest rates you're gonna charge, et cetera, et cetera.

And usually for large companies which are beingquicker to adopt AI 'cause they can afford it, um, they've got a lot of data.

So a rules-based decision where you've got lots of longitudinal data, that's almost a perfect environment for AI.

So a lot of those tasks that have those features tend to reside in lower managerial ranks and the people they supervise who tend to be entry-level workers or what a lot of companies call individual contributors who are out of that entry-level kind of probationary status, but are, but are still, uh, doing core work of, of the company, but they're not decision-makers.

Okay.