AI’s impact on productivity and the workforce

5 minutes 12 seconds

0:04 Fiona Greig: So Joe, we've been involved in a big think on megatrends and spent the last couple of years building a proprietary model to understand the impacts of megatrends not just on our economy, but our lives. Give us an overview.

0:18 Joe Davis: Megatrends are a number of forces that affect the economy, the markets, because there's a lot of debate out there what AI may or may not do.

0:25 And I think that has several implications. It has implications for growth. It has implications for standards of living. It also has implications for stock and bond returns because of the assumptions, either of low assumptions of productivity in the future, meaning our worker, our work productivity, and what technology may or may not do.

0:44 So this matters a lot in terms of the future of work and the future of the labor market, which has profound implications for growth, for the earning potential of companies, which then when you get the stock and bond markets and the risk of inflation given some of the demographic concerns we have.

1:01 So this matters a lot, and it matters for us as workers as well as for us as investors.

1:07 Greig: Yeah, and we think AI is likely to be as disruptive as the personal computer, which, you know, I think the personal computer didn't actually eliminate jobs.

1:17 What it did and what we think AI will do is augment them, right? Some 60% of jobs will be augmented by AI, right? AI will become this power tool that unlocks efficiency, productivity for the worker.

1:31 Davis: I would not be shocked that five years from now things such as healthcare analytics being fed in the financial plans to give a better sense of longevity assumptions which lead to the financial advice.

1:41 I think in five years there are actually table stakes, and that's when it would be called augmentation.

1:45 I'm not a financial advisor, but I think it has profound implications for the whole industry. Things such as the ability to potentially scale your practice, because the head advisor’s in high demand but there's only 24 hours in a day.

1:59 It means that you can spend, in theory, less time devising each financial plan, but the value of the plan goes up because it has more capabilities in it.

2:06 This is effectively what happened to automobile manufacturing, by the way, over the past 30 years.

2:11 And so behavioral coaching will matter, it will always matter, but I think it won't just be behavioral coaching.

2:19 Greig: What I think is amazing about the work is that, you know, we looked at 800 occupations, not just financial advisors, right? And for every single one of them, what are all the tasks involved in that occupation and how many of those will be augmented or replaced by AI, right?

2:36 And I think what we learned is 20% of those occupations, there's going to be very marginal impact; 60% there's going to be a real meaningful impact, potentially, you know, augmentation that we're talking about. And then 20% almost eliminate the job.

2:50 So, you know, the example of the nurse, right, is probably in that 60% range, where a nurse, with the augmentation of AI, can spend much more time with the patient, much more time on those high-value, meaningful tasks, less time typing up, you know, the visit.

3:09 And I think that's what's interesting about the work, that granularity across all of those occupations and understanding the impact on those specific tasks.

3:19 Davis: And it's data-driven, then we can aggregate that with a macro implication.

3:21 The consensus is assuming that AI is effectively marginal. Our diagnostics are saying unlikely; it's actually only 20% of occupations it’s going to have a marginal effect. Four out of five jobs, we're going to see disruption, but not elimination.

3:36 So this has profound implications. It has implications for interest rates and fixed income investments.

3:41 And we'll continue to update these analytics because I truly believe this is an innovative way to look at this framework across all these competing dimensions that affect the global economy.

3:52 Greig: But I think we're doing here really is putting AI into perspective, right? Is it going to be more like social media, which has been frankly a nuisance in my life, or is it going to be more like electricity, which unlocked, you know, the ability for kids to read at night safely without candles, right?

4:12 So that kind of positioning of AI, I think it's somewhere in the middle, right? Or maybe closer to electricity?

4:18 Davis: Our model does not know exactly where it will manifest, but it is saying that there's a likelihood.

4:25 So for AI to be transformative, it’s going to have to be in one of three areas. Because it's got to be an area that increases—it meets an unmet human need, reduces cost, but increases quality on a significant scale, that we all as human workers and consumers face.

4:39 And those three areas include clean and cheaper energy. Secondly, it would be some dimensional on healthcare. And the third would be along education.

4:48 Now, I don't know which one it will be, but our framework is saying the odds are fairly high that over the next five years we will start to see material knock-on beneficial effects in one of those three areas, which is really encouraging.

5:01 Greig: Fascinating.