I just ran across this quote in an AI-related post, and I love it:
But in general, take my advice, when you meet anything that is going to be Human and isn’t yet, or used to be Human once and isn’t now, or ought to be Human and isn’t, you keep your eyes on it and feel for your hatchet.
C.S. Lewis
I tend to agree. Most wealth managers/financial advisors seem to be reading from very similar scripts. I don’t think it would be hard for AI to emulate. Some are very different. More tax expertise. Distinctive strategies. But they are rarer.
Portfolio Managers at hedge funds are ramping up their use of AI, adding a great deal of efficiency to their data analytics.
Yes. This is an example of early adopters using AI to advantage. It is also an example of how those who understand how to harness AI benefit from the advantage at the expense of those the advantage displaces, in this case, the need for fewer data analysts.
The winners in the AI labor market will be those who figure out first and best how to use it.
Asset management has always seemed like an area ripe for AI - as it is, most asset managers can’t beat their respective market indices so why not rely more on AI? Are we going to really need legions of highly paid junior analysts when AI can do much of the same research in a fraction of the time.
It looks like AI gave birth to a cottage industry: the so called AI coaches and gurus. And new roles like VP of AI. Some of what these folks do is useful, but to create the impression of importance and to stay relevant, they also seem to generate a lot of noise. Like spamming everyone’s Teams channels with constant messages allegedly promoting “AI tips.” Both my husband and I are beginning to see this at our places of work.
Yikes!
Why? Most financial advisors are sales people. They have to find their own clients and sell them financial products.
Do they know this?
For some reason, they think it’s an easy job, with people lining up for advisers. (I don’t share this belief - my adviser has worked tirelessly to build his clientele & to service their needs well.)
For most people, becoming a financial advisor is a second career. I compare it to being a real estate agent. You did something else and one day decided to become an entrepeneuer, set up shop, pass a couple of tests, affiliate with a firm, call all your professional contacts and now you’re managing someone’s money.
And if you’re not good at raising assets, you work at a bank and prospect the bank’s clients.
AI wont eliminate their careers because it’s relationship driven. Many people can manage their own assets and do a pretty good job.
My kids are both using AI to automate routine tasks but the results will likely be very different.
In my daughter’s case, it will almost certainly reduce the need for entry level positions.
In my son’s case, it will increase his team’s profitability, resulting in higher pay for the team members, and not eliminating any jobs.
It would be nice to think that if financial advisors rely more on AI they would pass the savings on to the client. I suspect though that their motive will be to increase their own profits.
In general, competition would lead to lower costs over time, but that does not always happen. I have negotiated lower fee levels from financial advisors by focusing on what they are actually doing and not doing.
Will there be a decline of math professors, academics in general, in the short turn if AI tools become widespread?
If AI reduces white collar roles, such as academics, PhDs, who would then be left to verify what AI tools are doing? Could AI tools hallucinate solutions to tech problems?
“ AI developers face “a strong commercial incentive… to overstate the capabilities of their products,” the declaration read.
Released “on market timelines” rather than at the pace of human-reviewed science, AI publicity can “misleadingly use specific mathematical tasks as metrics for the general reasoning capacities of commercial models,” it added.Beyond the risk of math being enlisted for commercial gain, the declaration authors said AI systems could produce plausible-seeming but incorrect proofs that are hard for humans to verify, or undermine attribution and credit to researchers on whose work it builds.
They fear increased use of AI in math could incentivize bandwagon-chasing research that takes advantage of the new tools at the expense of other problems, short-circuit peer review systems and put researchers at the service of AI developers, rather than self-directed free inquiry as in universities.
AI also has potential harms in the shape of “warfare, mass surveillance, political disruption and environmental damage,” the authors wrote.
They urged individual mathematicians to “evaluate the ethical consequences of your research, and if necessary withdraw from harmful work.””
What about economists? Are we in a AI bubble? Heard a discussion on Bloomberg with an AI skeptic:
From Zitron’s latest article:
“
If you can’t measure how good something is, how much it might cost, or what your return on investment might be, it’s fair to ask why you’re even paying for it in the first place.
People are (reasonably!) harping on about the ROI problem, but I think the “can’t really measure the cost” part is an even bigger problem.
Yesterday, Microsoft’s GitHub Copilot moved all customers to token-based billing from a premium request model (as I reported a week before everyone) as users had been allowed to burn thousands of dollars of tokens on a $39-a-month subscription.“
AI Doesn't Have ROI “
A study conducted that WFH, not AI was largely responsible for grim hiring prospects for new graduates. The study does not discount the very real possibility that AI would become the main driver of unemployment for new graduates in the future.
More details.
https://www.npr.org/2026/06/01/nx-s1-5843076/remote-work-college-graduates-unemployment-ai
When someone’s performance review hinges solely on productivity, that person would avoid mentoring newbies because mentorship requires extra effort and time.