Is White Collar America About to Be Replaced by AI?
The jobs market is beginning to crack…
In the last month, numerous major corporations have announced significant layoffs. Proctor and Gamble is laying of 7,000 people, roughly 15% of its non-manufacturing staff. Microsoft announced it will be firing 6,000 people, most of them managers. Even Walmart has said it is laying off 1,500 positions in sales, tech, and advertising.
The cause of these layoffs is NOT economic contraction… rather, white collar corporate America is finding itself rendered redundant by Artificial Intelligence (AI).
Wall Street has heralded the AI revolution as being great for corporate productivity and profits. AI-related companies like Nvidia (NVDA), Palantir (PLTR) and others have seen their shares prices EXPLODE higher in recent months, adding hundreds of billions of dollars to their market capitalizations.
However, the flip side of this increase in productivity is that it means a LOT of people could potentially lose their jobs. Remember, AI doesn’t require a salary or benefits. And if there’s one thing corporate America has proven, it’s that it greatly values profits over people.
If you think this issue has yet to hit, you’re mistaken. As of the end of February, employers had already announced plans to lay off 220,000 workers, many of them managers or higher. As the Daily Mail notes, this is the highest layoff rate since April of 2009 (at the very BOTTOM of the Great Financial Crisis).
How bad will this get?
Dario Amodei, CEO of AI-firm Anthropic, recently told Axios that he believes AI could erase HALF of entry-level white-collar jobs.
Not half a percent, but HALF as in 50%!
What are the implications of this for investors?
It’s possible the U.S. might enter a technical recession in the coming months as unemployment rises, NOT due to the economy rolling over, at least not at first, but due to AI-induced layoffs. Remember, the people being laid off are white collar workers with higher levels of income. When they lose their jobs it puts a significant dent in consumer spending.
Moreover, as much as AI might improve productivity and cut costs, at the end of the day, it is the consumer, NOT computers, that drives economic growth in the U.S. And as the trade war has shown us, consumers can rapidly change their spending patterns if they get scared enough (Walmart, McDonalds, Southwest Airlines, Chipotle and even Pepsi-co warned of a major downturn in consumer spending in April as the trade war roiled the stock market).
How can investors profit from this?
By employing two strategies.
One strategy should consist of allocating capital in the best AI-companies to profit from this technological revolution (see NVDA and PLTR to name two). At the end of the day, our goal as investors is to make money, and so we need to ride major market trends when they happen.
The other strategy consists of keeping an eye on the exits for any signs that the stock market is peaking and ready to roll over should consumers get concerned enough that they begin to pull back on spending to the point of potentially triggering a recession. At the end of the day, all major market trends eventually end and the bull market in AI-stocks will be no different. They key for us as investors is to ride this trend for as long as possible before stepping to the side when things finally roll over.
Regarding that latter point, we recommend our clients use a proprietary trigger we’ve developed that flashes prior to major market downturns. This signal would have predicted the 1987 Crash, the Tech Crash, and the 2008 Great Financial Crisis.
We detail this trigger, how it works, and what it is saying about the stock market today in a special investment report titled How to Predict a Crash.
Normally this report would be available to our clients but given the potential for AI to really upset the labor market in the coming months, we are making 99 copies available to the general public.
To pick up one of the remaining copies…
Thank you for reading.
Graham Summers, MBA
Chief Market Strategist
Phoenix Capital Research