Juggling Dynamite

It now takes the average US worker 24 weeks to find a job after losing one, nearly a month longer than a year ago, according to federal data.

The hire rate—the number of hires as a share of overall U.S. employment—was just 3.3% in June, according to the Labour Department; below the 3.9% level in February 2020 and much less than the 4.6% registered in November 2021, when the job market was surging back (chart below since 2015, courtesy of WSJ.com).One in five employers surveyed plans to slow hiring further in the second half of 2025, almost twice the rate of companies that anticipated bringing on fewer people at this time last year. See, More US Companies Plan to Slow Pace of Hiring in Second Half of 2025.

Some CEOs have been bragging to investors about their shrinking workforces and plans to be more productive with fewer employees.

Tariffs have weighed on manufacturing, among other sectors, while workplace raids have hurt immigrant-dependent industries such as landscaping and meatpacking.

Multiple independent projections suggest that the US will experience negative net migration in 2025—a demographic shift not seen in at least 50 years.

Net negative migration, along with non-replacement birth rates, is another drag on GDP growth.

Weak job growth is an economic warning. As the economy starts losing jobs, the process can feed on itself, leading businesses and consumers to pull back, layoffs to pile up, and the country to slip into a recession.

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A new MIT report concludes that 95% of generative artificial intelligence (AI) pilots are failing to translate into revenue growth:

The GenAI Divide: State of AI in Business 2025, a new report published by MIT’s NANDA initiative, reveals that while generative AI holds promise for enterprises, most initiatives to drive rapid revenue growth are falling flat.

Despite the rush to integrate powerful new models, about 5% of AI pilot programs achieve rapid revenue acceleration; the vast majority stall, delivering little to no measurable impact on P&L. The research—based on 150 interviews with leaders, a survey of 350 employees, and an analysis of 300 public AI deployments—paints a clear divide between success stories and stalled projects.

Reality about the insane overshoot in share prices is beginning to be admitted openly, see OpenAI’s Sam Altman sees AI bubble forming as industry spending surges:

“When bubbles happen, smart people get overexcited about a kernel of truth,” Altman told a small group of reporters last week.

“Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes. Is AI the most important thing to happen in a very long time? My opinion is also yes,” he was quoted as saying.

Altman appeared to compare this dynamic to the infamous dot-com bubble, a stock market crash centred on internet-based companies that led to massive investor enthusiasm during the late 1990s. Between March 2000 and October 2002, the Nasdaq lost nearly 80% of its value after many of these companies failed to generate revenue or profits.

His comments add to growing concern among experts and analysts that investment in AI is moving too fast.

Historical studies show that 78% of forward 10-year equity returns are driven by starting valuations. When starting valuations are low, returns have averaged double-digit over the following decade. When starting valuations are at historic highs, equity returns have been flat to negative over the following decade.

Today the S&P 500 price is 5.3x the book value of underlying assets of the companies (was 5.1x at the 2000 peak), its price is 3.2x the sales of the companies (was 2x in 2000), the price to 12-month forward earnings is 28x (vs 25x in 2000), its dividend yield is 1.2% (same as in 2000), its market capitalization to US GDP is 212% (vs 150% in 2000). The US stock market was valued at 37% of global GDP in 2000; today it’s valued at an all-time high of 50% of global GDP. The chart below, courtesy of Bloomberg, shows the current all-time high in a composite of these valuation metrics since 1900 in gold, with the S&P 500 price underneath in black.
The tech-heavy Nasdaq index fell 78% from March 2000 to October 2002 and did not recover its 2000 price peak until 2015. The S&P 500 fell 50% and did not durably recover its 2000 peak until 2013. Emerging markets fared better, but still lost 40% from 2000 to 2002, as did Canada’s TSX.

Even major financial product companies like Vanguard, Goldman Sachs and Morgan Stanley are now acknowledging that, from present levels, government bonds are priced to outperform equities over the next decade. And yet, the public is heavily allocated to the riskier assets, with very little in bonds or cash equivalents.