AI is beginning to impact labor not by firing employees, but by reducing the need for new hires, particularly in white-collar roles like consulting and business services. This will likely suppress wage growth at the higher end, creating a natural rebalancing of the K-shaped economy from the top down.

Previous technological shifts primarily automated low-skill jobs, widening inequality. AI, however, is poised to replace or augment tasks done by high-earning knowledge workers. This could lead to a compression of the wage distribution, a reversal of historical trends driven by technology.

History shows that social stability is threatened not by the long-suffering poor, but by a disgruntled, overeducated middle class. AI's displacement of junior roles in tech and law creates a cohort of indebted graduates who played by the rules but now face unemployment. This group is far more likely to cause political and social unrest.

Contrary to long-held predictions, AI is disrupting high-status, cognitive professions like law and software engineering before manual labor jobs. This surprising reversal upends the perceived value of higher education and traditional career paths, as the jobs requiring expensive degrees are among the first to be threatened by automation.

The political hope is that AI-driven productivity will solve the national debt. The overlooked danger is that AI's first casualties will be highly-paid, indebted professionals (bankers, lawyers), whose mass defaults could crash the financial system before any 'age of abundance' arrives.

Contrary to fears of mass unemployment, AI's biggest losers will likely be the upper-middle class. The traditionally secure, high-paying career paths in consulting and law are highly susceptible to AI disruption, while other socioeconomic groups may see more benefits.

Recent graduates are surprisingly resilient to AI displacement as they are digitally native and relatively inexpensive. The greatest risk is for costly, mid-career employees whose work can be done almost as well by a recent graduate leveraging AI for a fraction of the salary.

Contrary to popular belief, highly compensated cognitive work (lawyers, software engineers, financiers) is the most exposed to AI disruption. If a job can be done remotely with just a laptop, an advanced AI can likely operate in that same space. Physical jobs requiring robotics will be protected for longer due to cost and complexity.

Contrary to fears of automating low-skill work, economist Alan Blinder argues that AI is more likely to replace high-paying white-collar jobs in finance and professional services. Lower-wage manual and service roles are less vulnerable, a dynamic which could potentially compress the upper end of the income distribution.