Unlike past industrial shifts, AI's impact won't be contained to specific industries. Once AI can perfectly replicate a human worker behind a keyboard, video, and mouse, it will trigger a simultaneous displacement wave across all remote-capable jobs.

AI's core strength is hyper-sophisticated pattern recognition. If your daily tasks—from filing insurance claims to diagnosing patients—can be broken down into a data set of repeatable patterns, AI can learn to perform them faster and more accurately than a human.

AI will primarily threaten purely cognitive jobs, but roles combining thought with physical dexterity—like master electricians or plumbers—will thrive. The AI-driven infrastructure boom is increasing demand and pushing their salaries above even those of some Silicon Valley engineers.

AI is rapidly automating knowledge work, making white-collar jobs precarious. In contrast, physical trades requiring dexterity and on-site problem-solving (e.g., plumbing, painting) are much harder to automate. This will increase the value and demand for skilled blue-collar professionals.

Unlike past technological shifts where humans could learn new trades, AI is a "tractor for everything." It will automate a task and then move to automate the next available task faster than a human can reskill, making long-term job security increasingly precarious for cognitive labor.

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.

Industries with fixed demand (accounting) will see job losses as AI handles the necessary workload. Sectors with expandable demand (software engineering) may absorb AI's productivity gains by creating vastly more output, thus preserving jobs for a longer period.

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.

As AI systems become infinitely scalable and more capable, humans will become the weakest link in any cognitive team. The high risk of human error and incorrect conclusions means that, from a purely economic perspective, human cognitive input will eventually detract from, rather than add to, value creation.