The Career Transition Map

Feb 07, 2026

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Many still miss the point that the AI paradigm is both automation and augmentation.

I’ve been arguing now, for a few years, that AI automates the bottom (meaning the undifferentiated tasks), it squeezes the middle (the tasks that while differentiated are hihly vertical and narrow), it raises the top middle (the more complex, ambigous, and less vertical tasks), while it amplifies or even more compounds the top (domain expertise).

This is the mental model you need to keep in mind.

Indeed, this connects with a great read, from FT’s Tej Parikh, which made a critical observation that cuts through the noise: the AI job-apocalypse narrative confuses correlation with causation.

The piece argued that the drop in US job vacancies predates ChatGPT’s release and dovetails instead with the Federal Reserve’s 500-basis-point rate-hike cycle. The 54,836 AI-linked layoffs in 2024? That’s 4.5% of total job-cut announcements.

But here’s what the article reveals that matters more for strategic career positioning: AI isn’t sorting the labor market into winners and losers—it’s transforming job content across a broad swath of the economy. In there, the Burning Glass Institute’s analysis of millions of job postings shows that even as AI automates certain skills, it simultaneously elevates demand for others—often within the same roles.

This is the Automation-Augmentation Paradox: the same technology that threatens to eliminate 90% of routine task content is expanding what the remaining 10% of judgment-intensive work can accomplish.

In short, there is a sweet spot in the automation-augmentation paradigm that is probably the most important signal to look for, as we move ahead in this AI wave.

Let’s see the implications of it, what it means, and why it matters to determine what’s next in your career.

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