
Here’s the brutal math of the labor transition facing the American workforce: It takes 30 days for a 25-year-old AI-native college graduate to become productive. Meanwhile, I have employees with 20 years of experience who struggle to shift from their comfort zone to master the new tools.

In the debate about the impact of automation and agentic AI on the American workforce, there are two camps: those sounding the alarm on massive job displacement and those who want to know which specific roles will be eliminated. The difference is stark. Vague warnings will likely only lead to panic and bad policy responses. But, as a country, if we know which jobs are at risk, we can prepare, retrain, and adapt.

When Chinese AI startup DeepSeek launched its R1 model requiring far less computational power than their American peers in January, it was only exposing the limitations Silicon Valley had already begun acknowledging. As millionaire investor Marc Andreessen noted, “we’re increasing GPUs at the same rate, but we’re not getting the intelligence improvements at all out of it.” That’s even before factoring in the supply chain challenge of providing enough chips to keep delivering the current rate of unsustainable growth.

The old outsourcing dilemma of build versus buy is already a time capsule of the recent past. In its 2024 survey of 500 global executives on talent sourcing, Deloitte found that digital transformation and the pace of emerging technologies are forcing organizations to rethink how they source and manage capabilities.