This is like a weather report for jobs in the age of AI: it uses data to see which kinds of work are already feeling AI’s impact and how, so leaders can prepare instead of being surprised.
Helps HR leaders, executives, and policymakers understand where AI is actually changing hiring, firing, and task structures today—cutting through hype to identify which roles are at risk, which are being augmented, and how quickly these shifts are occurring.
The defensibility comes from rigorous economic research methods, access to labor-market and firm-level datasets, and institutional credibility (Stanford) that make the findings influential for HR strategy and public policy debates.
Classical-ML (Scikit/XGBoost)
Structured SQL
High (Custom Models/Infra)
Data access and quality for detailed, up-to-date labor-market and firm adoption signals; replicating this at company level requires robust HRIS, payroll, and productivity data integration.
Early Majority
Focuses specifically on near-term, observed employment effects of AI—using empirical economic analysis—rather than speculative long-term automation scenarios, making it directly actionable for HR workforce planning and government labor policy.