DRI Methodology
The Displacement Risk Index (DRI) is a composite score (0–100) measuring the probability and velocity of AI-driven displacement for a given occupation. Higher scores indicate greater near-term risk.
0.25 × Task_Repeatability +
0.20 × Data_Availability +
0.25 × AI_Capability_Match +
0.20 × Adoption_Velocity −
0.10 × Human_Value_Premium
) × 100
Each factor is scored 0–100 based on normalized data from the sources below. Scores are updated quarterly as new data becomes available.
Factor Definitions
Task Repeatability
How much of the role involves repeating defined tasks with predictable inputs and outputs. Derived from O*NET task taxonomy and McKinsey occupational mapping.
Data Availability
Degree to which the occupation's core workflows operate on digitized, structured data accessible to AI systems. Roles working with analog or highly contextual data score lower.
AI Capability Match
Current and projected AI model capabilities against the core competencies required by the occupation. Evaluated against SWE-bench, MMLU, and domain-specific benchmarks.
Adoption Velocity
Speed at which AI automation tools are being deployed in this occupational category. Tracked via BLS hiring trends, Challenger Gray layoff reports, and earnings call AI mentions.
Human Value Premium
Degree to which clients, employers, and society specifically require human judgment, empathy, physical presence, or accountability. Acts as a protective offset against the other risk factors.
Risk Level Definitions
Active displacement underway. Expect significant role restructuring within 2–3 years. Immediate transition planning recommended.
Accelerating automation pressure. Core tasks are being automated. Upskilling in AI-adjacent areas is urgent.
Structural change likely by 2028–2030. Human premium exists but is narrowing. Strategic adaptation advised.
Strong human premium. AI augments rather than displaces. Resilience through 2030+ is likely for current practitioners.
Data Sources
Limitations & Caveats
DRI scores reflect task-level automation potential, not individual worker outcomes. Highly skilled practitioners in displaced occupations often successfully transition.
Regional variation is significant. Displacement rates in major metro areas can differ substantially from rural markets for the same occupation.
DRI scores are updated quarterly based on available research. Rapid AI capability changes (e.g., a major new model release) may cause scores to change significantly between updates.
Occupations with DRI < 40 still face AI augmentation pressure. 'Low risk' does not mean 'no change' — it means human practitioners retain clear value advantages.
Employer restructuring decisions involve financial, political, and organizational factors beyond AI capability alone. High DRI scores indicate elevated risk, not certainty of displacement.