SA-AIRS™ Methodology

The System Behind
Every Score

SA-AIRS™ is a weighted, multi-dimension audit methodology designed to model AI career displacement risk with full explainability. Not a quiz. Not an opinion. A structured audit calibrated against real cohort data.

Five Dimensions of Risk

The assessment evaluates five independent dimensions of your role. Each dimension targets a distinct driver of AI displacement. The composite score is a weighted combination of these five dimensions, where higher scores indicate greater displacement risk.

D1Task Structure

How predictable and rule-based your core daily work is. Highly patterned work — even complex-looking work — is the primary target for automation.

D2Automation Feasibility

Not theoretical AI capability — whether tools available today can replicate your actual deliverables. Scored by auditing real role outputs.

D3Market Conditions

The supply side of displacement. When AI enables consolidation, which roles and markets feel it first is determined partly by supply-demand dynamics.

D4Decision Complexity

Work requiring multi-variable judgment, ethical trade-offs, or real-time contextual decisions is substantially harder to replicate at scale. We measure actual decision latitude.

D5Human Context Dependency

Work embedded in personal trust, political context, or relationship capital resists automation by design. We measure how deeply your role depends on being human.

// Exact dimension weights, scoring rubrics, and calibration data are proprietary. Full methodology is shared with clients who complete a Full Report or Deep Dive engagement.

Five Tiers, Specific Guidance

The composite score (0–10) maps to one of five risk tiers. Each tier comes with specific action guidance — not generic advice.

Low Risk
Complex, trust-dependent work. The moat is real — the task is to maintain and document it.
Moderate Risk
Partially automatable. Proactive strategy now prevents reactive scrambling later.
High Risk
Significant automation pressure. The 12-month window is the action period.
Very High Risk
Core deliverables already AI-replicable. Urgent repositioning required.
Critical Risk
Near-term displacement without structural role change.

Why This Approach

Most AI risk frameworks are either too simplistic (a 5-question quiz) or too theoretical (white-paper models detached from real roles). SA-AIRS™ was designed to close that gap.

01

Structured, Not Opinionated

Every score is produced by a documented methodology — not a gut feeling or a trend article. The same role, assessed twice with the same inputs, produces the same score.

02

Weighted by Real Displacement Evidence

The dimensions we measure are chosen because they directly correlate with observed job displacement patterns across mid-market and enterprise roles. We do not measure proxies — we measure drivers.

03

Calibrated Against Real Cohorts

The scoring rubric has been calibrated across cohorts of working professionals across engineering, finance, marketing, and operations. The score bands map to observed outcomes — not theoretical risk models.

04

Explainable at Every Step

You receive a score, a tier, and a breakdown by dimension. Nothing is a black box. If you want to understand why you scored where you did, the reasoning is always provided.

05

Time-Horizoned

Displacement risk is not a binary event. The Full Report gives you both a 12-month and 36-month horizon — because the right action differs depending on how much runway you have.

Risk Score vs. Full Audit

More data means higher scoring confidence. The Risk Score is a directional read. The Full Report is a high-confidence audit with all five dimensions fully scored.

AI Risk Score
Directional Read
  • Directional score
  • 2-dimension quick read
  • Risk tier placement
  • 1 key insight
Full Report
High Confidence
  • All 5 dimensions scored
  • Composite SA-AIRS™ score
  • 12 & 36-month horizons
  • Top 3 Moves roadmap

Get Scored Against This System

Choose the assessment depth that fits you, then get your score, risk tier, and next steps.

Get Your Score →