What is the AI Kill Threshold?

The AI Kill Threshold is a probability (0-100%) indicating how likely your occupation will be replaced by AI. It is calculated using the Swiss Cheese Barrier Model across four independent dimensions: Learnability, Evaluation Objectivity, Risk Tolerance, and Human Presence.

How is the replacement probability calculated?

Using a Weighted Power Mean with r=-2 across four dimensions. Learnability has weight 0.30, Evaluation Objectivity 0.25, Risk Tolerance 0.20, Human Presence 0.25. An additional E+O interaction bonus applies when both knowledge is explicit and evaluation is objective.

What data sources does AIR use?

AIR aggregates from BLS OES 2023 (798 occupations employment data), O*NET (task structure labels), Eloundou et al. 2023 (LLM exposure measurement across 19,265 tasks), OpenAI GDPval (AI vs human expert blind evaluation), and the World Economic Forum Future of Jobs Report 2025.

How does AIR differ from MBTI?

MBTI measures personality. AIR measures occupational AI-replacement risk. Both use four binary dimensions producing a 4-letter code, but AIR's dimensions are grounded in automation economics literature and the output is backed by employment data from 798 real occupations.

What is the current industry-wide AI replacement rate?

As of 2026, the employment-weighted industry-wide AI replacement rate is 24.7%, calculated as Task Exposure (34.8%, Eloundou et al. 2023) times AI Win Rate vs human experts (71.3%, OpenAI GDPval).

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EOFH

The Human Bridge

“AI does the work, but they come back for YOU”

High Risk

Ersetzungswahrscheinlichkeit

62%–78%

Prognostizierter Jahresbereich

2029–2034

Risikostufe

High Risk

Explicit + Objective + Flexible + Human: AI can do everything, but clients trust YOU specifically

Superkraft

Trust and relationships that no algorithm can replicate

Schwäche

Once AI builds rapport through persistent personalization, your moat shrinks

Vier Barriere-Dimensionen

Lernbarkeit — Explizit (E)

Kann KI das Wissen und die Fähigkeiten erwerben und erlernen, die Ihr Job erfordert?

Bewertungsobjektivität — Objektiv (O)

Gibt es bei Ihrer Arbeit eine „richtige Antwort"? Lässt sich die Qualität objektiv messen?

Fehlertoleranz — Flexibel (F)

Wenn die KI einen Fehler macht, sind die Folgen tragbar? Kann man ihrem Output vertrauen?

Personenabhängigkeit — Mensch (H)

Liegt Ihr Wert in „was Sie produzieren" oder in „wer Sie sind"?

Warum exponiert

Knowledge is transparent, quality is measurable, and errors are forgivable — AI can learn, optimize, and iterate freely in 3 out of 4 dimensions.

Natürliche Verteidigung

People come to you for YOU, not just results. Human trust, personal reputation, and relationship continuity are your moat — but only if you actively cultivate them.

Typische Berufe

Sales & Related (41), Business & Financial Operations (13) — client relationship roles

Beispielberufe-Risiko

Sales Representatives of Services
Product knowledge is commoditized — AI recommendation engines erode information advantage
37
First-Line Supervisors of Retail Sales Workers
Operational tasks increasingly automated — human value shifts to team motivation
26
Counter and Rental Clerks
Transaction-oriented role — self-service kiosks and apps replace routine counter work
18
Retail Salespersons
E-commerce and AI recommendations eroding in-store advantage — relationship is the last moat
14
Insurance Sales Agents
AI can compare and recommend plans — agents survive on trust and complex case handling
14
Cashiers
Self-checkout terminals and mobile payment already displaced millions of cashier roles
5

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