What is an AI Moat Score?

An AI Moat Score measures how resistant a career is to AI displacement. It evaluates jobs across 21 factors and 5 pillars to determine their vulnerability to automation.

How is the score calculated?

The score is calculated by analyzing 21 factors across 5 pillars: Human Cognitive Moat, Social & Institutional Moat, Physical Reality Moat, Economic & Demand Moat, and AI Exposure Risk. Each factor is scored 1-5 and weighted based on importance.

What do the grade levels mean?

FORTRESS (80-100): Highly resistant to AI. RESILIENT (60-79): Moderately resistant. EXPOSED (40-59): Somewhat vulnerable. VULNERABLE (20-39): Highly vulnerable. ENDANGERED (0-19): Extremely vulnerable to AI displacement.

How accurate are the scores?

Scores are generated using AI analysis of career characteristics and are regularly validated against real-world automation trends. However, they should be used as guidance rather than absolute predictions.

Can I request a new career to be scored?

Yes! Simply enter any job title on the homepage to get it scored. The system will analyze it and provide a detailed breakdown.

Package Sorter

Loaded from database

0.0

ENDANGERED(0–19)

Logistics & Transport

Low Income

Summary

Package sorters are responsible for manually or semi-automatically directing packages to their correct destinations within a distribution center or sorting facility. This role involves physical labor, attention to detail, and a degree of spatial reasoning to identify labels, destinations, and sort codes. The work is repetitive and often physically demanding, with sorters standing for long periods and lifting/moving packages.

Future Outlook

The role of a package sorter is undergoing rapid transformation due to advancements in automation and robotics. While some manual sorting will persist, the integration of automated guided vehicles (AGVs), robotic arms, and advanced scanning and conveyor systems are steadily reducing the need for human intervention in many sorting processes. This trend is likely to accelerate, with a significant portion of existing package sorting tasks being automated within the next decade. Future iterations of this role may involve overseeing and maintaining automated sorting systems rather than direct manual sorting.

Package Sorter

Pillar Scores

Human Cognitive Moat

8.3 / 35

Social & Institutional Moat

6.8 / 28

Physical Reality Moat

12.4 / 21

Economic & Demand Moat

4.2 / 21

AI Exposure Risk

-26.0 / 35

Score Comparison

Sector Comparison: Logistics & Transport

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This Career

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Global Comparison

No data available

0255075100

This Career

0.0

What This Means

This comparison shows how this career's AI Moat Score compares to others in its sector and across all careers. A higher score indicates greater resistance to AI displacement. Scores range from 0-100, with higher scores being better.

Human Cognitive Moat

Moat Strength

8.3

/ 35

Moat Strength24%

Weak moat — limited protection from this pillar; other moats must compensate.

Social & Institutional Moat

Moat Strength

6.8

/ 28

Moat Strength24%

Weak moat — limited protection from this pillar; other moats must compensate.

Physical Reality Moat

Moat Strength

12.4

/ 21

Moat Strength59%

Moderate moat — some protection exists but AI advances could erode this over time.

Economic & Demand Moat

Moat Strength

4.2

/ 21

Moat Strength20%

Weak moat — limited protection from this pillar; other moats must compensate.

AI Exposure Risk

Penalty

-26.0

/ 35

AI Exposure Level74%

High AI exposure — significant portions of this role are already being targeted by AI.

Conditional Modifiers Applied

High AI Penetration & Task Routineness

-6

AI Penetration (-5) ≤-4 AND Task Routineness (-5) ≤-4

Penalty applied to total score

These modifiers are applied based on specific factor combinations that significantly impact AI resistance.

Key Strengths

Low skill requirement allows for quick onboarding and high availability of labor
Physical nature of the job provides a temporary barrier to full automation in dynamic environments
While repetitive, the need for human judgment in non-standard package handling or errors offers some resilience

Key Vulnerabilities

High degree of repetitive tasks amenable to automation
Increasing sophistication of robotic arms and AI for object recognition and manipulation
Potential for full automation of sorting lines with advanced conveyor and scanning systems

Adjacent Careers

Click any adjacent career to analyze it. If it already exists, you'll be taken to its detail page.

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How This Score Was Calculated

Pillar Score Formula

Pillar Score = (∑(Factor × Weight)) × (Normalization Factor)

Where factors are scored 1-5 (1=weakest, 5=strongest) for positive pillars, and -1 to -5 (-1=low exposure, -5=high exposure) for AI Exposure Risk.

Pillar Weights & Maximums

Pillar	Factors & Weights	Raw Max	Normalized Max
Human Cognitive	Judgment(3.0), Creative(2.5), Relational(2.5), HumanPref(2.5), Contextual(2.5)	65	35
Social & Institutional	Regulatory(3.0), Guild(2.5), Institutional(2.5), Proprietary(2.0), Trust(2.0)	60	28
Physical Reality	Dexterity(3.0), GeoTethering(3.0), Environment(2.5), Exertion(2.0), Sensory(2.0)	62.5	21
Economic & Demand	Demand(3.0), Training(2.5), EntryCost(2.5), Polymathy(2.5), Knowledge(2.5)	65	21
AI Exposure Risk	AIPenetration(4.0), TaskRoutine(4.0), Data(3.5), Output(3.5), Remote(3.0), Substitution(3.0)	105	-35

Actual Calculations for "Package Sorter"

Human Cognitive Moat

Raw: 15.5 / 65 × (8.3/35)

(1×3.0 + 1×2.5 + 1×2.5 + 1×2.5 + 2×2.5) × (35/65) = 8.3

Social Institutional Moat

Raw: 14.5 / 60 × (6.8/28)

(1×3.0 + 1×2.5 + 2×2.5 + 1×2.0 + 1×2.0) × (28/60) = 6.8

Physical Reality Moat

Raw: 37.0 / 62.5 × (12.4/21)

(3×3.0 + 3×3.0 + 2×2.5 + 4×2.0 + 3×2.0) × (21/62.5) = 12.4

Economic Demand Moat

Raw: 13.0 / 65 × (4.2/21)

(1×3.0 + 1×2.5 + 1×2.5 + 1×2.5 + 1×2.5) × (21/65) = 4.2

Ai Exposure Risk

Raw: 78.0 / 105 × (-26.0/35)

(5×4.0 + 5×4.0 + 2×3.5 + 2×3.5 + 4×3.0 + 4×3.0) × (35/105) = -26.0

Total Score Calculation

Base Score = 5.7

Conditional Modifiers Applied:

AI Penetration (-5) ≤-4 AND Task Routineness (-5) ≤-4 → -6 points

Final Score = 5.7 + modifiers = 0.0

Note: Pillar scores are normalized to ensure the total score fits within the 0-100 range. The maximum possible score with all positive factors at 5 and all negative factors at -1 (minimal AI exposure) is approximately 100, placing it in the FORTRESS grade band.