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.

Operations Analyst

Loaded from database

15.6

ENDANGERED(0–19)

Finance & Accounting

Mid Income

Summary

Operations Analysts are responsible for improving the efficiency and effectiveness of business processes and systems. They analyze data, identify bottlenecks, and recommend solutions to streamline operations, reduce costs, and enhance productivity. This often involves working with cross-functional teams to implement changes and monitor their impact.

Future Outlook

The role of an Operations Analyst is set to evolve significantly with the increasing integration of AI and automation. While routine data analysis and process mapping may be automated, the critical thinking, problem-solving, and strategic decision-making aspects of the role will become even more vital. Analysts will likely shift towards higher-level strategic work, focusing on designing and managing AI-driven operational systems, interpreting complex AI outputs, and ensuring ethical and efficient deployment of automation. There will be an increased demand for analysts who can bridge the gap between technical AI capabilities and business objectives. Skills in data science, AI ethics, change management, and human-AI collaboration will be highly valued. The profession will likely see a bifurcation, with some tasks becoming heavily automated, while the core analytical and strategic components become more sophisticated and indispensable, requiring continuous learning and adaptation.

Operations Analyst

Pillar Scores

Human Cognitive Moat

21.0 / 35

Social & Institutional Moat

10.7 / 28

Physical Reality Moat

8.4 / 21

Economic & Demand Moat

4.2 / 21

AI Exposure Risk

-22.7 / 35

Score Comparison

Sector Comparison: Finance & Accounting

No data available

0255075100

This Career

15.6

Global Comparison

No data available

0255075100

This Career

15.6

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

21.0

/ 35

Moat Strength60%

Solid moat — meaningful barriers to AI substitution are present here.

Social & Institutional Moat

Moat Strength

10.7

/ 28

Moat Strength38%

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

Physical Reality Moat

Moat Strength

8.4

/ 21

Moat Strength40%

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

-22.7

/ 35

AI Exposure Level65%

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 (-4) ≤-4 AND Task Routineness (-4) ≤-4

Penalty applied to total score

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

Key Strengths

Complex problem-solving and strategic thinking
Cross-functional collaboration and communication
Adaptability to new technologies

Key Vulnerabilities

Automation of routine data analysis
AI-powered predictive modeling
Standardization of operational processes

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 "Operations Analyst"

Human Cognitive Moat

Raw: 39.0 / 65 × (21.0/35)

(3×3.0 + 2×2.5 + 4×2.5 + 2×2.5 + 4×2.5) × (35/65) = 21.0

Social Institutional Moat

Raw: 23.0 / 60 × (10.7/28)

(1×3.0 + 2×2.5 + 2×2.5 + 3×2.0 + 2×2.0) × (28/60) = 10.7

Physical Reality Moat

Raw: 25.0 / 62.5 × (8.4/21)

(1×3.0 + 2×3.0 + 4×2.5 + 1×2.0 + 2×2.0) × (21/62.5) = 8.4

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: 68.0 / 105 × (-22.7/35)

(4×4.0 + 4×4.0 + 3×3.5 + 3×3.5 + 2×3.0 + 3×3.0) × (35/105) = -22.7

Total Score Calculation

Base Score = 21.6

Conditional Modifiers Applied:

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

Final Score = 21.6 + modifiers = 15.6

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.