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Analysis of Results

Patterns and insights across occupations, themes, and AI resilience

Occupations Analyzed
10

Seeded dataset

Avg Future Resilience
67%

Across all roles

Highest AI Exposure
91%

Accountant

Most Resilient Role
94%

Therapist

AI Exposure vs Future Resilience
Compare automation risk against future resilience across all 10 occupations
Resilience by Theme
Average resilience score per occupation theme
Resilience Distribution
How occupations break down across resilience tiers
Human Strength vs AI Exposure
Each bubble is an occupation — larger bubble means higher future resilience

Occupation Breakdown

Filter and explore all occupations

OccupationHuman StrengthAI ExposureFuture ResilienceRating
Nurse
92%
34%
88%
High
Truck Driver
45%
87%
28%
Low
Judge
89%
41%
82%
High
Artist
95%
52%
79%
Medium
Accountant
48%
91%
32%
Low
Teacher
88%
38%
85%
High
Software Engineer
72%
78%
65%
Medium
Therapist
97%
22%
94%
High
Warehouse Worker
41%
83%
31%
Low
Doctor
91%
45%
84%
High

Key Insights

Human-Centric Roles Lead

Occupations requiring empathy, emotional intelligence, and human judgment score highest in future resilience — averaging 89% across care-focused roles.

AI Exposure vs Resilience: Inverse Relationship

Roles with over 80% AI exposure show an average resilience of just 30%. The higher the automation risk, the lower the future outlook.

Creative Work Holds Strong

Despite moderate AI exposure (52%), creative occupations maintain high resilience (79%) due to irreplaceable human originality and expression.

Technical Roles at a Crossroads

Software engineers face high AI exposure (78%) yet moderate resilience (65%), suggesting augmentation rather than full replacement as the likely future.

About This Analysis

This analysis is based on the initial seeded dataset of 10 occupations across multiple themes. Scores reflect AI-generated assessments of human-centric strength, AI exposure risk, and future resilience for each occupation.

As more occupations are added and more users complete assessments, this analysis will become richer and more statistically meaningful.

Analysis and visualization contributed by Shawaiz as part of the AIxponential initiative.