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How We Calculate AI Job Risk

Our methodology combines peer-reviewed research, labor market data, and task-level analysis to assess automation probability for 200+ job categories.

Our Data Sources

Our risk assessments are built on research from leading institutions studying the impact of automation and AI on the workforce:

Oxford Martin School Study

Frey & Osborne's seminal 2013 research "The Future of Employment" analyzed 702 occupations and estimated that 47% of U.S. jobs are at high risk of computerization. We use their task-based framework for categorizing job vulnerabilities.

McKinsey Global Institute

McKinsey's ongoing research estimates that up to 800 million workers globally could be displaced by automation by 2030. Their analysis of 2,000+ work activities informs our understanding of which tasks are most susceptible to AI.

Bureau of Labor Statistics (O*NET)

We incorporate BLS occupational data including task descriptions, required skills, and employment projections to ensure our categories reflect real-world job requirements.

Risk Calculation Methodology

Base Risk Score

Each of our 200+ job categories has a base risk score (0-100%) derived from:

Task Routineness: How repetitive and predictable are the core job tasks?
Data Processing: Does the job primarily involve processing structured information?
Physical Dexterity: Does the role require complex physical manipulation in unstructured environments?
Creative Requirements: Does the job demand original thinking and novel solutions?
Social Intelligence: How much does the role depend on empathy, negotiation, and human connection?

Personalization Factors

Your quiz responses adjust the base score to reflect your specific situation:

Work Type: Data tasks increase risk; creative/physical work decreases it
Routine Level: Higher routine work = higher automation vulnerability
Experience: Longer tenure often correlates with more complex, harder-to-automate responsibilities

Risk Categories

Risk Level	Score Range	What It Means
High Risk	65-95%	Significant portions of job tasks can be automated with current or near-term AI technology
Moderate Risk	40-64%	Some tasks automatable, but core responsibilities require human skills
Lower Risk	5-39%	Job primarily involves tasks that are difficult for AI to replicate

Job Categories Analyzed

Our database includes 200+ occupations across 15 industry categories:

Administrative: Data entry, receptionists, clerks, assistants
Technology: Developers, engineers, analysts, IT support
Healthcare: Nurses, doctors, therapists, technicians
Creative: Designers, writers, artists, musicians
Finance: Accountants, analysts, bankers, advisors
Sales: Representatives, account managers, real estate
Service: Hospitality, food service, customer support
Trades: Electricians, plumbers, mechanics, construction
Business: Managers, consultants, HR, marketing
Education: Teachers, professors, counselors, tutors
Legal: Lawyers, paralegals, legal assistants
Logistics: Drivers, warehouse workers, shipping
Manufacturing: Assembly, machine operators, quality control
Media: Journalists, editors, content creators
Retail: Cashiers, sales associates, store managers

Limitations & Disclaimers

While our methodology is research-based, important caveats apply:

Predictions, not certainties: AI advancement is unpredictable. Our scores reflect current trajectory, not guaranteed outcomes.
Individual variation: Your specific role, company, and skills may differ significantly from category averages.
Continuous evolution: We update our database as new research emerges and AI capabilities change.
Not financial advice: This quiz is for informational purposes. Major career decisions should involve professional counseling.

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