Task-Based AI Exposure Analysis for Your Job
Learn to assess automation risk, identify AI-resistant skills, and build a 3-year career pivot plan using MIT economist methodologies
This guide teaches you how to conduct a task-based AI exposure analysis of your own job—the same methodology MIT economist Daron Acemoglu and his colleagues use to forecast which occupations are most at risk from AI automation.
What You'll Learn
By completing this guide, you will learn to break down your job into discrete tasks, assess AI automation potential for each task across three dimensions including technical feasibility and economic viability, calculate your personal automation risk score using weighted task analysis, identify AI-resistant skills that will remain valuable regardless of AI advancement, and create a career pivot plan with specific actions and timelines.
What You'll Build
By the end of this guide, you will have created a complete task inventory spreadsheet with detailed breakdown of your job responsibilities, an exposure assessment matrix with AI automation scores for each task, a personal risk dashboard providing visual representation of your automation exposure, a skill gap analysis comparing current versus required capabilities, and a comprehensive three-year career pivot plan with actionable roadmap and quarterly milestones.
Guide Chapters
Introduction
Why task-based analysis matters for career planning
Prerequisites
Required materials, tools, and time commitment
Theoretical Framework
Understanding AI exposure measurement methodology
Implementation Guide
Step-by-step framework for conducting your analysis
Advanced Techniques
Industry adjustments and specialized approaches
Troubleshooting
Common issues and solutions
Resources
Databases, tools, and research materials
Deliverables
Checklist of what you should have created
Conclusion
Key learnings and next steps
References
Related content and research citations