Work · Playbook
AI Audit Your Job
Use this playbook to understand which parts of your job AI may change first.
Step 1
List your weekly tasks
Write down emails, reports, calls, scheduling, analysis, data entry, support, writing, coding, documentation, meetings, physical work, sales, management, and troubleshooting.
Step 2
Mark routine screen tasks
Circle drafting, summarizing, sorting, generating, responding, formatting, structured data analysis, and template work.
Step 3
Mark human moat tasks
Star anything involving trust, judgment, physical presence, emotion, licensing, safety, liability, negotiation, management, conflict, local knowledge, or emergency response.
Step 4
Look for the gap
If most of your job is circled and little is starred, you need an upgrade plan. If both are present, move toward the starred tasks.
Step 5
Choose one next move
Learn AI tools for your field, move toward escalation, build a portfolio, ask for operations responsibility, pursue a license, compare a career change, or delay expensive training until payback is clear.
Next step
Now turn this checklist into a decision.
What to document
- Top 10 weekly tasks
- Tasks already affected by AI, software, outsourcing, or workflow automation
- Human-moat tasks that still depend on judgment, trust, safety, or accountability
- One upgrade move you can start this month
Questions to ask before acting
- Which tasks would my employer automate first?
- Which tasks make me trusted, accountable, or hard to replace?
- What proof would show I can verify AI output instead of only produce drafts?
You are done when
- You know which parts of your work are most exposed.
- You have one concrete upgrade move instead of a vague AI worry.
- You know which Kefiw calculator or guide to use next.
Related Work tools
Human review note
This page is written to help with career decision-making, not to guarantee an outcome.
A strong career decision should include:
- The numbers
- The local job market
- The cost of training
- The human moat
- The daily work reality
- The upgrade path
- AI risk
- Robotics risk
Source and assumption card
This page uses public career and labor-market information, occupational task patterns, AI exposure research, robotics/automation signals, and Kefiw editorial assumptions.
Career data can vary by state, employer, union status, specialty, experience, and local demand.
Before making a decision, verify:
- Local wages
- Current job postings
- Licensing rules
- Training cost
- Credential requirements
- Employer demand
- First-year pay
- Completion and placement outcomes
Work trust and methodology
Kefiw Work pages are decision support, not guarantees. Use the methodology, sources, score explanation, glossary, and advertising disclosure to understand how the advice is built.