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PlotFuture / Careers / Family and Consumer Sciences Teachers, Postsecondary

Family and Consumer Sciences Teachers, Postsecondary

Also known as: Assistant Professor, Associate Professor, Child Development Instructor, Dietetics Professor, Family and Consumer Sciences Professor (FCS Professor)
median $75,87010-yr demand +3.4%AI exposure 0/100typical entry Doctoral or professional degree
Family and Consumer Sciences Teachers, Postsecondary is mid-paying, AI barely touches it so far, and demand is steady.

The full pay distribution

Not one number — the spread from the bottom 10% to the top 10% of filed salaries.

How pay grows with experience

From entry to expert, by reported wage level.

How exposed is it to AI?

Two things matter: how much AI is actually used in the role today (right), and how much it could automate in theory (up). High potential, little real use yet.
Each faint dot is another occupation. The amber dot is Family and Consumer Sciences Teachers, Postsecondary — its position tells you whether the disruption is here yet or still over the horizon.
used today 0/100 automatable in theory 54/100 archetype The Sleeping Giant

If AI does come for this job — where could you go?

Adjacent careers ranked by how much safer + how much more they pay, and the skill gap to get there. Click any to see its full breakdown.

Which majors lead here

College paths that commonly feed this career — see each one's full outcomes.
Teacher Education And Professional Development, Specific Subject Areas
CIP 13.13
see major →
Family And Consumer Sciences/Human Sciences, General
CIP 19.01
see major →
Family And Consumer Sciences/Human Sciences Business Services
CIP 19.02
see major →
Family And Consumer Economics And Related Studies
CIP 19.04
see major →
Foods, Nutrition, And Related Services
CIP 19.05
see major →
Housing And Human Environments
CIP 19.06
see major →
Human Development, Family Studies, And Related Services
CIP 19.07
see major →
Apparel And Textiles
CIP 19.09
see major →
Work And Family Studies
CIP 19.10
see major →
Nutrition Sciences
CIP 30.19
see major →
How this is built. Median pay and the full distribution come from filed U.S. wage data (BLS OEWS + DOL/LCA filings); AI exposure blends O*NET task content with model-based automation potential; escape routes are computed from skill overlap between occupations, then ranked by how much safer + better-paid the move is. This joins real distributions and projects them forward — it needs the real distributions and the skill graph, not a guess. Figures describe group medians and trends, not any one person's outcome.