Healthcare degrees offer graduates the strongest career prospects against artificial intelligence (AI) automation, according to a new GoHumanize study that ranked 24 fields by employability.

The research analysed more than 100 occupations using projected job growth through 2034, unemployment rates, median wages, automation risk, and the level of public interaction each role demands. Healthcare took the top spot with 1.2 percent unemployment, the lowest of any field, and an automation exposure of just 24 percent.

The sector is projected to add 37,100 positions over the next decade across roles including registered nurses, nurse practitioners, and physical therapists. Average median pay sits at 117,700 dollars annually.

Computer science and information technology ranked second, with the fastest growth rate at 9.7 percent and 47,200 new positions expected through 2034. The trade off is a higher automation risk of 53 percent, though hiring continues to outpace most fields, and median pay reaches 109,900 dollars.

Personal care and cosmetology placed third on the back of 10 percent growth, with 30,600 openings projected, although median wages remain lower at 46,600 dollars. Business and management followed in fourth, with more than 60,000 new managerial positions expected and average pay of 123,100 dollars. Engineering closed out the top five at 8 percent growth and 41,300 new positions.

Retail majors face the bleakest outlook. The sector is projected to lose 162,000 jobs by 2034 while automation threatens roughly 80 percent of tasks. Office administration also ranks among the most exposed graduate categories.

“You can’t automate an electrician wiring a building,” said the founder of GoHumanize.

The study found that workers aged 22 to 25 have already recorded a 16 percent employment drop in AI-exposed roles within three years, with recent graduates hit hardest. The ranking weighted degrees by how well they protect graduates from unemployment and automation while still offering real opportunities. The findings point to a widening divide between fields that demand in-person human interaction and those tied to repetitive cognitive tasks now being absorbed by machine learning systems.