Research highlights how AI-generated narratives often reflect gender stereotypes, associating feminine characters with family and emotions, and masculine characters with politics and war. The key Goals are to investigate how AI models’ gender bias influences perceptions and decisions of frequent users and also to explore ways to adapt findings from prior studies to improve AI interactions and reduce the impact of bias in outputs. Students input five prompts into the AI, with outputs varying between generic masculine (experimental group) and gender-neutral/feminine-masculine forms (control group). They respond to questions about their desired childhood career (categorized by gendered or neutral terms) and rate the difficulty of gendered and neutral professions on a scale of 1–5. Responses are evaluated by gender and group (experimental vs. control). Cluster analysis via SPSS will create user persona (personalized fictional character). The experiment has received approval from the ethics committee, because participants remain unaware of the study’s purpose to avoid biased results.