AI-Written Job Ads Work as Well as Human Ones, Study Finds

Purpose This study explores the use of generative artificial intelligence (AI) in the pre-hiring stage of recruitment, focusing on the design of job advertisements. As AI tools become more prevalent in human resources management, understanding their perceived effectiveness and neutrality is essential to support informed integration into recruitment practices. Grounded in signalling theory, we conceptualize job advertisements as signals that shape perceptions of job appeal, job fit, job-pursuit intentions and ad informativeness. Design/methodology/approach Three experimental studies were conducted. Studies 1 and 2 surveyed business students in Sweden and the UK, who were randomly exposed to a real, expert-written, or AI-generated job advertisement. Their perceptions of job appeal, fit and informativeness were analyzed. Study 2 examined how respondents' characteristics influenced their perceptions. Study 3 assessed how HR professionals evaluated and identified the advertisement creator. Findings Results show that AI-generated job advertisements are perceived as equally effective and informative as human-written advertisements by both students and HR professionals. Human-written advertisements were more appealing to applicants with specific personality traits, while AI advertisements showed no such pattern, suggesting neutrality. HR professionals were sceptical but often failed to identify AI-generated content. Research limitations/implications The study relies on relatively modest sample sizes and self-reported measures. Practical implications Generative AI can support fairer, more effective recruitment communication, though human oversight and targeted design remain important. Originality/value This research investigates the application of AI in job advertisements, a key stage in the recruitment process and provides empirical evidence in the form of tangible findings. We contribute to signalling theory by showing the ability of AI-generated job advertisements to accurately portray the content and tone of an organization and how receiver characteristic differences influence the interpretation of job advertisements generated by different methods. It offers novel insights into how AI-generated advertisements are perceived by applicants and HR professionals, and their potential for bias reduction. The multi-study design enables comparison across applicant and professional perspectives.