Which jobs are most exposed to AI? ChatGPT, Gemini and Claude answers may surprise you

In recent times, artificial intelligence (AI) tools and chatbots have evolved beyond simple personal assistants, sparking concerns among workers about the potential for job displacement. To explore the implications of AI on various professions, economists and researchers examined advanced AI models to identify which jobs might be most at risk. However, their findings have revealed inconsistencies. A working paper highlighted by The Wall Street Journal, authored by economists Michelle Yin and Hoa Vu from Northwestern University alongside Claudia Persico from American University, evaluated three prominent AI systems: OpenAI’s ChatGPT-5, Google DeepMind’s Gemini 2.5, and Anthropic’s Claude 4.5. The researchers aimed to determine how these models ranked occupations based on their vulnerability to AI automation. The results were telling; the different AI models expressed varying opinions on which jobs are most susceptible to AI disruption. Notably, there was significant disagreement regarding supervisory roles and positions that blend mental and physical tasks. For example, while Claude indicated that accountants might face substantial risks from AI, Gemini countered this claim, suggesting that the profession is less vulnerable. Disparities also emerged concerning the roles of advertising managers and CEOs, with the AI models providing contrasting assessments. Although ChatGPT and Gemini aligned in their findings most of the time, they still exhibited around a 25% disagreement rate. Researchers speculated that these differences could stem from the diverse datasets each AI system is trained on. The study pointed out that certain professions, such as financial analysts, heavily utilize AI, which could lead future systems to categorize these roles as more intertwined with AI technology and thus more exposed to automation. As AI continues to evolve, the implications for job security may also shift. Economists caution against placing blind trust in AI-generated assessments of job risk. Michelle Yin emphasized the importance of not relying on a single metric to make career decisions, stating, "I personally would not rely on just one measure to say, ‘Oh, I should change my job,’ or ‘I should change my kid’s major.'"