Prior research has established associations between individuals’ languageusage and their personal traits; our linguistic patterns reveal informationabout our personalities, emotional states, and beliefs. However, with the increasing adoption of Large Language Models (LLMs) as writing assistantsin everyday writing, a critical question emerges: are authors’ linguisticpatterns still predictive of their personal traits when LLMs are involved inthe writing process? We investigate the impact of LLMs on the linguisticmarkers of demographic and psychological traits, specifically examiningthree LLMs — GPT3.5, Llama 2, and Gemini — across six different traits:gender, age, political affiliation, personality, empathy, and morality. Ourfindings indicate that although the use of LLMs slightly reduces the predictive power of linguistic patterns over authors’ personal traits, the significantchanges are infrequent, and the use of LLMs does not fully diminish thepredictive power of authors’ linguistic patterns over their personal traits.We also note that some theoretically established lexical-based linguisticmarkers lose their reliability as predictors when LLMs are used in the writing process. Our findings have important implications for the study oflinguistic markers of personal traits in the age of LLMs.