Generative AI tools such as ChatGPT, GitHub Copilot, and Gemini have rapidly transformed programming education by providing instant code generation and problem-solving support. This study analyzes the possible impact of these tools on an introductory Python programming course through an observational analysis through two different cohorts in 2022 and 2024. In total, we analyzed a corpus of 1,614 submissions from three assignments. To study the possible influence of AI gen AI tools, we created baseline solutions for each assignment using ChatGPT and Gemini. Then, we study code similarity between the baseline and the students’ submissions and and syntax errors across both cohorts. The results show that in Assignment 2, there was a decrease of 60.11% in peer-to-peer duplication between 2022 and 2024. For 2024 submissions, we observe substantial similarity to fixed AI baselines. Although this pattern is consistent with the convergence toward AI-generated solutions, we lack direct measures of tool use and make no causal claims. The number of syntax errors did not show statistically significant differences over the years. These findings suggest a shift in programming education, from direct student copying toward solutions that increasingly resemble AI-generated outputs, emphasizing the need for updated assessments and policies to promote fairness, integrity, and meaningful learning in introductory programming courses.