Artificial Intelligence, particularly Generative AI tools like GitHub Copilot and OpenAI's GPT, has transformed education by supporting tasks such as programming, problem-solving, and content creation. These tools hold significant potential in technology disciplines like computer engineering and can help address issues already present in the classroom. Among these challenges are varying levels of knowledge in programming courses, where some students are beginners while others have prior experience, as well as the steep learning curve faced by first-year students in programming, often exacerbated by large class sizes that limit individualized support. Generative AI tools offer opportunities to overcome these challenges. This research examines the integration of Generative AI tools into computer engineering curricula, with the goal of improving learning outcomes, enhancing critical thinking, and ensuring the responsible adoption of these transformative technologies. Specifically, we outline various actions to be implemented in different computer engineering courses for the integration of Generative AI tools. Among these actions, we suggest that Generative AI tools can act as virtual assistants (in a peer-programming methodology), offering real-time, tailored feedback and personalized guidance, thereby fostering student independence and enhancing learning efficiency. Additionally, these tools can help students by automating repetitive tasks, enabling them to focus on more creative and conceptual aspects of their work. We also consider potential risks associated with the use of Generative AI, such as over-reliance on AI-generated solutions, plagiarism, and ethical concerns related to intellectual property. To mitigate these risks, we propose the use of ethical guidelines and Generative IA use indicators to promote responsible and ethical practices in the use of Generative AI tools.

Keywords: Generative AI, peer-programming, ethical guidelines, indicators.