2025 ASEE Annual Conference & Exposition

The rapid advancements in Artificial Intelligence (AI) have revolutionized a wide range of industries, including healthcare, finance, transportation, and manufacturing. These innovations are not only enhancing efficiency and innovation in these sectors but are also reshaping the way we think about the future of work, problem-solving, and decision-making. AI’s transformative impact presents an exceptional opportunity to revolutionize education, particularly in Computer Science (CS) and Information Systems (IS) programs, where students are trained to lead in technology-driven fields. As AI continues to influence various aspects of society—from automation to data analytics—the urgency to equip students with relevant, cutting-edge knowledge and skills has never been more critical. In response to this growing demand, many universities are proactively developing new courses and degree programs that focus on AI and its applications across disciplines. These programs are designed to prepare students to navigate the rapidly evolving technology landscape, making them capable of contributing to and shaping AI-driven innovations. Alongside academia, global technology companies and online learning platforms have also recognized the need for AI expertise, offering training and certification programs that provide students, professionals, and learners at various levels with access to essential AI tools and methodologies.

At the undergraduate level, integrating AI into the curriculum offers students the opportunity to gain a foundational understanding of AI concepts, principles, and applications. Courses can introduce them to essential AI technologies, such as natural language processing, computer vision, robotics, and intelligent systems. By engaging in hands-on learning with real-world AI applications, students can better understand the practical implications of AI in various industries, while also building skills that align with the current demands of the job market. This exposure will not only enhance their technical proficiency but also cultivate problem-solving and critical thinking abilities that will be instrumental as they enter the workforce. Whereas at the graduate level, AI education takes on a more advanced and research-oriented approach. Graduate programs offer students the chance to delve deeper into cutting-edge AI research areas such as machine learning algorithms, deep learning, neural networks, and data-driven predictive modeling. By tackling complex, AI-driven projects, students are encouraged to develop not only their technical expertise but also their ability to think critically and creatively about how AI can be applied to solve real-world challenges. These projects often involve interdisciplinary collaboration, where students can apply AI solutions to fields like medicine, finance, environmental science, and beyond. Furthermore, graduate programs provide opportunities for students to engage in innovation and entrepreneurship, as they explore how AI can be used to create new business models or disrupt existing industries.

Ultimately, the integration of AI into CS and IS programs will significantly enhance student engagement, learning outcomes, and career preparedness. By equipping students with both the technical knowledge and ethical awareness needed to navigate AI's complexities, educational institutions can ensure that the next generation of professionals is prepared to leverage AI responsibly and effectively in the global job market. In this paper, we will identify key AI topics that should be incorporated into Computer Science (CS) and Information Systems (IS) curricula, including deep learning, reinforcement learning, and natural language processing. Additionally, we will propose the most suitable courses within both undergraduate and graduate programs where these topics can be seamlessly integrated to optimize student learning and ensure the achievement of critical educational outcomes.