Image: With the growing attention on artificial intelligence and its impact on society, many of you may be wondering what this moment means for studying computer science and how to prepare for successful careers. We believe this is an exceptionally exciting time to be in computing. As with every major technological shift, change is inevitable. However, rather than reducing opportunities, AI is likely to expand them for computing professionals. Throughout the history of computing, advances in software development tools have consistently improved productivity. Yet increased productivity has not reduced demand for developers; instead, it has led to the creation of more software and, consequently, greater demand for skilled professionals. We expect AI-based software development to follow a similar trajectory. For example, IBM CEO Arvind Krishna has suggested that AI may improve software development productivity by 20–30%, depending on the nature of the work, while ultimately increasing overall demand for software and developers. We are already observing encouraging signs locally: at the School of Computing at UGA, more companies are recruiting our students compared to recent years. National trends reflect a similar pattern — even in a challenging job market, software-related roles remain resilient, while machine learning and AI positions are among the fastest-growing across sectors. Despite the emergence of new layers of abstraction in software development, strong foundations in computer science are becoming even more important. AI-assisted development requires professionals who can guide AI systems, evaluate their outputs, and recognize when solutions do not scale, lack security, or contain subtle errors. This demands a deep understanding of software, systems, and computational foundations, along with strong problem-solving and critical-thinking skills. While AI tools may increasingly generate boilerplate code, large-scale, production-quality software still depends on careful design, rigorous review, extensive testing, and experienced teams ensuring reliability, availability, and security. Importantly, the disruptive technology transforming industries today is itself a computing technology. Just as the internet and the World Wide Web made every company a software company, many expect that organizations across sectors will increasingly become AI-driven enterprises deploying intelligent systems and AI agents. These agents are, fundamentally, software systems that rely on well-engineered data and infrastructure. AI adoption, therefore, creates ongoing needs for building, maintaining, evolving, and securing software and data platforms. What, then, is our message to current and prospective computer science students? In a period of significant transformation in work and employment, being close to the technologies driving that transformation is a clear advantage. Alongside strong foundational training in computer science, we encourage students to develop expertise in at least one of the following areas: A. AI technologies: understanding how models are trained and applied, as well as their limitations. B. Cybersecurity: knowledge of attack surfaces, defense mechanisms, and secure system design — increasingly critical as digitization and AI expand. C. Problem discovery and innovation: the ability to identify what should be built, not just how to build it. Experiences such as research, hackathons, and student organizations are valuable here. D. Product and business understanding: exposure to product management or business fundamentals to connect technological solutions with real-world needs. E. Communication and collaboration skills: the ability to work effectively in client-facing and interdisciplinary roles, which will become even more important as technology grows more powerful.
