Back at the end of October, Google CEO Sundar Pichai made a big announcement. It wasn’t a new device, app, or software; instead, Pichai revealed that more than a quarter of Google’s new code for its products was AI-generated (with human oversight).
Coming from one of Silicon Valley’s preeminent employers, this was a ground-shaking announcement – in particular, among computer science educators focused on career-readiness. After all, if AI can code, why should students learn CS in the first place?
Though it goes without saying, CS is so much more than syntax or writing loops. CS helps students build problem-solving muscles, contextualize how technology shapes their world, and develop the practical skills needed to thrive in an evolving workforce. Beyond technical knowledge, CS also hones creativity, collaboration, and ethical thinking – all key ingredients for young minds eager to make a meaningful impact.
Don’t count out CS just because computing is making a major leap forward. Here are six reasons to keep CS in the educational conversation as AI steps into the spotlight:
AI can write code, but it can’t replace a well-rounded understanding of how computing works at a fundamental level.
Learning algorithms, data analysis, and systems management helps students develop computational thinking – a problem-solving mindset that allows students to flexibly adapt to new challenges.
Computational thinking isn’t just crucial to developing new generations of computers; it also helps programmers interpret issues and debug code when it doesn’t perform as expected. That level of awareness is essential because no matter what, AI-written code (like human-written code) will never be 100% perfect every time.
Without these detail-oriented skills, students become passive users instead of empowered creators. Learning CS and coding helps keep them in the driver’s seat, no matter what role AI takes in their future career.
AI shouldn’t do all the work – and students shouldn’t learn to let it. By engaging with CS topics, students learn to divide their cognitive workload efficiently, with AI handling so-called “grunt work” while they apply themselves to higher-order problem formulation and solution selection.
With this kind of cognitive division, students are better prepared to solve meaningful real-world problems. Higher-order thinking is coveted by employers and communities alike, meaning students who engage with CS topics will be better positioned to become innovators — both in the workplace and in their community.
As Google has already demonstrated, AI isn’t replacing programmers—it’s becoming a powerful collaborator. Future professionals will need to prompt AI effectively, refine its outputs, and audit code for fairness, security, and quality.
For students here and now, there’s an important lesson to learn: success is not about being the best coder—it’s about knowing how to apply technology creatively, effectively and wisely. Coding, robotics, app design, and more can foster that mindset, leading to more fruitful AI-human collaborations down the line.
Technologies are only as fair and equitable as the people developing them, so it is crucial to help students learn the value of both through CS education. CS classrooms are unbeatable spaces to hear from diverse voices – another key ingredient in creating not just effective code, but also unbiased AI tools.
AI can also serve as a gateway, lowering barriers to programming for students with disabilities or those from underrepresented communities. By making coding more accessible, AI empowers students to see themselves as contributors to the tech landscape, fostering a sense of belonging and inclusion in CS classrooms. This not only broadens participation but also ensures that the technology they build reflects a wider range of perspectives.
While routine coding may become automated in time, hybrid careers that mix technical knowledge with problem-solving will thrive. These types of jobs are especially prevalent in the programming and information technology sector, which is expected to add 350,000+ well-paying jobs each year going forward.
Many of these roles will require experience with data science, machine learning, user experience, and mobile engineering – all of which students can get a taste for through CS activities and projects.
CS education also equips students for top roles in AI management, cybersecurity, and software architecture. And even outside the tech sector, fields like journalism, healthcare, and marketing will need professionals who can leverage AI tools and data effectively. So no matter their career path, students can get a leg up on the AI-powered economy, starting in their CS classroom.
CS education goes beyond the classroom to build life skills. Persistence, creativity, and resourcefulness are dispositions that CS students develop and carry into any field they pursue.
Through real-world projects, students also learn how to fail productively and bounce back stronger—a crucial skill for navigating challenges in both their personal and professional lives. Whether or not they become software engineers, students with CS experience will have the mindset to solve complex problems, collaborate effectively, and adapt to change.
Students who learn CS won’t just use technology—they’ll shape it. CS education isn’t about churning out coders; it’s about developing thoughtful creators, ethical decision-makers, and active participants in a wide variety of career fields.
In other words, computer science remains a crucial keystone in a student’s well-rounded education – even as AI’s coding capabilities continue to improve. K-12 schools should continue creating CS learning opportunities and ensuring those opportunities prepare students for what’s ahead in an AI-powered world.
To learn more about how you can bring engaging CS learning to your school, visit our CS & STEM hub or contact Program Manager, Sarah Phelps.
Tim directs the Learning Technology Center, providing strategic leadership, expertise, and operational management for statewide technology and digital learning initiatives.
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