Let’s give credit where credit’s due—AI is doing some wild stuff. It can generate code, spit out essays, solve equations, and even build apps. The rise of generative AI has many asking the hot-button question: Will computer science be replaced by AI? If a bot can code better than your college roommate, what’s left for the rest of us?
Enter Professor Ikhlaq Sidhu, Dean of the School of Science and Technology at IE University, and someone who doesn’t just teach tech—he helps shape its future. Sidhu’s take? That question isn’t just misleading—it’s fundamentally flawed.
Let’s break it down.
AI wouldn’t exist without computer science. Literally.
Professor Sidhu puts it plainly:
“AI systems, including Gen AI, need continuous development, optimization and maintenance.”
In other words, someone’s gotta build the bots—and that someone is a computer scientist. AI doesn’t spring from the void; it’s constructed through the core concepts of computer science: algorithms, data structures, software engineering, and machine learning.
Think of AI as the shiny sports car. Computer science? That’s the engine, the fuel system, the mechanics, and the people who know how to fix it when it breaks down mid-race.
AI runs on CS like your apps run on caffeine
Even the most advanced AI models don’t exist in a vacuum—they run on hardware like GPUs and TPUs, and live in cloud ecosystems that were engineered and optimized by… you guessed it: computer scientists.
Sidhu reminds us: “AI doesn’t replace the foundational computing infrastructure—it runs on it.” Distributed systems, databases, cybersecurity, and cloud computing aren’t glamorous headline grabbers, but they are the bedrock of every AI marvel.
In short, someone needs to build and maintain the house AI lives in.
AI still needs us to think for it
Sure, AI can write lines of code faster than most interns—but can it understand why it’s writing them? Can it debug a nightmare production bug, reason through complex problems, or design a secure architecture that actually scales? Not really.
Professor Sidhu stresses: “AI lacks deep algorithmic reasoning, problem decomposition, and the ability to architect complex systems.” These aren’t bonus skills—they’re the whole job.
Imagine AI as a brilliant assistant with no common sense. It’s quick, helpful, and can get you halfway to a solution—but you still need the human brain to finish the job and make sure nothing breaks along the way.
So…will computer science be replaced by AI?
No. The next frontier isn’t replacing CS—it’s expanding it.
AI isn’t shrinking the field of computer science—it’s making it evolve. New challenges are popping up: AI bias, misinformation, fairness, adversarial attacks. These problems require people who understand both the tech and the ethics behind it. That’s CS 2.0.
Sidhu notes: “AI-generated content creates risks like misinformation and security threats—leading to new domains in trustworthy AI, adversarial ML and AI governance.” Translation? The world needs more computer scientists, not fewer.
Add in emerging fields like quantum computing, robotics, and cryptography—none of which AI can master alone—and you’ve got more CS problems to solve than ever.
Computer science isn’t just coding—it’s creativity, logic and vision
AI may be good at spitting out code, but that’s just one piece of the puzzle. Computer science is about systems thinking, building things that last, and solving problems no one else has cracked.
As Professor Sidhu puts it, “CS involves logic, problem-solving, system design, and theoretical foundations—things that AI can enhance but not replace.” And let’s be honest, the best part of being a computer scientist isn’t typing semicolons—it’s imagining and building what’s next.
Should you still study computer science and AI?
Absolutely. If anything, now is the time to double down. AI is changing the game, but computer science is still the playbook. The key is learning to work with AI—not fear it. That’s exactly what the Bachelor in Computer Science and Artificial Intelligence at IE University is all about.
You won’t just learn to code. You’ll learn to lead. To build. To innovate. You’ll become the kind of tech-savvy thinker the world needs—someone who doesn’t ask “Will computer science be replaced by AI?” but instead asks, “What can we build next?”
So pull up a chair. The future’s still under construction—and it needs builders like you.