In the age of AI, many are concerned about the impacts it could have on career prospects. AI has already automated some tasks, and media reports have specifically discussed the impacts of AI on entry-level jobs in coding.
However, students and alumni at the University of Waterloo are much more optimistic about the future, and the general sentiment is that AI presents opportunities, not threats.
“I see AI as another frontier of technological innovation, much like Web3 or Extended Reality (XR),” said William Wang (BCS ‘25), a recent Waterloo computer science graduate. “I would rather go with the flow of innovation than resist, though there’s not really a choice in this rapidly evolving industry.”
Wang, who is currently working as a software engineer at Meta, is encouraged to use AI to boost his productivity and impact, from writing code to monitoring experiment metrics.
“I believe AI is a massive force multiplier for the individual. We may see single-owner companies that scale to billions in valuation,” he says.
Those who don’t adapt will fall behind
Josiah Plett believes the reporting on AI decimating jobs for computer science graduates lacks nuance. As he puts it, “macro trends” don’t impact everyone equally, because they don’t acknowledge someone’s unique expertise.
“Disruptors will come and go, but a software engineer who learns a lot will move where their value is seen,” he says. “As long as you don’t become complacent in only learning something you were told about seven years ago, then there will always be jobs available to you.”
After graduating in 2026, Plett has plans to return to his former employer, Maxima, an AI-powered accounting platform based in California. He was able to stay abreast in today’s tech scene through Waterloo’s co-op opportunities, which expose students to cutting-edge technology and a vast network.
Human v. Machine
What can humans do that AI can’t? For Wang, it’s reliability, as AI failure “is expected in the workflow.”
“AI models can hallucinate and make catastrophic mistakes with total confidence,” says Wang. This risk is amplified in high-stakes fields like finance and healthcare. Unlike AI, which isn’t invested in the outcomes of a project, “humans have their reputation on the line, so it’s easier to trust and hold them accountable versus an AI model.”
Indeed, this failure rate is highlighted by recent UWaterloo research, which shows that code created by AI is only 75% accurate.
Plett highlights how AI struggles with “high-level construal thinking,” also known as “big picture thinking.” Oftentimes, AI models can get lost in the weeds and prioritize non-essential tasks. For example, it may spot a bug and spend 15 hours fixing it, while a human would circle back and focus on the essential or foundational aspects of the project.
Plett and Wang also agree that AI lacks the soft skills that are needed in software development, such as collaboration, curiosity, and stakeholder management.
AI may work fast, but it’s still inefficient, showing that human judgment is needed more than ever.
AI will create more jobs, not less
Computer science has not only faced decades of disruption but has also been a key source of disruption for the wider economy. For example, the introduction of the internet sparked a demand for “web-based engineers.” Even the AI boom has invented jobs that didn’t exist five years ago or popularized them, like prompt engineers and AI security specialists.
Yet, computer science remains a thriving profession because it constantly produces technology that shakes up the status quo, which is what attracted Dasha Yefymenko to the field.
“Things like the modern laptop or phone happened because someone had a crazy idea, but they figured out how to implement it,” explains Yefymenko. “Although AI models still struggle with large-scale planning, they’re a fast and efficient tool for turning your vision into reality.”
Soon, Yefymenko will move to New York to work at her former co-op placement, Citadel. She advises students interested in computer science to position themselves as a “human in the loop” who can thrive in this new environment. Learn how to build AI projects by joining hackathons. Share your insights by cultivating a social media presence. Build a network by reaching out to AI experts.
“Invest in your skills and your personal brand, and job security will follow. I believe that AI is creating a lot of jobs at the same time as it’s taking away some of the older ones,” says Yefymenko. “The industry will always need people who can steer AI, even as it gets better.”
This echoes the approach to AI championed by the Cheriton School of Computer Science, where foundational skills in computer science and mathematics are at the core of the curriculum. Students learn how to engage critically with new and emerging tools, and are, in many cases, helping to build those same tools. Waterloo graduates are “AI-proof” precisely because these foundational skills will never be replaced.