The future of jobs in the software industry: Navigating the rise of AI

• A nuanced impact on software development jobs
• A need to understand the fundamentals
• Engineers add judgment and public trust
• Soft skills matter
• Interdisciplinary paths are booming
• Preparing for the future: education and training
• Hands-on experience is key
• Be strategic about upskilling
• Get involved
• Looking ahead

A nuanced impact on software development jobs 

Dr. Victoria Sakhnini, director of Waterloo's Software Engineering program, says that traditional entry-level work is changing.  

She explains that "instead of repetitive coding tasks, students are expected to think more critically from the start: designing systems, solving problems, and working with AI tools rather than competing against them." 

"It's a shift from writing basic functions to designing full solutions — and from “doing tasks” to deciding what should be built and how," she adds.  

Routine coding and test writing can be sped up, saving time and resources — and reducing the number of people to do this. At the same time, demand is rising for roles in data engineering, AI operations, model safety and governance, prompt and systems engineering, and human-centred design.  

A need to understand the fundamentals 

Dr. Sakhnini says that AI can generate solutions, but it doesn’t define new problems, design complex systems end-to-end, or make nuanced trade-offs. Software engineering education is increasingly focused on open-ended problems, challenging projects, and thinking beyond 'one correct answer'. 

"Without strong fundamentals, students won’t know what to ask, how to evaluate outputs, or when AI is wrong. This is why programs are doubling down on core learning, not skipping it."  

Dr. Mu Zhu, associate dean of AI strategy in Waterloo's Faculty of Mathematics, agrees. 

"AI will displace some existing jobs, but new jobs will be needed to manage AI. You can't manage anything that you don't have a good understanding of. These days, due to automation and online banking, we don’t have nearly as many bank tellers anymore, but successful banks are only getting bigger, not smaller, and employing more people, not fewer," he explains. 

In a report on how AI is creating coding jobs, Morgan Stanley, the global financial services firm, says "that despite concerns about job loss for software developers, AI should create more jobs as companies build increasingly complex applications. As AI coding tools become mainstream, developers are shifting toward more strategic roles." 

Engineers add judgement and public trust

During a 2026 industry retreat, experienced technology leaders explored how artificial intelligence is reshaping software engineering. Reflecting on the findings, Waterloo Engineering Dean Mary Wells noted that while AI can take on routine coding tasks, “what remains distinctly human and important that engineers can add is judgment and public trust.” 

AI can't replace human interaction and decision-making

Justin Krulicki is the Global Talent Acquisition Manager for Miovision, a Waterloo startup that helps cities optimize their road networks. He says that "humans are still needed to understand customer needs, build relationships, make strategic decisions, and collaborate across teams."  

Justin hires Engineering co-op students and graduates and sees a changing landscape.  

"AI is impacting all industries, not just software development. AI is reshaping how work gets done across industries and students in all fields need to adapt and build new skills." 

He adds that "new AI-focused roles are emerging and companies are increasingly hiring people who specialize in integrating AI into development workflows and improving developer experience." 

A shift in focus 

Going forward, software roles will focus on higher-level reasoning, systems thinking, and cross-disciplinary fluency. Organizations won’t value the ability to do routine tasks as much; roles focused on problem framing, architecture, reliability, ethics, and security will matter more.  

Employees who learn to lead AI-augmented workflows — combining prompt design, toolchain orchestration, data awareness, and governance — can make greater contributions to their organizations.  

Education that blends computer science fundamentals with data literacy, responsible AI, and product thinking builds durable skills for the future of jobs in the software industry. 

Soft skills matter

Learning to work with data scientists, product managers, designers, and subject matter experts helps ensure models solve real problems. Critical thinking and ethical reasoning help you spot risks and build safeguards. Clear technical writing — docs, model cards, and design reviews — builds transparency and trust. 

As cited by Fortune magazine, Udemy’s 2026 Global Learning & Skills Trends Report identifies qualities such as judgment, curiosity, flexibility, and risk tolerance as key to success in the AI era. 

Interdisciplinary paths are booming

Developers who understand areas like health care, finance, energy, or public policy can combine programming with AI tools to build targeted solutions. Human-computer interaction and design specialists craft explainable, trustworthy experiences around AI features.  

Roles that blend ethics, law, and engineering help address privacy, fairness, and compliance — showing how the AI impact on jobs reaches beyond pure coding. 

Preparing for the future: education and training

University education, such as Waterloo's Computer Science and Software Engineering programs, is evolving so graduates can build trustworthy AI-enabled products and adapt to new tools.  

Andrew Morton is the Director of Admissions for Waterloo's Faculty of Engineering. He says that over the last five years, the number of electives related to AI has tripled, there's an Artificial Intelligence option students can choose, and students use AI (such as Github and ChatGPT) for assignments, recognizing that these are skills that will be helpful in the workplace. 

Hands-on experience is key

Waterloo's world-leading co-op program and project-based learning gives students first-hand experience with how large and small businesses and organizations are adopting AI in their work.  

Padena, a recent Software Engineering graduate, says that there are a lot more startups emerging as AI advances and more early-stage startups are advertising more roles.  

"These roles typically come with more responsibility and a larger time commitment than a typical software development role and are more exposed to the business and sales aspects of the company." 

"Foundational knowledge from university is still essential, but real-world experience gives students a major advantage. Co-op helps students understand how businesses operate, solve real problems under time pressure, and build professional communication skills. Students with co-op experience are often more competitive in the job market," Justin Krulicki explains.  

Waterloo's co-op students are primed to succeed

• Working in the Tadesse Lab at the Massachusetts Institute of Technology (MIT), Jarett introduced the lab to AI and developed a diagnostic tool which leverages machine learning to address antimicrobial resistance in low-resource settings. 
• Dev took what he learned about AI in previous terms and leveraged that into co-op experience with Tesla. 
• As a software developer for SINTEF, one of Europe's largest independent research organizations, Shawn created an algorithm which monitors an AI model to predict inaccuracies in its responses.  
• During her work term at the Royal Bank of Canada (RBC), Linda designed an AI-powered system to streamline responding to employees’ human resources (HR) inquiries.

Be strategic about upskilling

Don’t chase every new framework. Anchor your learning in fundamentals like algorithms, distributed systems, and statistical reasoning, then add AI tools as needed.  

Keep up with responsible AI, privacy engineering, software assurance, and secure deployment to match the AI impact on jobs. 

Get involved

Community involvement helps you learn faster and meet mentors. Join meetups, hackathons, and seminars where people share their experiences. Ask good questions, document experiments, and share what you learn. These habits build credibility and often lead to opportunities. 

Looking ahead

AI is accelerating change across the software development field, but it’s also opening doors for creative, cross-disciplinary work. People who mix strong fundamentals with clear communication, ethical reasoning, and a willingness to learn will be ready for whatever comes next. 

Padena, the recent Software Engineering graduate, says that she’s not particularly concerned about AI replacing the need for software engineers. She explains that software design is complex and requires critical thinking about various tradeoffs. 

"Software engineering isn't just coding, it requires empathy towards the user, something I don't imagine AI can achieve."