Five tips to harness emerging talent and innovate with AI
By: Christie Zeb (she/her)
Employers and students explore how artificial intelligence (AI) is transforming work, and how emerging talent is uniquely positioned to drive innovation.
On November 19, Waterloo’s Co-operative and Experiential Education hosted The AI generation: Innovation powered by co-op students. The webinar explored how co-op students can drive both the adoption and effective use of AI.
Moderated by Dr. David Drewery, associate director of the Work-Learn Institute (WxL), the session featured insights from industry experts and a panel of three co-op students:
- Michèle Scrimger, director, Impact Lab, Impact Assessment Agency of Canada
- Justin Krulicki, global talent acquisition manager, Miovision
- Sara Joo, Computer Science co-op student, Faculty of Mathematics
- Aziz Chowdhury, Computer Engineering co-op student, Faculty of Engineering
- Aditya Chaudhary, Computer Engineering co-op student, Faculty of Engineering
The conversation examined how employers can harness student talent to experiment with AI and accelerate organizational AI maturity.
Students want training in responsible AI use and clear policies to guide it. Fewer employers are providing this, highlighting that AI isn’t just a technical challenge; it’s a human one. Bridging these gaps is key to building workplaces where AI empowers people, not replaces them.
Here are five tips shared by the speakers and student panel:
1. Treat students as strategic partners
A key insight from the event was that students excel when given meaningful responsibilities throughout an organization’s AI journey. They’re not just task executors – they’re co-creators and domain experts.
For example, at the Impact Assessment Agency, Michèle Scrimger runs Impact Labs on student talent and empowers students to experiment, build AI agents and contribute at every stage of AI adoption.
“We really treat our students as subject matter experts,” Scrimger says.
“We are ensuring that they have the possibility of bringing their lived experience, and their learnings in school or just out of school, to the workplace so that we can take advantage of that.”
Give students opportunities to design, validate and iterate. Their fresh perspectives can often uncover gaps and drive innovation throughout the AI process.
2. Start with the problem, not the tool
AI is powerful, but it’s not a magic fix. Successful adoption starts with a deep understanding of the problem before considering automation.
Sarah Joo spent a co-op work term at the Impact Assessment Agency of Canada and highlighted how her team at the Impact Lab always began by getting a good grasp of the issue before implementing a solution.
“It's really important that we explore the problem in-depth and find the root cause of inefficiencies,” Joo says. “Then we're able to prototype methods of solving the issue, either using AI or not.”
Involving students in identifying challenges and testing potential solutions ensures AI is applied intentionally.
3. Keep humans in the loop
Among the student panel, a common theme was the importance of keeping humans at the center of AI use.
Aziz Chowdhury explained how he uses chain-of-thought reasoning (asking the model to break problems into logical steps) and k-shot prompting (giving examples in the prompt) to reduce hallucinations.
He also gives the AI “reward” prompts to prioritize accuracy in tricky edge cases.
“My employer really empowered me to think about how to have the human in the loop, how to have fallbacks for when the AI makes false predictions, and that really allowed me to succeed,” Chowdhury says.
“I noticed that the AI would make hallucinations — incorrect or fabricated answers for various edge cases, and so I leveraged some prompting techniques to reduce those hallucinations.”
4. Balance AI use to maximize learning
Insights from the student panel revealed that overreliance on AI can reduce critical thinking, limit creativity and slow skill development.
Aditya Chaudhary realized that using AI as a shortcut took away the joy of problem-solving. After feedback from his manager during his co-op term at Miovision, he shifted his approach to using AI intentionally as a learning tool.
“I found that asking intelligent and directed prompts that have a single goal in mind yields the best results,” Chaudhary says.
“The only way that you're going to be able to ask such prompts is if you take the time to truly understand the architecture of the project and have a thorough understanding of the problem that you're trying to solve.”
5. Adapt recruitment to spot genuine talent
AI is shaping recruitment, from applications to interviews, making it harder for employers to assess candidates’ skills and creativity.
Justin Krulicki highlighted the importance of structured interviews and well-trained interview teams to reveal the true skills and thinking of each candidate. Using a combination of behavioural and non-behavioural questions can allow employers to assess both a candidate’s experience and real-time problem-solving skills.
“Having in-person interviews, which a lot of companies are starting to return to, is one strategy to combat the AI challenges,” Krulicki says.
“There's a lot of information in those social cues. People showing up to the right room on time, dressed appropriately. These are things that maybe you don't get in a virtual interview.”
Co-op students aren’t just temporary help – they’re co-creators in the AI era. Employers who give them responsibility, clear guidance and space to innovate will innovate faster and future-proof their organizations.