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Adewunmi Ajike never thought she would be working in the AI field when she was in school. Mentors encouraged her to apply for roles outside her comfort zone, which led her to a program that exposed her to product management and AI.
She saw how AI could be used to help team members work more effectively. She studied economics, business, and French in school, but she was able to upskill and learn on the job to become “AI-ready.” She has now been working in the technology and AI space for five years as a product manager. She notes that AI won’t replace all jobs, but “somebody who knows how to use AI could potentially replace your job.”
She shared her story with us as a panelist in the Bold Futures webinar, Plugged In: Youth Skills for an AI Driven World. The anticipated impact of AI on the labour market is uneven and deeply tied to systemic inequities. According to our DEVLab research, 49% of Black youth and 43% of racialized youth fear their jobs will be eliminated by AI within a decade, compared to 33% of white youth. Youth employed in trades, agriculture and manufacturing perceive a greater risk.
So, how do we create sustainable work ecosystems in the evolving AI landscape?
This article was originally published by Youthful Cities and has been reprinted with permission.
Learning in the AI era
Learning skills in the AI era demands intention. The temptation to collect certificates or hop between online courses to fulfill hiring requirements creates a shallow, fragmented understanding. Instead, deep learning – rooted in curiosity, application and reflection – is more essential than ever. Youth looking for sustainable employment must learn not just to use AI, but to question it: Where does the data come from? What biases are embedded? How can these tools support equity, rather than reproduce inequality?
Webinar panellist Uma Kalkar, a sociotechnical researcher and former research and innovation manager at Youthful Cities, explains:
“Education has to shift from being about memorization and getting really good grades to actually being able to mobilize. Can you leverage a tool that you’ve learned in one context and put it in something that is completely new?”
The role of mentorship and non-linear paths
Mentorship, collaborative learning and interdisciplinary thinking also emerge as critical pillars. Several panellists described non-linear journeys into AI, coming from psychology, civic tech or design.
Their message: you don’t have to be a computer science major to shape the future of technology. What matters is an openness to learn, a willingness to ask hard questions and a commitment to applying knowledge to real-world problems.
“The best mentors that I’ve had are people where the relationship has kind of developed organically. And I would say, get involved in community. It doesn’t even have to be the tech community. Sometimes you don’t know where the people who are going to help you will actually come from, “ said Genna Weber, webinar panelist and Open Data and IT Manager, Youthful Cities.
That said, employers also bear responsibility. As Genna Weber noted, if companies want skilled talent, they must invest in junior hires and foster sustainable growth. The current standard for “entry-level” roles – often requiring years of experience – is unsustainable. To truly future-proof the workforce, we must build ecosystems where young people can experiment, fail and learn.
Policy: Youth must have a seat at the AI table
At the policy level, Canada has invested heavily in AI research, yet lags in AI regulation. As policy expert and sociotechnical researcher Uma Kalkar noted, the federal government’s proposed Artificial Intelligence and Data Act (AIDA) remains non-binding and lacks enforceable protections. Meanwhile, the European Union has passed comprehensive legislation in the form of the EU AI Act.
This regulatory vacuum leaves frontline educators and youth to navigate AI’s risks without support. The Canadian Teachers’ Federation (CTF/FCE) warns, “Right now, Canada lacks clear federal and provincial/territorial policies to ensure AI systems in schools are safe, ethical, and equitable. Without urgent action, teachers will continue to face the burden of managing AI’s impact on students – without the protections or guidance they deserve.”
This concern is echoed by webinar panellist Samin Khan, GenAI Research Engineer in Education and former teacher. When asked what he would do if he could wave a magic wand to improve AI in education, he said:
“The answer that I’ve heard the most frequently from teachers has been something like having smart glasses, or Google Glass, in the classroom. Being able to see where each of the students are on their learning journeys. Teachers want to be able to have that level of insight into their students’ learning levels without being overburdened by information … [having] computational models that will identify what misconceptions students are making and then provide them with follow-up questions to keep them at that zone of proximal development.”
These visions are ambitious – but they reflect a growing need for tools that are thoughtfully integrated, rather than passively adopted. And the CTF/FCE research indicates that Canadians agree:
- 95% of Canadians support the rights of parents, students and educators to consent to how and when their data is used in public education.
- 93% of Canadians agree that provincial/territorial governments are responsible for ensuring student and teacher data is protected and secured.
Reimagining participation and power
The policy landscape in Canada also sidelines the very people most affected by AI: young people. A high-agency approach to policy means involving youth not just as stakeholders, but as co-designers. Whether through youth-led research, solution labs or public consultations, their lived experience must shape how AI is governed.
Data governance, algorithmic transparency and equitable access to AI tools aren’t just technical concerns, they’re civil rights issues. Building intergenerational, future-oriented policy is no longer optional. It’s urgent.
In the face of automation hype, job displacement fears and overwhelming information, it’s easy to feel powerless. But the antidote is high-agency thinking: the belief that you can act, create and make change. It means learning purposefully, working adaptively and organizing collectively.
AI may shape the future, but it is young people who will shape AI.
