We need a ‘renewed mindset of lifelong learning’: Five takeaways on how Canadians can best navigate the turbulent future of work

A profound transformation is underway in the Canadian economy, driven by artificial intelligence, automation, and a new era of industrial policy. In a recent Hub Dialogues episode, presented in partnership with Pearson, three key leaders from the realms of business, higher education, and global learning issued an urgent, collective warning: Canada’s future prosperity hinges on its ability to bridge a growing chasm between the skills graduates possess and the dynamic needs of the modern workforce. The conversation, featuring Theo Argitis of the Business Council of Canada, Gabe Miller of Universities Canada, and Jessica Biga-Wadstein of Pearson, revealed a striking consensus on the challenges and necessary paths forward. Below are five key takeaways from their discussion. 1. The pace of change is the central challenge The core issue is not necessarily today’s skills gap, but the accelerating rate of economic change that threatens to leave the education system behind. Argitis framed the problem not as a curriculum issue, but as a systemic one. “The real question for Canadian CEOs is not really about that gap today, but whether the education and training system can move at the same pace as the economy is moving,” he stated. He emphasized that the concern is “the potential gap that’s coming,” warning that Canada risks being “structurally left behind in a big way” if it fails to keep up. This sentiment was echoed by Biga-Wadstein, who pinpointed “the pace of change” as a primary obstacle. “Technology, especially AI, it is reshaping this workforce faster than curricula can adapt,” she said, noting that by 2030, “nearly 65 percent of in-demand skills will be redefined by AI and digital transformation.” 2. The solution lies in “connective tissue” and agility All three guests agreed that the solution requires building stronger links—or “connective tissue”—between employers, educational institutions, and government. Argitis argued that the system must be “built for agility,” fostering an environment where universities, colleges, employers, and governments “are going to be working a lot closer together in ways that we probably haven’t done before.” Miller pointed to the revolution in “work-integrated learning”—such as co-ops and internships—as a prime example of this connective tissue in action. “From that world that I graduated into… we’ve transformed the country to one where almost half of students studying for a bachelor’s degree will get some kind of work-integrated learning experience,” Miller noted, adding that “three quarters of them say after graduation it helped them find their first job.” 3. The “learn to earn” model is obsolete—lifelong learning is the new norm A recurring theme was the definitive end of the traditional educational pathway. The old model of learning once and working for decades is no longer viable. “That traditional learn to earn model… You go to school, you get a degree, and that’s supposed to carry you through for the rest of your career. That just isn’t the case anymore,” Biga-Wadstein asserted. She called for a “renewed mindset of lifelong learning,” where people can continuously upskill “without having to step outside of the workforce.” Miller emphasized that universities are now obsessed with two objectives: educating people for a full life as citizens, and equipping them “for today so that they can step off of campus the moment they graduate into a world that is incredibly challenging and disruptive, and feel like they are fluent enough in the modern workplace… so that they cannot just survive, but start thriving.” 4. In an AI world, human skills and management become universal While technical and digital skills are in high demand, the discussion highlighted the enduring and perhaps heightened importance of human-centric skills. Miller suggested that in the face of “unknown unknowns,” the safest bet is on “the human or the executive skills, communication, emotional intelligence, judgment, intercultural facility.” He also introduced a provocative idea about the future of work in an AI-saturated economy: “I was just reading a very interesting piece that said in an AI world, everyone’s going to be a manager. We’re all going to be needing to direct the work of… a team of AI agents.” This, he argued, means that management skills, once a specialized domain, will need to be cultivated in nearly every worker. 5.  A truly integrated system requires leadership and shared infrastructure The final takeaway was a call for a more cohesive and collaborative ecosystem. Argitis identified a major barrier as a “lack of information,” where employers “often don’t know where to start.” He called for all parties to “take some responsibility to figure out how to build that… soft tissue.” Miller pointed to the cultural leadership required, warning that as universities face financial pressures, there is a risk of retreating to a traditional model. “We have to keep that door open during this very challenging period… because that’s the future and a lot is counting on it for the country,” he said. Biga-Wadstein positioned Pearson as a potential facilitator, stating that achieving a truly integrated system requires “shared infrastructure for learning that includes shared goals, shared data, even shared accountability.” She concluded that for this to work, institutions must act as “career enablers,” and employers must “proactively contribute a little bit more to co-develop those learning pathways and not wait for talent to arrive job-ready. It’s going to take all three of us.” The message was clear: Navigating the turbulent future of work will require unprecedented agility, collaboration, and a lifelong commitment to learning from every sector of Canadian society. Generative AI assisted in the production of this story.