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Join on Telegram Rabat – As policymakers, educators, and technology leaders gathered at the World Governments Summit 2026, one of the most pressing topics resonating across sessions was the challenge of equipping today’s learners and tomorrow’s workforce with the skills they need to thrive in an era of artificial intelligence.
At the heart of this conversation was Cynthia Breazeal, Director of the MIT Responsible AI for Social Empowerment & Education (RAISE) initiative, who offered a clear call to action: governments around the world must move beyond narrow assumptions about AI education if they hope to prepare future workforces equitably and effectively.
Speaking in a plenary session attended by ministers of education, heads of national AI strategies, and leaders of global education foundations, Breazeal outlined what she sees as the single biggest misconception many governments hold about AI literacy, and why rethinking that misconception matters for countries at every stage of economic development.
‘AI Literacy is not just for tech students’
One of the central themes of Breazeal’s remarks was the idea that AI literacy cannot be confined to elite universities or specialized technical programs.
Rather, she argued, governments often underestimate the breadth of AI’s impact, and thus the scale of the educational response required.
“What I hear from many governments today is a strong focus on university‑level programs and pilot efforts in selective schools,” Breazeal said.
“But the reality is AI is transforming many different roles across many different industries, and so AI literacy is truly for all students.”
She stressed that this is not just about future engineers or computer scientists: AI technologies are already embedded in everyday tools and systems used across sectors like healthcare, agriculture, customer service, manufacturing, transportation, and media.
Breazeal expanded this idea to argue that AI literacy needs to be built from the earliest stages of schooling all the way through adult education.
“AI literacy should start in K‑12 and create a glide path to two‑year vocational technical colleges, four‑year colleges, and so forth,” she said.
In other words, meaningful AI education must begin early and extend into lifelong learning systems, otherwise large segments of the population risk being left behind.
This broader perspective challenges a common assumption that exposure to AI should be limited to older students or those pursuing advanced degrees.
Breazeal pushed back against that idea. “Even children are growing up with technologies that have AI infused in them,” making it critical that they understand not only how to use these tools, but what they are, how they operate, and the social and ethical questions they raise.
The opportunity of community and technical colleges
A striking part of Breazeal’s intervention was her emphasis on educational sectors that are sometimes overlooked in global policy conversations: two‑year vocational and technical colleges, often known as “community colleges” in the United States.
“I can tell you that as I go to more conferences and speak about this topic, many governments are paying attention to the K‑12,” she said.
“They acknowledge that, and many are certainly focusing on the university level. But the technical vocational two‑year educational track is also a really critical segment to pay attention to, and that’s a big opportunity.”
In the US, community colleges exist in all 50 states and serve a wide range of learners, not just recent high school graduates, but adults already in the workforce who are seeking new skills or career pathways.
Breazeal described these institutions as “engines” that could be repurposed to serve national goals of AI upskilling and workforce transformation.
“They’re not teaching AI skills yet,” she acknowledged, referring to many current programs. “But they could certainly be engines for that for the nation.”
In her view, community colleges offer a flexible bridge between formal education and practical workforce needs, providing accessible opportunities for people to add AI competencies regardless of their age or prior background.
This message resonated with leaders from countries with large populations of young people and rapidly evolving labor markets, particularly African states where vocational training systems are expanding but many learners lack access to AI‑related content.
How governments can ensure AI education works
Another key question Breazeal addressed was how governments can move beyond pilot programs, short‑term, small‑scale projects, and build education systems that deliver AI literacy at national scale.
At MIT RAISE, she explained, the organization’s approach to education implementation is intentionally phased and grounded in local context.
“It is a phased approach where you intentionally, logically, you do start small in a pilot,” Breazeal said.
But rather than treating pilots as one‑off experiments, her team uses them as platforms for collaboration with local educators, diverse schools, and students representing the populations education systems want to serve.
The goal, she said, is to co‑design educational material that is not only technically sound but also culturally relevant and deliverable in classrooms.
Teachers and schools involved in early pilot stages then become trainers themselves, forming the backbone of a train‑the‑trainer model that expands capacity over time.
“But the whole goal here is MIT is providing these open and free materials by which a region, a country, can customize them, localize them, translate them,” Breazeal noted.
“Whatever it takes for them to really own it and feel that this is really a quality representation of what AI literacy means to them.”
This emphasis on open resources capable of localization is critical for governments with diverse languages, educational traditions, and technological infrastructures.
Rather than imposing externally developed textbooks or curricula, the model supports adaptation and ownership by local educators and ministries of education, a distinction Breazeal sees as essential for sustainability.
Once these teaching resources are tested and adjusted in early pilots, the next phase involves building teacher capacity nationwide, often through partnerships with local education organizations, including teacher unions, municipal systems, and regional educational nonprofits.
“That intentional capacity building is what allows programs to scale,” Breazeal argued. “We help bootstrap it, but then we transition it, and we allow local capacity to really take it from there and be sustainable.”
Balancing AI creation and AI use in emerging economies
In a session focused on education policy challenges facing African nations and other emerging economies, Breazeal was asked whether governments should prioritize training AI creators, those who build new technologies, over AI users, those who apply tools in the workforce.
She responded by emphasizing that the distinction isn’t a choice between mutually exclusive goals: both are needed for healthy economic and social growth.
“You really do need both,” she said, citing the importance of innovators who can conceive and build new solutions that improve industries and civic life, as well as professionals who can use AI tools effectively in everyday roles.
Breazeal stressed that “using AI to create new value” includes a spectrum of activity, from people developing large foundational models or new AI systems to entrepreneurs and business owners who leverage tools to improve efficiency, design novel products, or reach new markets.
Equally important, she insisted, is preparing people to be responsible users of AI in their personal and civic lives.
“We need to make sure that people are conscientious users as well as designers,” she said, “because these tools can do really cool, exciting things, but they can also do really harmful things if used without awareness of their risks and potential harms.”
Looking ahead
As the summit drew to a close, several clear policy implications emerged from Breazeal’s remarks and the broader discussions they informed. These include:
Governments should embed AI education across all levels of schooling, ensuring that every student, from young children to adult learners, gains a baseline understanding of how AI works and how it shapes the world around them.
Rather than focusing exclusively on elite universities or isolated pilot programs, policy frameworks should include pathways that connect earlier education stages with vocational training, higher education, and workforce development.
Open educational resources should be adaptable, culturally relevant, and flexible so that countries with diverse languages and traditions can make them their own.
Scaling AI education isn’t just about distributing materials; it’s about empowering teachers, administrators, and local institutions to deliver quality learning experiences sustainably.
Preparing people to both create with AI and use it responsibly ensures that societies benefit from the technology while minimizing harm.
