Artificial intelligence is reshaping education and work in real time. As one of the most transformative technologies of our time, it can either expand opportunity or deepen inequity depending on how it is used.
I remain optimistic about AI because I fundamentally see it as a tool. Used wisely and safely, it can help people work more efficiently, learn more effectively and access knowledge in new ways. But if access is uneven or young people are not given the guidance to use it effectively, AI could accelerate existing inequities rather than help close them.
We have seen this pattern before. As the internet became widely available, access at home, in schools and through public resources such as libraries was far from equal. For students, the divide was not simply about getting online. Those with a computer at home, reliable internet service and adults who understood the technology had more opportunities to learn how to use it and apply it.
AI appears to be following a similar path. Although its use among young people is already widespread, availability alone does not create meaningful access. The real advantage comes from understanding how to use these tools, knowing which questions to ask and being exposed to the technology early enough to explore its possibilities.
There is also a new layer to the access question. Increasingly, the most powerful capabilities of these tools sit behind premium plans, additional credits and paid subscriptions. We should be careful not to define equitable access as simply making some version of AI available. If the students with the greatest resources consistently have access to more capable tools, more computing power and more opportunities to experiment with them, we risk recreating the same digital divide in a new form.
Students from affluent communities may also have greater access to adults who use AI in their own work and can help them understand its applications. They have something else that often goes unspoken: the time, space and freedom to explore. The ability to explore should not be a luxury.
The challenge is not AI itself. It is whether every student will have access to the opportunities that come with it.
The risk is not simply that some students will lack access to AI. It is that they will fall behind in understanding how the technology is used, where it is creating possibilities and how it can help advance their education and career goals across fields including healthcare, manufacturing, construction, energy and the skilled trades.
At our TGR Learning Labs, we see the effects of this gap firsthand, particularly among students from under-resourced communities, and we are working intentionally to help close it.
To balance the risk, it is critical that underserved students are introduced to AI and other emerging technologies at an early age through lessons that build core fundamentals while also providing relevant learning experiences.
These experiences, grounded in mentorship and career exposure, are important. So is access to trusted environments where students learn how technology can enhance human connection rather than replace it. That includes helping students understand that AI is a resource, not a replacement for foundational learning.
Students still need strong foundations in reading, writing and mathematics. They need to think critically, communicate effectively, evaluate information and solve problems. As AI becomes more capable, these durable human skills will become more valuable, not less. These skills are what students will rely on most, whatever path they choose. Overreliance on AI could allow students to produce work quickly without mastering the fundamentals needed for long-term success. Education must continue to prioritize curiosity, critical thinking and original ideas.
Those of us already using AI extensively in our work are learning this firsthand. I can let AI run with a problem and become dramatically more productive as a result. But I also know that I have to question its work, challenge its assumptions and ultimately apply my own judgment and experience to what it produces. The more powerful the tool becomes, the more important that judgment becomes. Young people need to learn that distinction early. AI can accelerate their thinking, but it cannot become a substitute for learning how to think.
Meaningful AI literacy for young people also requires practical experience. Students need opportunities to use AI beyond simply generating an answer—to build something, test an idea, analyze information and solve real problems. Those experiences can reveal possibilities students may not have known existed and lead to new skills, adjacent careers and pathways they may not otherwise encounter.
Perhaps most excitingly, AI has dramatically shortened the distance between an idea and the ability to create something. A young person no longer needs years of coding experience to begin building an app, developing a prototype or testing a business idea. The barriers to creation and entrepreneurship are falling at extraordinary speed. For students who historically may not have access to technical expertise, capital or professional networks, that represents an enormous opportunity—if we give them the tools and knowledge to take advantage of it.
In practice, that approach is reflected in access to free programs and experiences that teach young learners the core competencies of AI at an early age, offer stackable lessons and trainings as they grow, provide exposure to high-demand careers and create opportunities for real-world learning with industry professionals.
At TGR Foundation, we’re already practicing what we preach through our new AI curriculum partnership with Comcast. Students at our TGR Learning Labs begin by building foundational AI literacy through hands-on experiences that demystify how AI works. This ranges from understanding how prompts shape responses and how AI recognizes patterns to evaluating the reliability of AI-generated content and using these tools responsibly. They then apply those skills to authentic challenges in healthcare, entrepreneurship, marketing and other fields, using AI to analyze information, develop solutions and create real-world projects. Through capstone experiences, students identify challenges in their schools and communities and leverage AI agents to support research, ideation and problem-solving. The goal is not simply to teach students how to use AI, but to empower them to become ethical innovators who use AI to address meaningful issues in their communities.
The goal is to ensure all young learners have the knowledge, experience and support needed to use AI in ways that deepen learning, expand creativity and strengthen their capabilities without replacing the thinking and effort required to develop them.
Another opportunity we need to share with students is what AI means for their future careers. Understanding how to harness AI as they move through school and into the workforce is vital. Equally important is helping them understand that the opportunities being created by AI extend far beyond careers at technology companies.
Supporting that growth will require skilled professionals to build, power, cool and maintain the infrastructure behind it. These careers require technical knowledge, problem-solving and adaptability while offering strong, often entrepreneurial pathways.
Preparing students for this future requires earlier career exposure, hands-on learning and opportunities to develop durable skills. They also need mentors, internships and relationships that help connect their interests and abilities to meaningful career pathways.
If access to AI, meaningful exposure and informed guidance are not equitably available, the opportunity gap will widen. Students who are already ahead may accelerate further, while those who have historically lacked access to technology, professional networks and career-connected learning risk falling further behind.
We cannot allow AI literacy to become another advantage reserved for students who are already best positioned to succeed.
Closing this gap will require collaboration across education, nonprofit organizations and industry. We need to invest in equitable access to AI education, support educators as they navigate rapidly changing tools and create clear pathways into evolving careers.
AI has the potential to make learning more personalized, career pathways more visible and opportunity more widely available. But technology alone will not create equity. That will require intention, investment and a shared commitment to every young person.
We have a responsibility to get this right. The goal is not simply to prepare students to use new technology. It is to ensure they have a meaningful place in the future that technology is creating.
And a meaningful place begins with knowing what is possible. In the next article in this series, I want to talk about why helping a young person discover what they care about—early, and on purpose—may be the most important thing we do.
