A recent global talent shortage survey found that more than 70% of employers are struggling to find workers with the skills they need. ManpowerGroup’s 2026 study ranked AI roles among the most difficult roles to fill. Additionally, a 2025 World Economic Forum survey of more than 1,000 employers found that approximately 40% of the core skills of workers are expected to change as AI adoption accelerates.
Not only are companies struggling to hire AI talent, they are also rethinking how they build their talent pipelines. In addition to hiring more AI specialists, companies are grappling with how to build a broader level of AI-savvy workforce.
“The bigger, more pressing need is broad AI fluency across the organization,” said Greg Fuller, vice president of Codecademy Enterprise at education technology program provider Skillsoft. He noted that employers are increasingly prioritizing real-world competencies and the ability to interpret and apply AI in context.
New school models are beginning to explore this issue by incorporating AI directly into the learning process.
Alpha School’s AI-powered learning
Alpha School, a growing network of private schools, is built around an AI-first model. This approach targets students in kindergarten through 12th grade and rethinks how students spend their time in the classroom. Core academic instruction, including math, reading, and science, will be provided for approximately two hours per day through an AI-powered self-paced learning platform. The remaining time will focus on workshops and applied learning skills such as communication, entrepreneurship, collaboration, and problem solving. Teachers serve more as guides than traditional instructors.
According to Alpha School co-founder and CEO MacKenzie Price, the goal is to use AI to personalize learning to a level not typically possible in a traditional classroom. “We are finally able to elevate the role of teachers from mere content distributors to mentors and motivational experts, providing highly specific, individualized academic plans that meet each student at the level and pace that is right for them,” she said in a recent interview with Fox Business.
Alpha School describes the model on its website as “reimagining school” and positions it as an approach to preparing students for a workforce where AI is already part of how work is done. This approach allows students to complete core academic subjects in a fraction of the time, Price explained. “We’re teaching life skills… We’re helping develop kids who are ready to succeed in this AI-first world,” Price said in an interview on Fox.
AI in the classroom: delivery models and skill development
This new approach to education is built around AI, but the technology’s role is less about teaching AI as a subject and more about using AI to deliver the core educational experience. Fuller said models like Alpha School demonstrate that AI can personalize the pace and delivery of learning in ways that traditional instruction often cannot. And that principle is exactly what the workforce needs.
The most effective learning today is not static, one-size-fits-all learning, but “interactive, personalized, and embedded in real-world situations,” Fuller said. That distinction is important. “Using AI as a delivery mechanism improves the ease of use of the tool, but comfort is a prerequisite for readiness, not a substitute,” he said.
However, comfort alone is not enough. To use these tools effectively, learners need basic digital literacy fundamentals and an understanding of how AI works. Without it, businesses and educators risk moving too quickly to AI without a clear understanding of how it should be used.
This gap is not just theoretical. Adoption of AI in education is being held back less by the technology itself and more by a lack of human readiness, especially when it comes to AI literacy, suggests Gartner Vice President Analyst Tony Sheehan in his research report, AI in Higher Education 2026: How to Reduce Three Barriers and Increase AI Maturity.
AI fluency and job readiness
That’s not the only question how Students learn, but what Students must perform in the real world.
Fuller said companies still need AI specialists such as data scientists, machine learning engineers and AI architects, but the broader need is for AI fluency across roles. Hiring practices are increasingly moving towards a skills-first approach, with employers prioritizing demonstrated actual competency over degrees and titles, he added.
“The most in-demand candidates combine technical AI literacy with human-centered skills: critical thinking, communication, collaboration, and ethical awareness,” Fuller explained. “These are the people who can not only operate the tools, but also interpret the output of AI and use AI responsibly.”
Alpha School’s model aligns more closely with a broad definition of AI fluency than training for a specific technical role. We value adaptability and comfort in working with AI over deep technical expertise. This approach prioritizes adaptability, problem-solving, and comfort with AI systems by incorporating AI into the learning process and emphasizing self-directed learning and life skills.
But familiarity and fluency are not the same. While students may be familiar with using AI, it is less clear whether this will lead to the deep understanding needed to question, interpret, and apply those tools in real-world settings.
Personalization alone is not enough
While this level of personalization can improve efficiency and engagement, it also raises the question of what might be lost as learning becomes increasingly mediated through AI systems.
Alpha’s model is built around continuous feedback and adaptation, using AI to tailor lessons to students’ abilities and interests. In theory, this approach allows learners to progress faster through the material they have mastered, while also allowing them to spend more time on areas where they need support. This is one of the core promises of AI-driven education.
AI raises the bar for everyone, but it can also lower the ceiling if learners don’t acquire deep, domain-specific knowledge.
greg fullerVP of Codecademy Enterprise at Skillsoft
However, personalization alone does not guarantee understanding. Fuller warned of what he called the “knowledge cliff,” where learners appear competent because they can produce results with AI, but lack the fundamental expertise to operate independently. “AI will raise the floor for everyone, but it may also lower the ceiling if learners do not develop deep domain-specific knowledge,” he said.
This concern is becoming more apparent in the educational field as well. A Gartner study found that while the use of AI is widespread, most institutions are still not seeing meaningful results, and only a minority are reporting measurable returns from their investments. More broadly, this study points to a deeper problem. In other words, AI readiness is not about the technology itself, but whether people know how to use it effectively. Students could become dependent on AI without knowing when to trust or question it. The work they produce may seem sophisticated, but they lack the ability to explain it or use it outside the classroom.
The future of AI-driven education
Learning models like Alpha School could signal far-reaching changes in education, but it’s still early days. “This is a meaningful signal, but it’s not yet a proven change,” Fuller said. “What models like Alpha School get right are the underlying principles: AI needs to make learning more personalized, more applicable, and more measurable. That’s the direction the entire learning industry is moving.”
Much AI training, both in school and in the workplace, still follows a familiar pattern. In other words, they consume the content, check the box, and move on. The change Fuller described is a move toward a more hands-on, adaptive approach that focuses on building real capabilities over time.
But that transition comes with challenges, particularly around scale, equity, and outcomes. As these models evolve, questions remain about how broadly they can be applied, who will benefit from them, and whether they consistently produce measurable results. AI has the potential to transform education, but Gartner research shows that AI adoption remains uneven and often lacks a clear strategy.
Alpha schools may not represent a new way to teach AI, but a new way to teach in a world where AI is already embedded. It is still an open question whether this approach will lead to true fluency in AI or just habituation.
Liz Hughes is an award-winning editor and writer covering AI and emerging technologies and a former magazine editor. AI business and Today’s IoT world.
