Introduction
We are living in a time when the world is changing at an unprecedented rate. Artificial intelligence (AI), algorithms, automation, and big data are no longer just buzzwords—they are reshaping how we live, how we work, and how we learn. In their powerful and practical book, What To Do When Machines Do Everything, Malcolm Frank, Paul Roehrig, and Ben Pring explore how individuals and businesses can survive—and thrive—in this rapidly evolving world. Although the book is primarily geared toward business leaders, its insights hold deep meaning for educators as well. If machines can now perform many tasks that used to require human intelligence, then what exactly should we be teaching in our schools? Moreover, how should we be teaching it?
This article examines the pressing need to reassess education, specifically curriculum, instruction, and assessment, in light of the changes described by the authors. More importantly, it outlines how educators can respond not with fear or resistance but with creativity, confidence, and vision.
Rethinking Curriculum: From Memorization to Meaning
Let us begin with the heart of education: the curriculum. Traditionally, schools have focused on helping students memorize facts and master content. However, in a world where machines can store and recall information faster than any human, that approach is no longer enough. As the authors point out, the most valuable skills in the AI era are those that machines struggle to replicate—skills such as critical thinking, emotional intelligence, creative problem-solving, and adaptability. These are the capabilities that truly distinguish humans.
So, what does this mean for curriculum design? It means schools must shift their focus from “what students know” to “what students can do with what they know.” More than ever, we need to teach students how to think across disciplines, how to question assumptions, and how to approach challenges from different angles.
It also means weaving digital fluency throughout the school experience. In today’s world, technology cannot be an afterthought—it must be part of every subject. For example, students should discuss the ethics of AI in philosophy class, analyze data trends in history, explore coding in math, and use simulations in science. Instead of keeping subjects in separate boxes, we must encourage students to make connections and apply their knowledge to real-world problems. In this way, the curriculum becomes less about memorizing information and more about preparing for life.
Transforming Instruction: From Lectures to Learning Partnerships
Of course, changing what we teach also means changing how we teach. In the traditional classroom, the teacher stands at the front and delivers knowledge while students take notes. But today, machines can do much of that work. AI-powered tools can now explain concepts, track student progress, and even personalize instruction to meet individual needs. This does not mean that teachers are no longer needed. On the contrary, their role has never been more important.
As Frank and his co-authors suggest, teachers must become designers of learning experiences and mentors for a new generation. That means moving away from passive lectures and toward active, student-centered learning. It means creating classrooms where students collaborate, ask questions, and engage in meaningful projects. It means guiding students to explore ideas deeply and think critically—skills that machines can’t replicate.
At the same time, educators themselves should model what it looks like to work effectively with technology. This means using AI tools not just as add-ons but as integral parts of instruction. For example, teachers might utilize virtual tutors, writing assistants, or real-time data dashboards to gain a deeper understanding of their students’ needs. By doing so, they not only improve their teaching, they also show students how to use technology wisely, responsibly, and ethically.
Reimagining Assessment: From Testing to True Understanding
Assessment is another area where change is long overdue. For decades, we have relied on standardized tests to measure learning. However, these tests often reward surface-level memorization rather than deep understanding. In a world shaped by AI, we need assessments that prioritize creativity, collaboration, and critical thinking skills, essential in the real world.
Instead of just filling in bubbles on a test sheet, students should be asked to demonstrate what they have learned through portfolios, presentations, group projects, and real-world problem-solving tasks. These forms of assessment enable students to demonstrate their knowledge in meaningful and authentic ways.
AI can also support better assessment by giving instant feedback, identifying learning gaps, and helping teachers tailor instruction. However, we must remember that machines cannot interpret emotions, context, or personal growth. That is where the teacher comes in—using human judgment and care to guide students and help them grow.
Leading the Shift: A Strategic Model for Change
So, how do schools make this transformation? One helpful guide is the AHEAD model, as described in the book. This five-part framework—Automate, Halos, Enhance, Abundance, and Discovery—offers a powerful way to think about how education can evolve:
Automate: Utilize machines to handle routine tasks, such as grading and scheduling, allowing teachers to spend more time building relationships and mentoring students. Halos: Surround traditional learning with digital tools—like apps, dashboards, and simulations—that deepen understanding and engagement. Enhance: Utilize technology to support and expand human potential rather than replace it. Let AI assist with tasks, allowing teachers and students to focus on creativity and connection. Abundance: Use digital platforms to make high-quality resources available to all students, not just the privileged few. Discovery: Encourage innovation by giving students opportunities to explore, experiment, and create in ways that are meaningful to them.
This kind of change will not happen overnight. It requires leadership, courage, and a willingness to rethink long-standing traditions. Teachers need professional development. Schools need better access to devices and internet connectivity. Policymakers must support these shifts with adequate funding and a clear vision. However, the need is urgent, and the opportunity is enormous.
Conclusion
In What To Do When Machines Do Everything, the authors remind us that machines will take over many tasks, but they cannot take our place as thinkers, creators, and moral beings. That message should resonate deeply with educators. Schools are not factories for producing test scores. They are communities where young minds are shaped and prepared for the future.
If we want that future to be bright, we must act now. We must redesign the curriculum to develop the human skills that matter most. We must transform instruction to make learning an active, collaborative, and meaningful experience. Moreover, we must rethink assessment so it measures what truly counts. Most importantly, we must teach our students not to fear machines, but to use them wisely, partner with them creatively, and lead with values that only humans can hold. The age of intelligent machines is here. Education must rise to meet it, not with fear, but with purpose.
