Quantum Computing is widely perceived as “the next bit thing” in technology, offering incredible gains in power. For example, in October 2025, Google’s Willow chip (105 qubits) performed a computation in under five minutes that would take today’s fastest supercomputers roughly 10 septillion years.
As of May 2026, Quantum Computing has officially crossed the threshold of verifiable quantum advantage, moving from theoretical laboratory experiments to measurable superiority over classical supercomputers for specific tasks. The hard work at this stage is designing highly specific new algorithms for the highly specific tasks Quantum Computers can perform.
In education, it is speculated that Quantum Computing will enable hyper-personalization, where the billions of data points reflecting a learner’s cognitive load, attention span and emotional state can be resolved in real-time to enable deeply nuanced guidance. There also intriguing possibilities from security and credentialling through to advanced STEM simulations.
Opportunity Statement
Market-building for Quantum Computing has barely begun across global industries – the opportunity horizon in teaching and learning is wide open. What are educators going to do with Qubits?
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The fast growth of Artificial Intelligence in education is both unavoidable and mostly positive. As technology becomes more powerful, students and teachers can access information and learning resources much faster than before. AI can help learners receive feedback, guidance, and educational support in a shorter time and in a more organized way.
However, one important concern for me is the idea of hyper-personalized learning. If AI prepares all educational content, questions, and learning materials based on each student’s personality and personal abilities, students may slowly start learning very different things from one another. Although this can improve individual learning, it may also create problems in teamwork and communication.
In group work, people need some shared understanding and common ways of thinking. But if every learner is guided differently by AI, based on personal data and AI decisions, students may develop very different perspectives about the same topic. Instead of building a common educational foundation, learning may become fragmented. This could make collaboration and mutual understanding more difficult. For this reason, I believe AI personalization should be balanced with common learning experiences that keep students connected to one another.
What interests (but also intimidates me) about quantum computing is not necessarily the technical side itself, but the possibility that entirely new forms of computational power could fundamentally reshape educational systems in ways we can barely predict yet. While much of the current conversation around generative AI in education focuses on personalization and efficiency, quantum computing raises questions about what happens when data processing, simulation, prediction, and optimization reach levels far beyond what current systems can manage.
I recently attended a keynote on quantum computing (Timothy King), where he discussed the scale of computational power now being embedded into increasingly small and everyday technologies like the iPhone. What struck me the most was not the technical details themselves, but the realization of how quickly technologies that once felt theoretical now feel normalized and infrastructural. It made me think about how easily education can underestimate emerging technologies until they are already reshaping systems around us.
One thing I find very interesting about this is how this could further change personalized learning environments. While personalization has clear benefits, I also share concerns about fragmentation in learning and the potential loss of shared knowledge foundations. If learning becomes increasingly individualized through predictive systems, what does this mean for collaboration, understanding, and what it means to learn together in educational spaces?
Overall, I think quantum computing represents one of those frontier technologies that educators need to pay attention to, even if we do not fully understand its implications.
https://unitary.foundation/posts/2025_quantum-arcade_update/
I’m excited about the future of quantum technology because it feels like a big jump in computing which could greatly impact our lives. Of course, current quantum computers are big machines that only a few organizations can get a hold of, but as with conventional computers in the 50’s and 60’s, I think that we will gradually see the size and cost of these machines decrease.
What does this mean for Education? Well, the technology itself allows for simultaneous calculations of advanced calculations and would be ideal for simulations, better understanding quantum mechanics such as photosynthesis, and complex ideas such as protein folding.
Future quantum computers will allow educators and researchers to visualize complex scenarios in simulation, and Educators will also need to respond to this technology as it becomes more advanced.
Finally, I think that quantum technology will likely not be alone, but rather will co-develop along with increasingly advanced AI technologies and efficient power sources.
What stood out to me in this post is the idea that quantum computing may not transform education through one broad application, but through highly specific algorithms designed for highly specific tasks. That makes me think its most realistic value in education may be less about everyday classroom use and more about large-scale optimization.
For example, quantum computing is already being explored for optimizing traffic lights during rush hour, where many variables interact at the same time. I wonder if a similar logic could be applied to education system design. Instead of only asking how quantum computing could personalize learning for one student, we could ask how it might help institutions optimize the conditions around learning: student-teacher ratios, course sequencing, class scheduling, instructor workload, support services, and resource allocation.
This matters because education is not only a content or personalization problem. It is also a structural design problem. A course or program may fail not because the content is weak, but because the system around it is poorly balanced. There may be too many students per instructor, uneven workload across courses, limited support at key points, or inefficient scheduling that affects engagement and completion.
From this perspective, qubits could help educators test more complex “what if” scenarios before making institutional decisions. For me, the opportunity is not simply quantum-powered learning content, but quantum-supported learning system design.
My interest in quantum computing is not so much from the perspective of education, but rather it’s implications in the general technological world, which will subsequently affect education. Quantum computing has the potential to influence fields such as cybersecurity, artificial intelligence, medicine, and data processing, potentially transforming how societies operate and how information is created and shared. From an educational perspective, these broader societal changes are important because education often adapts in response to technological shifts. New technologies can alter the skills students are expected to develop, the knowledge educators prioritize, and the ways educational systems prepare learners for future careers and social environments. Even if quantum computing is not immediately tied to classroom practice, its potential long-term impact makes it an influential emerging technology worth considering from both a general and educational perspective.