by Asya Trofimova, PhD.
My fascination with artificial intelligence (AI) began in 2017 – not just out of curiosity, but in response to a real challenge we faced at Sanderland School. Many of our students were eager to ask questions and receive feedback outside of scheduled sessions, yet the vast majority of their questions were routine – repeating every term and every year. We realized that responding manually to these repetitive requests was time-consuming and inefficient. So we began searching for a smarter solution – one that could support our teaching efforts without replacing the core human connection.
That experience marked the beginning of our exploration into AI in education.
Today, the need for intelligent, scalable educational solutions is more urgent than ever. Both traditional and online education systems still operate on outdated “one-size-fits-all” models, which fail to reflect the diversity of learners’ skills, pace, and cognitive profiles. AI now offers a powerful and realistic pathway forward – one that brings personalization, flexibility, and inclusion to learning on a global scale.
The Case for Innovation in Education
The education sector is notoriously slow to adapt to innovation. However, change is accelerating. According to recent projections, by 2026, over 400 million learners worldwide will be using AI-powered education tools. By 2030, this number is expected to surpass 700 million. These shifts are being driven by the increasing demand for personalized, accessible, and results-driven learning.
Cognitive science research consistently demonstrates that learners vary widely in how they acquire and process information. Yet most educational systems still rely on standardized curricula and assessments. AI-driven adaptive learning platforms have emerged as a solution to this mismatch. These platforms use machine learning to adjust instruction dynamically based on a student’s real-time performance, learning history, and behavioral data.
According to McKinsey & Company (2024), institutions that integrate adaptive learning technologies see performance improvements of 25-40% in student outcomes, along with measurable gains in engagement and retention.
Beyond Traditional Testing: Intelligent Assessments
The conventional testing system measures a narrow band of academic ability and often fails to assess practical skills, creativity, or problem-solving capacity. AI opens the door to more comprehensive and dynamic assessment models. Through natural language processing (NLP), deep learning, and behavioral analytics, AI can evaluate written responses, track student interaction patterns, and offer feedback on critical thinking.
By 2027, it’s projected that over 60% of secondary and post-secondary institutions in high-income countries will adopt some form of AI-based assessment tools, replacing or supplementing conventional exams (OECD Future of Education Outlook, 2024). These tools will allow for continuous assessment, enabling students to demonstrate mastery at their own pace rather than during high-pressure timed exams.
Personalized Learning, at Scale
AI doesn’t just assess learners, it helps them understand themselves better. With deep learning algorithms analyzing user data, students can receive recommendations about when and how they learn best, what resources fit their style, and how to structure their own learning paths. This self-awareness is critical in building lifelong learning skills.
By 2030, most leading educational platforms are expected to offer AI-generated individual learning paths, tailored not only to academic objectives but also to the student’s emotional and cognitive state. These intelligent systems will track progress, predict challenges, and proactively offer support, thus making personalized education a global norm rather than a luxury.
Supporting Educators, Not Replacing Them
AI is often misunderstood as a threat to teachers, but in reality, it can be a powerful support system. At Sanderland, our experience has shown that AI tools can relieve educators of repetitive administrative tasks and provide rich analytics about student performance, allowing them to focus on mentorship, creativity, and interpersonal learning.
The World Bank estimates that by 2026, educational institutions that implement AI-driven support systems could see a 30–35% increase in educator productivity. Predictive analytics, for example, can identify students at risk of falling behind and recommend personalized interventions, giving teachers the tools they need to act early and effectively.
Group Learning Powered by Algorithms
Collaborative learning is an essential skill for the 21st-century workforce. AI is making it smarter. Using data from academic profiles, surveys, and even social behavior, AI systems can form optimized student groups for peer learning and projects. These algorithm-informed groupings improve engagement, foster diversity in skill sets, and create more inclusive collaboration dynamics.
By 2027, AI-based group formation tools are expected to be used in over 40% of blended and online learning platforms, enhancing peer-to-peer learning outcomes and reducing group conflicts.
The EdTech Boom: Global and Local Trends
The global edtech market is projected to exceed $400 billion by 2030, with AI-driven platforms playing a central role in this growth (Global Market Insights, 2024). Increased demand for skills-based, remote, and flexible education is driving this trend, accelerated by global shifts in work and learning.
Why Educators Must Lead AI Innovation
The success of AI in education depends not just on algorithms, but on people. Specifically, those with deep pedagogical experience. The most impactful edtech solutions will not come from technology alone, but from educators and ‘edupreneurs’ who understand the nuances of learning, the daily realities of the classroom, and the emotional journeys of students.
Great edtech fades into the background. It doesn’t disrupt, it supports. It empowers learners without distracting them. And this kind of seamless innovation can only be created when the people behind it are deeply rooted in education.
Conclusion
Artificial intelligence is already transforming how we teach and learn. AI will drive massive improvements in personalization, assessment, accessibility, and engagement in education. But for this transformation to be truly meaningful, it must be led by educators who understand that learning is more than content delivery, it’s a complex, human-centered experience.
Our vision is clear: an education system where every learner receives exactly what they need, when they need it – powered by AI, guided by educators, and designed with purpose.
