Over the past two decades, EdTech has expanded access and introduced powerful tools into the learning process. From smartboards to live classes, MOOCs to adaptive platforms—each wave built on what was possible with the technology of its time. These innovations improved reach, added new formats, and supported teachers. But they didn’t fundamentally transform the learning experience for every child, nor did they close the loop between instruction and mastery.
Generative AI (GenAI) marks a shift with fundamentally different capabilities. For the first time, we have a technology that can simulate human-like interaction, respond in real-time, and create hyper-personalised learning journeys at scale. This isn’t just about convenience or better content—it’s about reimagining what high-quality teaching and learning can look like for every child, every day.
To understand this shift, it helps to recall what meaningful technology disruption in education has always aimed to do:
1. Break the boundaries of access: Taking great teaching beyond the limits of a single classroom or teacher.
2. Drive pedagogical innovation: Teaching at the right level, providing timely feedback, and adapting to how each student learns best.
In the last 15 years, EdTech platforms largely delivered on access. Smartboards made classrooms more visual and multimedia-rich. MOOCs like Coursera and edX opened up Ivy League classrooms. YouTube made every concept explainable on demand. Live classes and recorded lectures scaled effective teachers beyond cities.
On the pedagogy front, adaptive platforms tried to personalise practice and assessment. They adjusted questions based on student responses and offered data to teachers. But these platforms had limitations. They didn’t step in to teach (like a teacher) when a student was confused. They required teachers to interpret data and act. The feedback loop was longer than ideal, and the student experience remained mostly passive.
GenAI has the potential to close that loop as it can provide:
1. Conversational interfaces that move beyond rigid screens.
2. Real-time feedback that adapts in the middle of a lesson.
3. On-demand generation of content—text, audio, and even video—that meets a student’s need in the moment.
4. Most importantly, personalisation that doesn’t require more teacher time or expensive tutoring infrastructure.
Let’s explore what this could mean—inside and outside the classroom.
Most classrooms today are focused on syllabus delivery. A typical teacher might spend 3–4 lectures covering a chapter, followed by a unit test every few chapters. The results of the test rarely change what happens next. There’s limited opportunity to reflect, intervene, or ensure mastery. As a result, gaps widen quietly. Even high-performing students might carry forward small misconceptions. That’s why tuitions remain essential for most families: in-school learning doesn’t guarantee understanding for every child.
With GenAI, we can change that.
After every class, GenAI tools can help teachers identify which students are struggling and on which specific concepts. Platforms like Acadally are already enabling teachers to run quick, formative checks after each lesson and get AI-suggested insights to adjust instruction or provide remedial classes. Parents and tuition teachers can also be looped in with personalised summaries, making the support system around a child much more targeted.
Teachers still spend hours compiling reports and marking tests. GenAI can change this. With a few prompts—text or voice—it can generate individual performance reports, detect conceptual misunderstandings, and even highlight the underlying issues. The burden of assessment reduces dramatically, giving teachers time back for teaching. Learning platforms that combine the power of reporting will take away the burden from teachers and make outcome assessments more meaningful for students, parents and teachers.
With the admin burden lowered, GenAI can become a true co-pilot. Teachers are using tools like MagicSchool to create lesson plans, in-class experiments, differentiated worksheets, or group projects—all in minutes. This isn’t about replacing the teacher’s creativity, but accelerating it.
Most high-quality digital content has historically been in English or a few major Indian languages. Translation has been an expensive and time-consuming effort. GenAI can break this barrier by instantly translating and contextualising material into regional languages, with local references. That means a classroom in Gwalior or Guwahati could have access to the same quality of learning material as a school in Gurgaon.
Supplemental learning—tuition, test prep, edtech platforms—has become essential. But the ecosystem is stretched at both ends.
Recorded videos were meant to scale content, but they often become the “third thing” on a child’s schedule, after school and tuition, and hence remain underused. On the other hand, 1:1 tutoring provides true personalisation, but faces two big constraints in India: unsustainable unit economics (low gross margins, high CACs) and limited supply of high-quality teachers at scale. Some companies tried to address this by offering structured lessons that average teachers could deliver, but quality suffered.
GenAI can unlock a new middle path—scalable, affordable, and personal.
Platforms like Arivihan are experimenting with AI tutors that not only explain concepts but also respond to student queries in real time—offering tailored follow-ups, including custom-generated video explanations. By replicating the dynamics of a human tutor, these solutions create the feel of 1:1 instruction without the high operational cost. Building this experience, however, requires deep training data, strong academic scaffolding, and expert moderation to ensure quality. Over time, these AI teachers can either stand alone or work alongside human teachers—acting as intelligent, always-available assistants.
Whether in a 1:1 or group setting, GenAI can support teachers by answering doubts, providing feedback, and conducting assessments—freeing up time for teachers to focus on explanation and connection. Platforms like Codeyoung are enabling this model by integrating real-time feedback tools and AI-generated content into live classes. This creates a hybrid approach that retains the strengths of personalised instruction while improving affordability and scale.
Instead of sitting through 40-minute generic videos, GenAI enables learners to build short, interactive, and adaptive learning journeys—based on attention spans, prior performance, and preferred formats. Whether it's revision notes, flashcards, concept explainers, or mock tests, students can now generate just-in-time content tailored to their needs. Emerging tools like SigIQ, SuperKalaam, and ZuAI are building solutions that allow students to engage in self-learning that is more active and outcome-driven.
Conversational AI is pushing self-learning even further. Khanmigo, built by Khan Academy, helps students reason through problems step-by-step and offers feedback mid-process—simulating a tutor’s thought-partner role. Meanwhile, apps like Stimuler let students practise spoken English through realistic conversations with AI bots. These bots not only correct errors but also give feedback on pronunciation, tone, and fluency—helping students improve without the fear or pressure of a classroom setting.
Personalised learning has historically been expensive. Whether through 1:1 tutoring, content ops, or dedicated mentors, it came with high variable costs. That’s why most quality offerings were designed for premium markets.
GenAI shifts this equation:
1. Fixed costs (platform, model training, curriculum design) still exist.
2. But variable costs (content production, delivery, student support) drop sharply.
This opens up new possibilities for reaching India’s broader market, where families might only be able to pay ₹500–₹1,000/month.
No matter how powerful the technology, success in education depends on how it's delivered. The best ideas fail if they don’t reach the learner in a form that is trusted, timely, and affordable.
This is where GTM and distribution will separate winners from the rest.
1. A GenAI-powered tutor can’t succeed if parents don’t see its value compared to a ₹2,000/month local tuition teacher.
2. A brilliant classroom co-pilot needs deep teacher onboarding and support.
3. A regional-first strategy needs local influencers and language support, not just a product.
We’ve seen this in past waves, too: those who cracked distribution, whether through school tie-ups, teacher networks, or organic parent referrals, outlasted those who bet only on tech.
The lesson is clear: build for trust, distribute for scale. That’s what will make GenAI truly matter. As we’ve written before at Enzia, innovation must translate into outcomes. Businesses that deliver on learning outcomes—faster mastery, deeper understanding, or better performance—build trust. That trust drives organic growth, retention, and defensibility. GenAI makes it easier to measure and demonstrate outcomes in real time. The winners will be those who make this feedback loop central to their product and GTM motion.
In all of this, the role of the teacher doesn’t diminish—it evolves.
Yes, GenAI can generate reports, create personalised lessons, and simulate empathy in conversation. But real learning is human:
1. Motivation and self-discipline don’t come from a chatbot.
2. Children need routines, boundaries, and feedback—delivered with care and conviction.
3. Peer interaction, debate, and collaboration—these are all deeply human and social.
In fact, GenAI will succeed when it enables teachers, not replaces them. By taking away the repetitive and manual, it can give teachers the tools to be better guides, mentors, and facilitators of learning.
Generative AI is not just a better tool—it’s a new paradigm. For the first time, we can combine scale, personalisation, and quality in ways that were previously impossible. But great EdTech businesses will still need to get the fundamentals right.
Innovation needs to meet GTM. Personalisation needs to deliver outcomes. And technology needs to amplify—not replace—the teacher.
If we get this right, the next decade won’t just be about better learning apps. It will be about building a learning ecosystem that works for every child, not just the top 10%.
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