As India accelerates the digital transformation of its education system, improving English proficiency remains a critical priority for academic and career readiness. In this interview, Rajeev Ranjan, Editor at Digital Terminal, speaks with Deepak Verma, CEO of EnglishHelper, about how AI-driven adaptive learning, speech-enabled platforms, and curriculum-integrated language solutions are helping bridge learning gaps at scale.
Rajeev: Why do English proficiency outcomes remain uneven in India despite rapid digitisation in education, and where do you see traditional teaching models falling short?
Deepak: India has made meaningful progress in expanding access to English education through digitisation, improved infrastructure, and policy support. Digital classrooms, smart devices, and online content have significantly increased exposure to English across geographies that were previously underserved. Many schools and states are now actively investing in English as a core skill for future readiness, and this has begun to show positive momentum in learner engagement and awareness.
At the same time, outcomes continue to vary because learners enter classrooms with very different starting points, home language environments, and levels of prior exposure. Traditional teaching models were designed for standardised delivery and perform well for a segment of learners, but they are not structured to consistently personalise practice or feedback at scale.
In large classrooms, it becomes challenging to ensure that every learner receives the repetition and reinforcement needed to build fluency across listening, speaking, reading, and writing. Digitisation has addressed access, and the next phase of progress lies in complementing it with personalised support that adapts to individual learning journeys.
Rajeev: How can AI-driven, adaptive learning platforms help address large-scale English literacy challenges in schools and the workforce more effectively than instructor-dependent approaches?
Deepak: AI-driven adaptive learning platforms complement classroom instruction by providing structured, individual practice that is difficult to deliver consistently within limited classroom time. These systems assess learner proficiency and continuously tailor content, pace, and difficulty to individual needs, ensuring that each learner progresses meaningfully. Instant feedback on pronunciation, grammar, and comprehension helps learners correct errors early and build confidence through regular practice.
Rather than replacing instructor-led learning, AI strengthens it by handling routine reinforcement and assessment at scale. This allows teachers and trainers to focus more on discussion, application, and mentoring. In both education and workforce settings, this blended approach has proven effective in supporting large and diverse cohorts while maintaining consistency, quality, and measurable outcomes.
Rajeev: Could you explain how solutions like ReadToMe and the Reading & Comprehension Assistant use AI, speech recognition, and text-to-speech to improve reading fluency and comprehension at scale?
Deepak: Solutions such as ReadToMe and Reading & Comprehension Assistant are designed to strengthen reading outcomes by combining AI, speech recognition, and text-to-speech in a structured and learner-friendly manner. Learners can listen to text being read aloud, adjust speed and accent, and follow along visually to improve word recognition and fluency. Speech recognition enables learners to read aloud and receive immediate, actionable feedback, helping them build accuracy and confidence over time.
These tools also support comprehension by offering explanations, translations, and concept-level breakdowns when learners encounter difficulty. By enabling repeated practice in a non-judgmental environment and aligning closely with academic content, they help institutions scale reading support without increasing instructional load on teachers.
Rajeev: How does embedding English learning into core academic subjects help institutions improve outcomes without adding to curriculum pressure, especially in government school environments?
Deepak: Embedding English learning into core academic subjects builds on existing classroom instruction rather than competing with it. When learners develop comprehension and vocabulary through science, social studies, or vocational content, English becomes a practical learning tool instead of a separate academic requirement. This approach strengthens subject understanding while simultaneously improving language skills.
For government schools, where time and resources are carefully balanced, this integration helps improve outcomes without expanding the timetable. Multimodal support such as audio, visual aids, and guided explanations ensures that learners can access subject content confidently, while teachers benefit from improved engagement and comprehension across the classroom.
Rajeev: With deployments across states and partnerships with IITs and enterprises, what insights has EnglishHelper gained about scaling AI-led language learning in low-connectivity and diverse learning contexts across India?
Deepak: Large-scale deployments have shown that India is ready for AI-led language learning when solutions are designed for real-world conditions. Programs across states demonstrate that mobile-first access, low-bandwidth functionality, and multilingual support significantly improve adoption and sustained usage. Learners respond well when technology aligns with their curriculum and daily learning needs rather than operating as a standalone tool.
The success of such deployments is driven largely by the depth of commitment from state governments and ecosystem partners. Their support is critical across multiple dimensions, including leveraging existing infrastructure, formally endorsing the program, mobilizing stakeholder buy in, and enabling data driven continuous monitoring, performance tracking, and timely course correction.
Another important insight is the value of trust and transparency. Institutions show strong preference for explainable, reliable AI systems that deliver consistent feedback and safe learning experiences. When combined with teacher involvement and clear outcome measurement, this approach enables AI-led language learning to scale effectively across diverse regions, connectivity levels, and learner profiles.
𝐒𝐭𝐚𝐲 𝐢𝐧𝐟𝐨𝐫𝐦𝐞𝐝 𝐰𝐢𝐭𝐡 𝐨𝐮𝐫 𝐥𝐚𝐭𝐞𝐬𝐭 𝐮𝐩𝐝𝐚𝐭𝐞𝐬 𝐛𝐲 𝐣𝐨𝐢𝐧𝐢𝐧𝐠 𝐭𝐡𝐞 WhatsApp Channel now! 👈📲
𝑭𝒐𝒍𝒍𝒐𝒘 𝑶𝒖𝒓 𝑺𝒐𝒄𝒊𝒂𝒍 𝑴𝒆𝒅𝒊𝒂 𝑷𝒂𝒈𝒆𝐬 👉 Facebook, LinkedIn, Twitter, Instagram
