Every Teacher’s Ally: Harnessing AI for Equity and Excellence

Indian education continues to grapple with deep, persistent challenges: large class sizes, acute teacher shortages (especially in rural-remote areas), heavy administrative burden o and widespread linguistic diversity. Recently, a Parliamentary Standing Committee report noted that 1 million school teacher posts are vacant across the Samagra Shiksha Abhiyan (SSA) funded schools, of which around 750,000 vacancies are at elementary and primary levels. The situation is likely to be even worse if all state schools are taken into account as well. Karnataka, for instance, reported 55,000 vacancies in teacher posts, which are likely to increase to nearly 100,000 after more teachers retire in April 2026. Compounding the issue, data from UDISE+ reveal that nearly 7 percent of government schools operate with only a single teacher. In some states like Jharkhand, 30.9 percent of primary schools are single-teacher institutions, where several schools enrol more than 50 students across multiple grades.

Meanwhile, teachers spend a lot of their time in non-teaching activities such as paperwork, data upload, government programmes, and election duties, resulting in lost teaching hours. Mid-day meal-related activities alone account for an estimated 2.5 to 3 hours of teachers’ time each day. Overall, teachers spend 33.9 percent of their time on core activities (preparing lesson plans, remedial teaching, assessing learners, test correction, and sports or co-curricular activities) and 21.6 percent of their time on actual teaching. The remaining 40-45 percent was consumed by non-teaching activities.

AI tools can reduce administrative load, help manage multi-grade teaching, tailor student feedback, support professional growth, and preserve teacher autonomy.

In such stretched settings, which are not likely to resolve soon, the critical question for educational excellence is: how can we relieve the burden of teachers, save their time, maintain instructional quality, and support learning equity? One strategic lever is artificial intelligence (AI), which, if thoughtfully designed, has the potential to become a teacher’s ally. AI tools can reduce administrative load, help manage multi-grade teaching, tailor student feedback, support professional growth, and preserve teacher autonomy.

Why AI, and How?

AI is integral to India’s education policy vision. The National Education Policy (NEP) 2020 explicitly promotes technology integration and digital learning. Initiatives such as NIPUN Bharat, which target foundational learning, have begun to leverage AI for diagnostics and remedial support at scale. State governments are actively partnering with tech providers (IBM, Intel, among others) to upskill teachers. The 2025 Union Budget allocated INR 500 crore to an AI Centre of Excellence for Education, signifying a long-term, system-wide agenda.

Studies also report growing digital capabilities of teachers in India. States like Kerala and Maharashtra lead with 87 and 75 percent, respectively, of teachers trained in ICT-based pedagogy. Although states like Bihar, Jharkhand, and Odisha lag behind with less than 40 percent of teachers receiving adequate digital training, studies from tribal regions also reveal that younger teachers have strong competencies in using multimedia and digital platforms. Pre-service training should, therefore, offer more targeted upskilling in areas with comparatively weaker capacities, like in strategic or reflective integration of AI tools for collaborative learning facilitation and skills in technical troubleshooting or security.

Unlike piecemeal administrative reforms or temporary, contractual outsourcing, AI offers scalable, adaptive tools that support teachers holistically, automating routine tasks, enhancing student engagement and personalising support for each classroom context.

Thus, as AI emerges as a clear policy priority, along with growing basic competencies among teachers who enter the pre-service training, it gets uniquely positioned to address the above-mentioned intertwined challenges. Unlike piecemeal administrative reforms or temporary, contractual outsourcing, AI offers scalable, adaptive tools that support teachers holistically, automating routine tasks, enhancing student engagement and personalising support for each classroom context.

Several initiatives already illustrate this potential:

• Shiksha Copilot, launched in Karnataka, has shown promising results. Teachers report it has significantly reduced their lesson planning time, cutting it from around 40 minutes to 10 minutes, effectively saving up to 70-80 percent of their time on this task alone.
• Sahayak is an AI-powered teaching assistant specifically designed to support teachers in multi-grade classrooms. It can read and understand curriculum documents, generate differentiated worksheets for various grade levels, create engaging stories, and respond in multiple languages such as Hindi, Marathi, and English, aiding teachers in managing diverse learning needs efficiently.
• Teachmint is an Indian platform that integrates AI-powered classroom management features, including automatic attendance, homework tracking, and student analytics. It supports multiple regional languages and is being widely used in budget schools and rural areas due to its mobile-first approach, helping teachers manage classrooms more efficiently.
• PrepAI assists educators in creating assessments aligned with student levels, generates individualised feedback, and maintains a consistent evaluation process. It reduces grading time, allowing teachers to focus more on personalised instruction and student engagement. While these are relatively new tools, their impact is already being felt across Indian classrooms.

While these tools are relatively new, their impact is already tangible. Teachers report that AI-assisted lesson planning, assessment, and classroom management save significant time, which can be redirected toward direct teaching, mentorship, and student engagement. A McKinsey study postulates that overall, technology can help save 20-30 percent of teachers’ time, which can instead be devoted to classroom instruction.

Source: McKinsey, 2020

Building on these developments, the challenge going forward is how to scale and institutionalise AI as a teacher-centric support system. Policy frameworks, therefore, must move beyond pilot projects to create sustainable, ethical, and context-sensitive AI adoption strategies. This involves aligning AI tools with curriculum and assessment standards, strengthening teacher digital capacities in weaker regions, ensuring multilingual and multi-grade adaptability, and embedding safeguards for data privacy and algorithmic transparency. By doing so, AI can transition from a promising experiment to a systemic enabler, freeing teachers to focus on instruction, mentoring, and equitable learning outcomes. The next section makes some key recommendations to this end.

Teachers report that AI-assisted lesson planning, assessment, and classroom management save significant time, which can be redirected toward direct teaching, mentorship, and student engagement.

Policy Recommendations for Making AI Every Teacher’s Ally

To translate AI’s potential into tangible classroom impact, policymakers must implement decisive, teacher-centred strategies. The following recommendations will provide a roadmap to harness AI for reducing teacher workload, strengthening instructional quality, and promoting equitable learning outcomes across India.

1. Policies should prioritise AI tools that support teachers, taking into account classroom realities, multi-grade settings, and linguistic diversity. States should create clear approval frameworks with clearly defined indicators and outcomes to guide schools in selecting AI solutions that are scalable, effective, and aligned to local educational contexts. A centralised monitoring and reporting system managed by the State Council of Educational Research and Training (SCERTs) to track pilot performance in real time, collecting quantitative data (usage stats) and recording qualitative feedback (teacher/student experiences), would be helpful to ensure the credibility of AI systems.
2. Targeted upskilling of teachers in areas such as AI-assisted lesson planning, assessment design, facilitation of collaborative learning, cybersecurity and technical troubleshooting is crucial. Pre-service and in-service training programs should include structured modules on critical engagement with AI and its responsible use.
3. Tools like Sahayak and Teachmint demonstrate that adaptive AI platforms can address student diversity effectively. Policies should incentivise the development of adaptive and multilingual AI solutions that allow teachers to personalise learning for every student, including in rural and tribal schools.
4. Policies should streamline administrative tasks through AI to reduce non-teaching burdens. For example, with real-time digital registers for attendance tracking, automated report generation for school management/state authorities and parental communication, digital maintenance of mid-day meal records, swachhta reports, and survey submissions, reducing paperwork during campaigns or inspections.
5. Alongside AI adoption, it is crucial to establish mandatory ethical standards, privacy safeguards, and accountability frameworks for all AI tools used in schools. AI tools should have transparent algorithms and strict safeguards to protect student and teacher data.
6. Although pilot programmes are increasing, they should be accompanied by rigorous monitoring and evaluation to assess AI’s impact on teaching quality, student outcomes, and equity. These lessons from pilots should be used to scale successful models nationally, while iterating or discontinuing ineffective approaches.
7. Governments should move beyond procurement-based partnerships to dynamic co-creation and accountability-based partnership models with tech companies, edtech startups, and NGOs. Policymakers, teachers, and developers should jointly iterate solutions in schools and prioritise cost-effective, high-impact solutions, particularly for resource-constrained schools. An institutionalised channel for teacher feedback should also be created so that solutions remain accountable and evolve with changing classroom realities and pedagogical shifts, strengthening teacher agency.

Scalable, adaptive, and ethically implemented AI can help keep education human-centred in the digital age, while strengthening equity and fostering excellence across India’s classrooms. By freeing up time and enhancing capacity, it ensures that every teacher can focus on what matters most—teaching and mentoring.

Arpan Tulsyan is a Senior Fellow at ORF’s Centre for New Economic Diplomacy (CNED).

• Education
• India
• ai for education
• ai for teachers
• india education policy
• indian education system
• national education policy 2020
• nep 2020
• nipun bharat initiative

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