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Emerging tech tools like AI and AR can bridge India’s skills gap—but only if access is equal, infrastructure is strong, and policy keeps up
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Artificial Intelligence (AI) and Augmented Reality (AR) are rapidly transforming how people learn and work worldwide. From adaptive learning software to immersive training simulations, these technologies promise to democratise education and upskill workers at scale. At the same time, they raise concerns about deepening divides—between those with access to cutting-edge tools and those without, between advanced economies and developing ones, and even within classrooms and companies. For India, home to one of the world’s largest and youngest workforces, it is essential to understand both the opportunities and challenges these technologies bring.
AI-driven tools are making learning more personalised, flexible, and accessible. Intelligent tutoring systems can tailor instruction to individual student needs, identifying where learners struggle and providing targeted support. Platforms like Duolingo, for instance, report that users achieve language proficiency 30 percent faster with AI-driven lesson paths. In regions with a paucity of teachers and resources, such innovations can be especially impactful, acting as round-the-clock digital coaches. AI also enhances accessibility by offering real-time translation, speech-to-text, and other assistive functions for learners facing language or physical barriers.
Intelligent tutoring systems can tailor instruction to individual student needs, identifying where learners struggle and providing targeted support.
Meanwhile, AR complements AI by enabling experiential, hands-on learning. It allows users to practice complex skills safely, whether as trainee electricians working on virtual circuit boards or factory workers following step-by-step AR-guided machine maintenance. AR is redefining skill development across industries by reducing real-world risks and making training more scalable and cost-effective.
A central question is whether such advancements will act as equalisers or amplifiers of economic inequality. These technologies can bridge skill gaps by bringing high-quality learning to underserved populations. For example, AI-powered learning tools are helping address teacher shortages in developing regions – an estimated 58 million additional teachers are needed worldwide, a gap technology could help fill.
However, while emerging technologies like AI and AR offer developing nations the potential to overcome educational barriers—enabling students in remote areas to access advanced learning tools and match or surpass developed countries in specific skills—they could also widen inequalities if access remains uneven. Wealthier institutions and individuals may benefit from superior AI tutors and high-speed connectivity, while low-income communities risk receiving lower-quality, tech-based education with minimal human support. Many remain excluded without affordable internet, electricity, and devices, reinforcing existing disparities rather than reducing them.
Such innovations also transform labour markets—shaping job roles, worker productivity, and wage distribution. AI adoption in industry often boosts productivity and output, as machines can automate routine tasks and optimise complex processes. Yet, recent analyses by the International Labour Organization (ILO) revealed that while tech innovations have consistently increased labour productivity, they have also tended to reduce the share of income going to workers.
Global labour’s share of income has declined in recent years, a trend exacerbated by the pandemic and the initial concentration of tech capabilities among only a few firms. If AI is primarily deployed to cut costs—replacing workers with algorithms or robots — the profits may flow to company owners or tech providers, widening income inequality between capital and labour. The lack of policies to manage this transition could further erode worker earnings and bargaining power, exacerbating income inequality.
The risk is a bifurcated labour market. AI and automation tend to redefine the demand for skills rather than eliminate work. They often take over routine and repetitive tasks while increasing the need for complex cognitive and technical skills. This can polarise the job market: high-skill roles that design, programme, or leverage AI become more valuable (and better paid), while some middle and low-skill jobs shrink if they can be largely automated.
The lack of policies to manage this transition could further erode worker earnings and bargaining power, exacerbating income inequality.
There is already evidence of a growing skill premium due to AI. Workers with AI-related or digital skills expertise are commanding higher salaries; one study in India found that employees with AI skills could see pay boosts of over 50 percent, especially in industries like Information Technology (IT) and Research and Development (R&D). A recent employability report revealed that 46 percent of Indian graduates are now deemed employable in AI and Machine-Learning (ML) roles, which is a significant jump in a short period. Yet, only 42.6 percent of Indian graduates are considered employable overall, down from 44.3 percent two years ago—suggesting many are still graduating without the holistic skills needed in an AI-driven economy. Employers increasingly struggle to find candidates with the right mix of technical know-how and soft skills like problem-solving and communication.
While labour market disruption is a feature of any new productivity-enhancing technology, the unprecedented pace of change in AI and AR makes their effects far more rapid and extensive. This demands urgent policy interventions to manage job transitions, reskilling, and wage disparities. Countries proactively investing in broad-based skilling, infrastructure, and inclusive technology access will be better positioned to harness these technologies for economic growth and shared prosperity.
The dynamic demands of the AI-driven economies are rendering traditional, teacher-centred education systems—rooted in theoretical knowledge and memorisation— inadequate. To re-align education for Industry 4.0, restructuring skill-based education that cultivates adaptive, technology-integrated, problem-solving competencies is essential.
Digital competencies are crucial to ensure that labour is proficiently utilising AI tools, enhancing their competitiveness and reducing the risk of being replaced by automation.
Three key competencies stand out: cognitive adaptability, digital competency, and social-emotional skills.
First, as AI and AR systems evolve, workers must develop cognitive adaptability, i.e. the ability to learn and apply new knowledge quickly. It necessitates continuous learning and upskilling through stackable micro-credentials, with a growth-oriented mindset for lifelong learning. Second, digital competencies are crucial to ensure that labour is proficiently utilising AI tools, enhancing their competitiveness and reducing the risk of being replaced by automation. More and more roles, including non-technical ones, now necessitate a better use and understanding of AI-driven decision-making. Therefore, skill-based education must integrate AI literacy, coding, data processing, and digital problem-solving as fundamental competencies across disciplines. Third, while the technology has advantages in pattern recognition and automation, it lacks essential human traits like empathy, creativity, intuition, and ethical judgment. Skill-based education must emphasise developing social-emotional skills to enhance these, particularly critical thinking, teamwork, ethical use of AI, and complex problem-solving among learners. By integrating the three dimensions of cognitive adaptability, digital competency, and social-emotional skills at all levels of education, developing countries like India can leverage technology to close economic inequalities rather than deepen them.
Soumya Bhowmick is a Fellow and Lead, World Economies and Sustainability at the Centre for New Economic Diplomacy (CNED) at the Observer Research Foundation.
Arpan Tulsyan is a Senior Fellow at the Centre for New Economic Diplomacy, Observer Research Foundation.
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Soumya Bhowmick is a Fellow and Lead, World Economies and Sustainability at the Centre for New Economic Diplomacy (CNED) at Observer Research Foundation (ORF). He ...
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Arpan Tulsyan is a Senior Fellow at ORF’s Centre for New Economic Diplomacy (CNED). With 16 years of experience in development research and policy advocacy, Arpan ...
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