The artificial intelligence (AI) landscape has been significantly transformed since the emergence of generative AI in 2022, marking a shift from incremental technological progress to the rapid and widespread diffusion of new capabilities. Unlike earlier waves of digital innovation, AI adoption has been exceptionally swift, with continuous improvements in models and applications driving its integration across sectors. While concerns around large-scale job displacement persist, AI is increasingly being viewed as a productivity-enhancing tool with the potential to reshape business processes and decision-making. At the same time, there is a growing focus on the use of AI for social good, particularly in sectors such as healthcare, agriculture, education and public service delivery.
Within this evolving landscape, India is emerging both as a significant adopter and an increasingly influential player in shaping the direction of AI. On the adoption side, the country has seen rapid uptake across individuals, enterprises and government. At the same time, India is positioning itself as a key participant in global AI development through initiatives such as the IndiaAI Mission and international engagements like the India AI Impact Summit. The policy approach has moved from an initial focus on ecosystem building towards a more comprehensive framework that integrates innovation, regulation and global cooperation.
India’s AI adoption trajectory
AI adoption in India has expanded rapidly across individual users, firms and the government. At the level of individual users, India has emerged as one of the largest and fastest-growing markets for generative AI, driven by widespread smartphone penetration and affordable data tariffs. It ranks among the top five countries globally in the use of tools such as ChatGPT, particularly for coding, content creation, education support and professional productivity, although usage remains concentrated in urban and higher-skilled segments. At the enterprise level, adoption has moved beyond pilot projects to large-scale deployments. According to recent industry reports, 80-90 per cent of Indian firms are now using AI in some form, with a rising share integrating it into core operations such as customer engagement, supply chain optimisation, fraud detection and decision analytics. However, as in the case of individual users, adoption remains uneven across firm size and sectors, with small and medium enterprises still facing constraints related to cost, skills and infrastructure. The government, across the central, state and local levels, represents a major stakeholder, both as a user and as an enabler of AI. Public investment by the central government is being directed towards shared compute infrastructure, open data sets and skilling, while union ministries, state governments and local bodies are increasingly deploying AI in governance and public service delivery in areas such as welfare targeting, agriculture advisories, health diagnostics and urban management.
Policy impetus by the government
With a structured mix of policy support, public infrastructure creation and regulatory oversight, the government aims to accelerate the adoption of AI while managing associated risks. A key milestone was the launch of the IndiaAI Mission in March 2024, with an outlay of around Rs 100 billion to build foundational capabilities such as high-end compute infrastructure, curated data sets, application development support and skilling initiatives. The mission reflects a broader approach of treating AI as part of India’s digital public infrastructure, similar to Aadhaar and Unified Payments Interface. Significant progress has been made under the mission, including the onboarding of more than 38,000 graphics processing units (GPUs) for a shared compute facility accessible to start-ups and academic institutions at subsidised rates, the shortlisting of multiple teams for the development of indigenous foundational large language models and the approval of several India-specific AI applications across sectors.
The government also hosted the India AI Impact Summit in February 2026, which brought together multiple countries and international organisations to deliberate on AI governance and collaboration. The summit led to outcomes such as guidance on responsible AI adoption and initiatives aimed at promoting inclusive and trusted AI ecosystems. At the same time, continued investments in digital infrastructure, data sets and skilling are supporting wider adoption of AI across sectors. The government is also taking policy and regulatory measures to improve transparency, accountability and risk mitigation in the deployment of AI systems, particularly generative AI.
Emergence of India-specific AI use cases
AI applications in India are increasingly shaped by country-specific factors such as linguistic diversity, variations in access to services and the structure of the economy, rather than relying solely on generic use cases. For instance, the government has rolled out the AI-powered platform “BHASHINI” to enable multilingual access to digital services by developing AI models for speech recognition, translation and text processing across a wide range of Indian languages. In agriculture, AI is being used for crop disease detection, yield prediction and precision farming, supported by both government and private sector initiatives. Healthcare is another major area of application, where AI-driven diagnostics, telemedicine platforms and predictive analytics are improving access to care, especially in rural areas, while also reducing the burden on public health systems. Education is witnessing the integration of AI through adaptive learning platforms, virtual assistants and AI-enabled teaching aids in schools. In financial services, including banking and fintech, AI is being used for fraud detection, credit scoring, customer service chatbots and risk assessment. In manufacturing, AI is supporting the transition towards smart factories through predictive maintenance, quality control and automation. Public administration and governance have also emerged as important areas of application, with states deploying AI for tasks such as pension verification using facial recognition, crime analytics through data integration and predictive policing, and the use of large-scale data platforms that improve the targeting of welfare schemes and service delivery. Retail and consumer sectors are using AI for demand forecasting, inventory management and personalised marketing.
Measures to encourage ethical and responsible AI use
As AI’s footprint expands across sectors, the ethical and responsible use of the technology has become increasingly important to ensure that its benefits are widely shared across all sections of society and that associated risks are effectively managed. Without appropriate safeguards, AI systems may reinforce existing biases in data, generate opaque outcomes and compromise individual privacy. AI-driven credit scoring models, for instance, may disadvantage certain groups if historical data reflects unequal access to finance. In healthcare, AI-based diagnostic tools must ensure reliability and accountability, as errors can directly affect patient outcomes.
In India, there has been a growing policy focus on embedding ethical considerations within the AI ecosystem. Regulatory developments such as the Digital Personal Data Protection Act, 2023 have strengthened the legal framework around data privacy and consent, which is central to responsible AI. However, going forward, there is a need for clearer and more enforceable standards on issues such as algorithmic accountability, bias audits and explainability, particularly for high-impact applications.
Key issues and challenges
Despite a strong policy push, the adoption and diffusion of AI in India face a range of structural, institutional and socio-economic challenges. A key constraint is the absence of large-scale indigenous foundational models comparable to those developed by global technology firms, even as the country focuses on application-led growth. There are also gaps in infrastructure, particularly the limited availability of high-end computing power and energy-intensive data centres, which remain concentrated among a few large players, which is restricting broader participation by start-ups and academic institutions despite efforts under the IndiaAI Mission. In addition, many firms face funding constraints and uncertain returns on investment, as the costs of adopting and scaling AI technologies are high while measurable productivity gains often take time to materialise. Another important issue is the uneven availability of high quality data, which is central to training robust AI systems. The country also relies heavily on imported hardware such as advanced semiconductors and GPUs, making it vulnerable to global supply chain disruptions and strategic restrictions. There is also a shortage of advanced AI researchers and domain specialists.
Outlook
AI is set to play a dominant role in shaping the technological landscape in the coming years. The global AI market, estimated at around $375 billion in 2026, is growing at an annual rate of 25-30 per cent and is projected to exceed $2 trillion by the early 2030s. In India, AI adoption is not only expanding in scale but is also becoming more closely aligned with the country’s specific economic and administrative requirements. This creates significant opportunities for a wide range of stakeholders, including firms seeking productivity gains, start-ups driving innovation, workers upgrading skills, and governments improving service delivery and policy design.
While India has made notable progress in articulating an AI strategy, the path to widespread and equitable adoption will depend on addressing deep-rooted constraints related to data availability and quality, infrastructure gaps, skill shortages, regulatory clarity and integration with global technology ecosystems.
