Artificial Intelligence Ecosystem in India: Policy and Roadmap – Economic Survey 2025-26 Analysis
Artificial Intelligence represents a transformative technology with profound implications for economic growth, productivity, and the nature of work. The Economic Survey 2025-26 dedicates a chapter to the evolution of the AI ecosystem in India, examining AI's place in the economic context, a development-oriented approach, human capital requirements, and safety considerations. This article explores India's AI strategy and the roadmap for building a thriving AI ecosystem.
AI in India's Economic Context
The Economic Survey 2025-26 situates AI within India's broader economic development context. Unlike advanced economies that approach AI primarily as a productivity enhancer, India must consider AI's role in job creation, skill development, and inclusive growth.
India's large young population entering the workforce annually represents both an opportunity and a challenge for AI adoption. On one hand, these workers can leverage AI tools to enhance productivity. On the other hand, AI-driven automation could displace certain types of jobs before alternative employment is created.
The survey discusses highly leveraged AI-infrastructure investment that has exposed business models dependent on optimistic timelines and narrow customer concentration. This caution about AI investment sustainability is relevant as India navigates its own AI development path.
India's approach must balance enthusiasm for AI's potential with pragmatism about its current limitations and risks. The technology offers genuine productivity benefits in many applications but is neither a solution to all problems nor without challenges that require management.
A Development-Oriented Approach to AI
The Economic Survey 2025-26 articulates a development-oriented approach to AI that differs from approaches in countries at different development stages. This approach emphasizes using AI to address India-specific challenges while building domestic capabilities.
AI applications in agriculture can help farmers with crop selection, pest identification, and yield prediction. Given agriculture's importance in India's economy and employment, AI that benefits farmers addresses development priorities directly.
Healthcare AI applications can extend specialist medical knowledge to underserved areas. Diagnostic AI can assist primary health workers in identifying conditions that require referral, addressing the shortage of specialists in rural areas.
Education AI can personalise learning for students at different levels, addressing the challenge of classroom teaching that cannot meet individual needs. Language AI enables content delivery in vernacular languages, expanding access.
Government services can use AI to improve delivery efficiency and reduce corruption. AI-enabled document processing, fraud detection, and chatbots for citizen queries are already being deployed across government departments.
Human Capital for AI
Building an AI ecosystem requires human capital spanning multiple roles. Researchers who advance AI capabilities, engineers who build AI applications, and users who deploy AI tools all need appropriate skills.
India produces large numbers of engineering and science graduates, providing a potential talent pool for AI. However, AI-specific skills in machine learning, deep learning, and related areas require additional training beyond standard curricula.
The survey's discussion of human capital development applies to AI. Upgrading curricula to include AI fundamentals, creating specialised AI programs, and enabling continuous learning for working professionals are all necessary.
Faculty development is a critical bottleneck. Universities and colleges need faculty who can teach AI effectively, but industry often offers more attractive compensation for AI talent. Building faculty capacity through training programmes and incentives is essential.
Beyond technical skills, AI deployment requires understanding of domain applications. An AI solution for healthcare needs healthcare domain knowledge, not just programming skills. Interdisciplinary training that combines AI with domain expertise is increasingly valuable.
AI Safety and Governance
The Economic Survey 2025-26 discusses AI safety and risks as an important dimension of AI policy. As AI systems become more capable and widely deployed, ensuring their safe and beneficial operation becomes critical.
AI systems can embed and amplify biases present in training data. An AI hiring tool trained on historically biased hiring decisions can perpetuate discrimination. Governance frameworks must address bias identification and mitigation.
Transparency and explainability are important for AI systems making consequential decisions. When AI is used for credit decisions, medical diagnoses, or legal judgments, affected individuals have legitimate interests in understanding how decisions are made.
Privacy implications of AI that processes personal data require attention. AI systems that analyse faces, voices, or behavior patterns raise privacy concerns that regulation must address.
Security risks from AI include misuse for surveillance, manipulation, and cyberattacks. Governance frameworks must prevent harmful applications while enabling beneficial ones.
India's approach to AI governance is still evolving, with principles-based guidelines rather than prescriptive regulations. This allows flexibility as the technology develops while providing some guardrails.
A Phased Roadmap for India's AI Future
The Economic Survey 2025-26 outlines a phased roadmap for India's AI development. This roadmap sequences investments and initiatives to build capabilities progressively.
The first phase focuses on building foundational capabilities. This includes developing AI talent, creating research capacity, establishing computing infrastructure, and generating datasets for Indian applications.
The second phase emphasizes application development across priority sectors. Agriculture, healthcare, education, and government services offer opportunities for AI deployment that addresses development challenges while generating learning.
The third phase involves developing frontier AI capabilities and becoming a global AI player. This longer-term ambition requires the foundations built in earlier phases.
Throughout these phases, governance frameworks must evolve to address emerging challenges while enabling innovation. India's participation in global AI governance discussions positions it to shape international norms.
AI Infrastructure: Compute and Data
AI development requires computing infrastructure for training and running AI models. Training large AI models requires substantial compute capacity, typically using specialized hardware like GPUs.
India is building AI compute infrastructure through initiatives like the India AI Mission. Access to compute resources enables researchers and startups to develop AI applications without massive upfront investment.
Data is the fuel for AI systems. Indian language data, in particular, is essential for developing AI that serves non-English speakers. Curating and making available datasets for Indian applications supports ecosystem development.
The digital public infrastructure approach that India pioneered with Aadhaar, UPI, and other platforms can extend to AI infrastructure. Shared compute resources, datasets, and AI services can democratise access.
AI and Employment: The Critical Question
The employment implications of AI are perhaps the most debated aspect of the technology. Optimists argue AI will create new jobs while automating routine tasks. Pessimists worry about mass displacement before new jobs emerge.
India's situation is complex. Many jobs involve tasks that AI can assist rather than replace entirely. A data entry operator using AI for form recognition can process more documents, potentially creating more value without losing employment.
New job categories are emerging around AI. Data labeling, AI training, prompt engineering, and AI auditing create employment that did not exist before. India's English-speaking, technically educated workforce is well-positioned for some of these roles.
The transition period is critical. Workers displaced by AI need pathways to new employment through reskilling. Social safety nets must support those who cannot immediately transition. The pace of AI deployment should consider absorption capacity.
The Economic Survey 2025-26's emphasis on skills development and inclusive growth provides the framework for managing AI's employment impacts.
Startup Ecosystem and Innovation
India's AI startup ecosystem has grown rapidly, with companies addressing diverse applications from agriculture to healthcare to financial services. Venture capital funding for AI startups has increased, though global funding uncertainties affect all technology sectors.
Some Indian AI startups have achieved global recognition, demonstrating that Indian entrepreneurs can compete in this space. Success stories encourage more entrants and attract talent to the sector.
Corporate AI adoption creates demand for solutions that startups can provide. Large enterprises increasingly use AI for customer service, process automation, and decision support, creating markets for AI solution providers.
The government's role includes creating enabling conditions through policy, funding research and development, and being an early adopter of AI solutions that can then scale to private sector applications.
Global AI Landscape and India's Position
The global AI landscape is characterised by intense competition, particularly between the United States and China. These countries lead in AI research, investment, and deployment, with significant strategic implications.
India occupies a distinctive position. It is neither a current AI leader nor a complete laggard. Its large talent pool, growing digital economy, and development-oriented approach offer differentiated strengths.
Partnerships with global AI leaders can accelerate India's AI development. Technology collaborations, research partnerships, and investment relationships bring knowledge and resources. The India-EU free trade agreement discussed in the survey potentially facilitates technology integration.
Strategic autonomy considerations apply to AI as to other critical technologies. Over-dependence on foreign AI systems for critical applications creates vulnerabilities. Building domestic capabilities in key areas ensures control over strategic technology.
UPSC Relevance: Artificial Intelligence
AI is increasingly important for UPSC:
- GS-III: Science and Technology, economic development
- Ethics: AI ethics, governance, impact on society
- Essay: Technology and development, future of work
- Current Affairs: Policy developments, applications
Practice MCQs on Artificial Intelligence - Economic Survey 2025-26
Q1. The Economic Survey 2025-26 emphasizes which approach to AI for India:
(a) Replicating US approach
(b) Development-oriented approach
(c) Limiting AI adoption
(d) Only research focus
Answer: (b) Development-oriented approach addressing India-specific challenges
Q2. Human capital for AI includes:
(a) Only PhDs in computer science
(b) Researchers, engineers, and domain experts
(c) Only data scientists
(d) Only policy makers
Answer: (b) Researchers, engineers, and domain experts with AI skills
Q3. AI safety concerns mentioned in Economic Survey 2025-26 include:
(a) Only technical failures
(b) Bias, transparency, privacy, and security
(c) Only energy consumption
(d) Only cost overruns
Answer: (b) Bias, transparency, privacy, and security
Q4. India's AI roadmap is structured as:
(a) A single-phase rapid deployment
(b) A phased approach building capabilities progressively
(c) Complete import dependence
(d) Research only, no deployment
Answer: (b) A phased approach building capabilities progressively
Q5. The relationship between AI and employment in India requires:
(a) Ignoring transition challenges
(b) Banning AI to protect jobs
(c) Reskilling and managing transition pace
(d) Only creating research jobs
Answer: (c) Reskilling workers and managing the transition pace
Conclusion
The Economic Survey 2025-26's chapter on AI ecosystem evolution provides a comprehensive framework for India's AI journey. The development-oriented approach emphasizes using AI to address Indian challenges while building domestic capabilities. Human capital development, safety governance, and phased roadmap implementation are all essential elements. The challenge is realising AI's potential while managing risks to employment, privacy, and equity. For UPSC aspirants, understanding AI policy from India's unique development perspective, rather than simply applying frameworks from advanced economies, is essential for nuanced examination answers.