AI Ecosystem in India – Economic Survey 2025-26 Analysis

       Artificial Intelligence (AI) has emerged as one of the most transformative technologies of the 21st century. The Economic Survey 2025–26 devotes a full chapter to AI, reflecting its growing importance in shaping economic growth, employment patterns, and global power structures.

Unlike earlier discussions that focused on potential, the current survey highlights that AI is now actively being adopted across industries worldwide. This shift makes it imperative for India to design a strategy that aligns with its unique economic realities, demographic structure, and resource constraints.

AI in the Global Economic Context

     The global AI landscape is witnessing rapid expansion, with a large number of firms integrating AI into their business processes. However, this adoption is uneven. While usage is widespread, the development of advanced AI systems remains concentrated in a few countries and firms due to high requirements of capital, computing power, and specialised talent.

      At the same time, early evidence suggests that fears of immediate large-scale job losses may be overstated. In the short term, AI is largely complementing human labour rather than replacing it. However, there are signs of structural changes, such as a decline in the responsiveness of employment to economic growth, indicating that long-term labour market impacts remain uncertain.

Key Challenges in the AI Ecosystem

1. Concentration of AI Capabilities

• The ability to build and train advanced AI models is restricted to a handful of global firms. 

• This creates a divide where most countries may remain users rather than creators of AI technologies, limiting their influence over standards and innovation.

2. Resource Constraints

• AI development is highly resource-intensive, requiring large amounts of electricity, water, and advanced hardware. 

• For a country like India, which already faces constraints in energy and infrastructure, indiscriminate scaling of AI infrastructure may not be sustainable.

3. Hardware and Supply Chain Dependence

• The global supply of critical components like GPUs is limited and concentrated. 

• Even with sufficient financial resources, access to hardware can become a bottleneck, slowing down AI expansion in India.

4. Impact on Employment

• AI adoption increases productivity but may also reduce the demand for certain categories of labour, especially in low-value service sectors. This creates a policy dilemma between maximising efficiency and ensuring employment generation.

5. Risks to India’s IT Sector

• India’s traditional advantage as a global IT service provider is under threat. As AI automates routine tasks, there is a risk that outsourcing demand may decline unless the sector evolves towards higher-value roles.

Strategic Direction: India’s Distinct AI Pathway

The Economic Survey strongly argues that India should not replicate the capital-intensive, frontier-model approach adopted by advanced economies. Instead, it proposes a development-oriented, bottom-up strategy.

1. Bottom-Up, Application-Driven Approach

• India should focus on developing sector-specific AI solutions in areas such as agriculture, healthcare, education, and governance. 

• These solutions are more relevant to local needs and can deliver immediate economic and social benefits.

2. Focus on Small and Efficient Models

• Rather than investing heavily in large foundational models, India should prioritise small, task-specific AI models that can operate on limited hardware. 

• This approach is more aligned with India’s resource constraints and allows wider participation from startups and institutions.

3. Open and Collaborative Ecosystem

• Encouraging open-source and interoperable AI systems can reduce dependence on foreign technologies and promote innovation. 

• India already has a strong community of developers, which can be leveraged for collaborative growth

4. AI as Public Infrastructure

The Survey proposes treating AI as a public good, similar to digital public infrastructure like UPI and Aadhaar. The government can play a catalytic role by:

• Providing shared data platforms

• Creating common compute infrastructure

• Facilitating standardisation

5. Strategic Autonomy with Global Integration

• India must strike a balance between self-reliance and global cooperation. 

• While complete independence is neither feasible nor efficient, excessive dependence on foreign systems can pose risks to national security and economic stability.

Human Capital: The Core of AI Strategy

The success of India’s AI ecosystem will depend largely on its ability to build the right kind of human capital.

1. Changing Nature of Skills

AI is shifting the demand from routine cognitive skills to:

• Critical thinking

• Problem-solving

• Domain expertise

• Analytical reasoning

2. Education System Reforms

• The Survey emphasises the need to integrate education with real-world experience. 

• Initiatives such as earn-and-learn models and flexible academic pathways can help students gain practical exposure alongside theoretical knowledge.

3. Strengthening Foundational Skills

At the school level, emphasis should be placed on:

• Literacy and numeracy

• Communication skills

• Logical reasoning

These form the foundation for adapting to an AI-driven economy.

4. Focus on Human-Centric Jobs

• AI may not replace all jobs but will increase demand for roles requiring human interaction, experience, and judgement, such as healthcare, skilled trades, and education.

Governance and Regulatory Approach

The rapid growth of AI requires a balanced regulatory framework.

1. Need for Adaptive Governance

• India should adopt a light-touch, flexible regulatory approach that encourages innovation while managing risks. 

• Overregulation may hinder startups, while under-regulation can create systemic risks.

2. AI Economic Council (Proposed)

The Survey suggests the creation of an AI Economic Council to:

• Assess labour market impacts

• Guide phased AI deployment

• Align technology with socio-economic goals

3. Human-Centric Regulation

• The primary objective of AI governance should be to ensure that technology enhances human welfare rather than replacing it. 

• This includes safeguards against misuse, bias, and excessive automation.

Key Trade-offs in AI Development

India’s AI strategy must carefully navigate several trade-offs:

• Productivity vs Employment

• More AI → higher efficiency and output

• But → fewer jobs in some sectors

• Challenge: How to grow without job loss?

• Scale vs Inclusion

• • Rapid AI adoption → fast economic growth

  • But → may exclude low-skilled workers

    • Choice: Speed vs social stability

• Regulation vs Innovation

• • Strict rules → safety, accountability

  • But → may slow innovation

    • Choice: Safety vs speed

Recognising and managing these trade-offs is crucial for sustainable development.

     Artificial Intelligence represents not just a technological shift but a strategic and developmental choice for India. The country’s strength lies not in competing with global leaders in building large-scale AI models, but in leveraging its diverse data, human capital, and institutional capabilities to create context-specific solutions.

A carefully designed, bottom-up approach can ensure that AI contributes to economic growth, employment generation, and social inclusion. The ultimate goal should be to build an AI ecosystem that is efficient, equitable, and aligned with India’s long-term developmental priorities.