Fortune and Future in AI – PM’s Vision at India AI Impact Summit
Why in News:
At the India AI Impact Summit in New Delhi, Prime Minister Narendra Modi presented India’s approach to Artificial Intelligence (AI), emphasising:
- AI as a “Global Common Good”
- Open, inclusive and ethical AI
- Opposition to monopolistic and strategic control of AI
- Need for global governance standards
UPSC Relevance: GS-III: Science & Tech GS-II Security
India’s AI Philosophy – “MANAV” Vision
PM Modi introduced the MANAV framework, meaning human-centric AI.
M – Moral and Ethical Systems
AI must be built on ethical guidelines.
A – Accountable Governance
Transparent rules, oversight mechanisms.
N – National Sovereignty
Data belongs to those who generate it (Data sovereignty).
A – Accessible and Inclusive
AI should not become monopoly of few companies/countries.
V – Valid and Legitimate
AI must be lawful, verifiable and compliant with regulations.
Core Commitments:
1. Evaluate AI in real-world contexts
- Assess AI impact on jobs, economy, skills.
2. Strengthen multilingual & contextual AI
- Improve cross-lingual AI support.
- Focus on under-represented languages (important for India & Global South).
3. Publish anonymised AI usage insights
- Support evidence-based policymaking.
- Understand AI diffusion across economy.
Multidimensional Impact of Artificial Intelligence
1. Economic Growth and Development
AI enhances productivity through automation, predictive analytics and intelligent manufacturing, thereby accelerating GDP growth and digital economy expansion. It also enables the emergence of new industries such as robotics, data analytics and autonomous systems. However, unequal access to AI capabilities may widen technological and income disparities across countries and firms.
2. Employment and Labour Markets
AI substitutes routine and repetitive tasks in manufacturing, clerical work and services, leading to structural labour displacement. At the same time, it generates new high-skill employment in AI engineering, data science and robotics. The core policy challenge lies in workforce reskilling, education reform and managing technological unemployment during the transition.
3. Governance and Public Service Delivery
Governments increasingly deploy AI for welfare targeting, tax compliance, smart cities, policing and disaster prediction, improving efficiency and evidence-based policymaking. However, risks of mass surveillance, exclusion due to algorithmic errors and opacity in automated decision-making raise concerns regarding accountability, transparency and citizens’ rights.
4. Ethical and Societal Implications
AI systems often reproduce biases embedded in training data, resulting in discrimination in hiring, lending or policing. Emerging threats such as deepfakes, misinformation and behavioural manipulation undermine trust, democratic discourse and human autonomy. Therefore, ethical AI principles such as fairness, transparency and human oversight are essential.
5. Security and Military Transformation
AI is transforming warfare through autonomous drones, cyber operations, intelligence analysis and surveillance systems. Lethal Autonomous Weapons Systems (LAWS) raise profound moral and legal questions regarding machine decision-making over life and death and may trigger a global AI arms race.
6. Data Governance and Privacy
AI relies on massive datasets, making data a strategic economic and political resource. Issues of data ownership, consent, facial recognition and surveillance threaten privacy and civil liberties. Robust data protection and accountable data governance frameworks are therefore critical.
7. Geopolitics and Global Power
AI capability is emerging as a determinant of economic competitiveness, technological sovereignty and geopolitical influence. The global AI race among major powers risks technological bifurcation and strategic dependence for developing countries lacking domestic capabilities.
8. Regulatory and Institutional Challenges
Balancing innovation with safety is the central regulatory dilemma in AI governance. Divergent global approaches — ranging from innovation-led to rights-based regulation — highlight the need for international cooperation, standards and ethical governance mechanisms.
India’s Position in the Global AI Landscape: Strengths and Challenges
1. Structural Strengths of India in AI
Large IT Workforce
India possesses one of the world’s largest pools of software engineers, data professionals and technology graduates, enabling rapid AI development, deployment and service provision.
Digital Public Infrastructure
India’s digital identity, payments and data platforms provide interoperable datasets and scalable architecture conducive to AI applications in governance, finance and public services.
Vibrant Startup Ecosystem
India hosts a rapidly expanding AI startup landscape across fintech, healthtech, agritech and SaaS sectors, fostering innovation and indigenous technological solutions.
Large and Diverse Data Pool
India’s vast population, linguistic diversity and expanding digital penetration generate extensive datasets essential for training AI systems, particularly in language technologies and public service applications.
Semiconductor Push
- AI models require: High-performance chips (GPUs, AI accelerators), Data processing hardware
- India is Promoting semiconductor manufacturing under national initiatives, Trying to reduce dependence on imports, Building chip design and fabrication capacity.
Quantum Computing
- Quantum computing:
- Can solve highly complex problems faster than classical computers.
- Has applications in cryptography, climate modelling, drug discovery, AI optimisation.
- India is investing in quantum research to Stay ahead in next-gen computing and to avoid technological dependency.
Secure Data Centres
- AI runs on:
- Massive datasets, Cloud storage, Continuous computation
- India is expanding:
- Domestic data centres, Cloud infrastructure, Data localisation mechanisms
2. Challenges to AI Development in India
Low R&D Expenditure
India’s research spending remains around 0.6–0.7% of GDP, constraining frontier AI research, indigenous innovation and advanced model development.
Talent Gap in Advanced AI
Despite abundant IT talent, shortages persist in high-end AI research, semiconductor design, deep learning and core algorithmic innovation.
Computing Infrastructure Deficit
AI development requires high-performance computing, semiconductor capability and cloud infrastructure, areas where India remains import-dependent and capacity-constrained.
Data Quality and Accessibility Issues
Fragmented, unstructured and low-quality datasets limit reliable AI training and deployment across many governance and economic sectors.
3. Key Sectors Where AI Can Transform India
Agriculture
AI can enable precision farming, crop prediction, pest detection, climate advisory and market intelligence, improving productivity and farmer incomes.
Healthcare
AI-based diagnostics, telemedicine, disease surveillance and resource optimisation can strengthen public health delivery and address doctor shortages.
Education
Personalised learning systems, adaptive assessments and multilingual digital content can improve learning outcomes and educational access.
Governance
AI can enhance welfare targeting, fraud detection, smart city management and service delivery efficiency, improving state capacity.
Language Technology
AI-based translation and speech technologies can enable digital inclusion across India’s diverse linguistic landscape.
Climate and Disaster Management
AI can support flood forecasting, climate modelling, early warning systems and resource planning for climate adaptation.

Emerging Global Governance and Regulatory Challenges in AI
Artificial Intelligence has cross-border impacts on economies, security and societies, necessitating global governance responses.
Need for Global AI Governance
AI risks such as misinformation, autonomous weapons and economic disruption transcend national boundaries. However, there is no universal regulatory framework, creating demand for multilateral cooperation through platforms such as the Global Partnership on Artificial Intelligence.
Frontier AI Risks and Safety
Highly capable frontier AI systems introduce risks such as large-scale misinformation, cyber manipulation, biosecurity misuse and loss of human control over autonomous systems. The absence of global safety standards heightens systemic risks.
Concentration of AI Power
Advanced AI development requires massive data, compute and capital, concentrating power within a few corporations and countries. This raises concerns of monopolisation, opacity and technological dependence of developing nations.
Responsible and Ethical AI
Bias, privacy invasion, surveillance and lack of explainability create ethical risks in AI deployment. Responsible AI frameworks emphasise fairness, transparency, accountability and human oversight.
Global AI Inequality
AI capabilities are concentrated in technologically advanced countries, creating an “AI divide” where developing countries become technology consumers rather than producers. Bridging this gap requires capacity building and technology cooperation.
Open vs Closed AI Debate
A key policy debate concerns whether advanced AI models should be open-source or proprietary. Balancing innovation diffusion with safety control and accountability remains a major governance challenge.
Labour Market Disruption
AI-driven automation will reshape employment structures worldwide, requiring large-scale reskilling, education reform and social protection to ensure inclusive transition.
Conclusion
Artificial Intelligence is a transformative general-purpose technology with profound economic, social and strategic implications. India possesses significant structural advantages in AI adoption but must bridge gaps in research investment, advanced talent and computing infrastructure. At the global level, human-centric governance, ethical regulation and international cooperation are essential to ensure that AI advances inclusive, safe and sustainable devel
Practice Mains Questions
- “Artificial Intelligence is a double-edged sword for developing countries.” Discuss.
- How can Artificial Intelligence improve governance and public service delivery in India?
- AI and employment: threat or opportunity? Examine.
- What ethical and regulatory challenges are posed by Artificial Intelligence?
- “Artificial Intelligence presents both opportunities and structural challenges for India.” Discuss.