Artificial Intelligence for Inclusive Welfare

• India hosting the fourth AI Impact Summit signals a shift from AI safety to geopolitical competition, with sarvajana hitaya, sarvajana sukhaya emphasising inclusive, welfare-oriented AI leadership.

Need for AI for Welfare in India

• Food Security: With ~70% of food produced by smallholders facing low productivity, AI advisories improve yields, input efficiency, and climate resilience.
• Health Access: India’s public doctor–patient ratio (~1:11,000) makes AI-enabled telemedicine and diagnostics essential for universal healthcare.
• Skill Deficit: Only ~5% of India’s 950 million workforce has formal training; AI platforms enable large-scale, personalised skilling.
• Service Efficiency: AI-driven analytics strengthen welfare targeting, reduce leakages, and improve delivery across 1.4 billion beneficiaries.
• Inclusive Growth: With rural internet access at ~24% versus 66% urban, welfare-oriented AI can reduce regional and gender inequalities.

AI as Welfare Transformation Tool

• Food Security: AI tools enhance the productivity of smallholders who supply ~70% of global food. E.g., Kisan E-Mitra handles ~20,000 farmer queries daily in 11 languages.
• Income Growth: Precision AI can raise farm incomes while reducing chemical inputs. E.g., Telangana’s Saagu Baagu doubled chilli farmers’ earnings with lower fertiliser and pesticide use.
• Care Access: AI-enabled telemedicine offsets doctor shortage. E.G., eSanjeevani completed ~389 million virtual consultations by mid-2025.
• Skill Scale: AI platforms scale education and skilling. E.g., DIKSHA reached ~275 million users, with ~70% of users in rural areas.

Structural Barriers to AI

• Digital Divide: With only 24% rural households online and low digital gender parity, large populations remain excluded from AI benefits.
• Energy Constraints: AI’s rising compute demand will stress India’s weak grids, unreliable power supply, and limited transmission capacity.
• Talent Shortage: A 1:10 ratio of skilled professionals to AI roles reflects gaps in advanced training, slowing innovation and scale.
• Supply Dependence: Over 90% import reliance for semiconductors and critical inputs makes AI ecosystems vulnerable to US–China tech rivalries.
• Data Deficit: Despite massive data generation, the lack of clean, annotated, multilingual datasets undermines AI accuracy and inclusiveness.

Way Forward

• Welfare-Centric AI: Define AI success by outcomes, farm yield, disease detection, literacy gains, not model size or geopolitical power.
• DPI Scaling: Deploy AI through Digital Public Infrastructure to reach scale, as shown by 389 million e-health consultations and 275 million digital learners.
• Skill Acceleration: Use AI-enabled skilling to address the 10:1 AI jobs-to-talent gap and upskill a workforce where only 5% are formally trained.
• Infrastructure Sync: Align AI growth with broadband, energy grids and domestic hardware capacity, given only 24% rural internet access and heavy chip import dependence.
• Lean Governance: Simplify AI regulation and promote “good-enough” AI to reduce compliance friction while accelerating innovation for the public good.

AI can redefine India’s welfare state when innovation aligns with inclusion, skills, and infrastructure, “technology with a human touch.” Bridging digital, data, and capacity gaps will turn AI from promise to progress, advancing Sabka Saath, Sabka Vikas, Sabka Vishwas.

Reference: The Indian Express

PMF IAS Pathfinder for Mains – Question 548

Q. Artificial Intelligence is a key instrument of next-generation governance reform in India. Analyse its role in improving public service delivery and examine the key constraints in its deployment. (250 Words) (15 Marks)

Approach

• Introduction: Write a brief introduction about the AI role in public welfare.
• Body: Write AI’s role in improving public service delivery, the key constraints in its deployment, and the way forward.
• Conclusion: Emphasis on an integrated and cooperative approach to successfully implement the AI for governance.