In News:

• NITI Aayog has released a landmark study titled “AI for Inclusive Societal Development”, shifting India’s artificial intelligence discourse toward the informal workforce, which constitutes the backbone of the national economy. This first-of-its-kind framework seeks to harness AI and frontier technologies to formalise and uplift nearly 490 million informal workers, who contribute around 45% of India’s GDP but remain largely excluded from institutional protections and productivity systems.
• At the core of this initiative is the proposed National Mission “Digital ShramSetu”, conceptualised as a technology-enabled bridge connecting informal workers to formal systems of work, finance, skilling, and social protection — a critical step for achieving the Viksit Bharat 2047 vision.

Mission Digital ShramSetu: Vision & Framework

Objective:To drive large-scale socio-economic inclusion by integrating AI, blockchain, robotics, IoT, AR/VR, and immersive learning into workforce development.

Key Components

India’s Informal Workforce: Current Realities

• Size: ~490 million workers (≈85% of labour force)
• GDP Share: ~45%
• Productivity: ~USD 5/hour vs national avg. USD 11/hour
• Annual Per Capita Income: ~USD 1,800 (projected USD 6,000 by 2047 if status quo continues; target ≈ USD 14,500)
• Women’s Informal Sector Participation: ~15% (ex-agriculture) vs 37% national avg & 47% global avg
• Social Security Access: ~48%
• Formalisation Vision: Reduce informal sector to 40% by 2047; formalise73.2% of current informal enterprises

Existing Support Tools:e-Shram Portal, PM-JJBY, PM-SYM, Atal Pension Yojana, Micro-lending schemes, Skill India programmes

Challenges Confronting Informal Workers

• Income Instability & Wage Delays: No contracts; reliance on informal credit
• Limited Market Access: Fragmented, unorganised demand; lack of digital presence
• Low Skilling & Tech Adoption: Traditional workflows; language & literacy barriers
• Poor Social Security Coverage: Non-portable records and scheme awareness gaps
• Migrant Vulnerability: No portable credentials or employment networks
• Safety Risks: Hazardous work environments without monitoring support

Institutional & Policy Architecture

• Apex Mission Leadership: PM-level council for policy, funding & coordination
• Sector-Specific Task Forces: Agriculture, construction, healthcare, retail etc.
• State Coordination Units: Local deployment, innovation hubs, adoption drives
• Partnership Ecosystem: Government, industry coalitions (CII, NASSCOM), World Bank, global philanthropies & academia

Why It Matters

The roadmap stresses that technology alone is insufficient; success depends on human-centric deployment, affordability, and multi-stakeholder collaboration. With proactive adoption, India can multiply informal productivity, enhance incomes, reduce vulnerability, and transition toward a high-productivity, high-trust labour economy. Delay, however, could lock millions into low-income traps, weakening India's development trajectory.

In News:

NITI Aayog has unveiled its strategic report “Roadmap on AI for Inclusive Societal Development”, which presents a comprehensive vision for leveraging Artificial Intelligence (AI) to strengthen India’s vast informal economy through enhanced digital inclusion, skilling, and social protection systems.

Status of India’s Informal Workforce

• Scale and Economic Role: Approximately 490 million Indians—about 90% of the national workforce—are engaged in informal employment spanning agriculture, construction, and services, together contributing nearly half of India’s GDP (MoLE, 2024).
• Rural Dominance: Over 80% of rural labourers operate without written contracts or social security coverage, especially in construction, handicrafts, and retail sectors.
• Gendered Vulnerability: Women constitute around 55% of the informal workforce, with significant representation in home-based and agricultural activities (ILO, 2023).
• Low Productivity and Earnings: Informal sector productivity remains roughly one-fourth that of the formal economy, perpetuating low wages and economic insecurity.
• Emergence of Urban Informality: The gig and platform economy has created a new informal class, with nearly 7.5 million platform workers (NITI Aayog, 2022) still outside formal labour protections.

Core Challenges

• Financial Instability: Over three-fourths of informal workers earn below ?10,000 per month and face limited access to affordable credit or insurance (PLFS, 2024).
• Market Inefficiencies: Only about 12% of small producers or artisans access digital or organized markets directly, remaining dependent on intermediaries.
• Digital and Skill Divide: Around 70% of informal workers lack basic digital literacy, impeding their participation in AI-integrated economies.
• Weak Social Protection: Just one-third of eligible informal workers are registered under welfare schemes such as e-Shram or PM-SYM.
• Policy Fragmentation: Overlapping databases and weak institutional coordination hinder effective benefit delivery and erode worker trust.

Transformative Potential of AI

• Financial Empowerment: AI-based credit assessment tools (e.g., SBI YONO, Setu.ai) can facilitate microloans for workers lacking traditional financial records.
• Digital Public Infrastructure (DPI): Platforms such as Aadhaar, UPI, and e-Shram can establish verifiable worker identities, improving transparency in wage payments and welfare targeting.
• Smart Contracts and Blockchain: Use of blockchain for wage traceability and supply chain verification (e.g., Tata Steel Foundation’s pilot in Jharkhand) can curb exploitation.
• AI-driven Skilling: Adaptive learning ecosystems like Skill India Digital can deliver personalized, voice-enabled vernacular micro-courses for re-skilling informal workers.
• Predictive Governance: AI-based data analytics can enhance targeting and timeliness of welfare delivery (e.g., integration with PM-Kisan data systems).

Major Recommendations

1. Launch of ‘Digital ShramSetu Mission’: Create an AI-enabled national platform integrating social security, skilling, and livelihood databases for informal workers.
2. Sector-specific AI Models: Focus on high-impact areas—agriculture, construction, logistics, and retail—for productivity enhancement.
3. Inclusive Design: Develop voice-first, multilingual AI interfaces to ensure accessibility for low-literacy populations.
4. Public–Private Collaboration: Promote partnerships among government agencies, startups, and tech firms for scalable innovation in informal ecosystems.
5. Responsible AI Charter: Establish a framework ensuring transparency, privacy, and inclusivity in AI deployment for social sectors.
6. AI-based Skilling Framework: Institutionalize micro-credential courses and continuous re-skilling under Skill India 2.0.
7. Impact Evaluation Mechanism: Implement real-time data-driven monitoring to assess inclusion, income enhancement, and service delivery outcomes.