Artificial Intelligence (AI): Its Socio Economic Effects

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As per a PwC report, AI adoption is poised to drive unprecedented productivity, innovation, and economic expansion, potentially adding $957 billion to India’s economy by 2035. With India’s aspirations of becoming a $5 trillion economy, AI can be a transformative force across sectors.
However, in a country characterised by socioeconomic diversity, a vast informal workforce, and unequal access to technology, unregulated AI adoption could deepen inequality and labor distress, particularly in low-skill sectors.

Socio-Economic Effects of AI Adoption in India

Productivity Boost: AI optimizes production lines in manufacturing through automation & robotics.
Product Development: The IT sector leverages AI for software development, data analytics, and customer service, reinforcing India’s global tech hub status.
Startup Ecosystem: AI startups are rapidly emerging, with over 100 AI-based startups in 2023 (NASSCOM). E.g., Niramai’s AI-powered breast cancer detection.
Contribution to GDP: A PwC report predicts that AI could add $957 billion to India’s economy by 2035.

Healthcare: AI-driven diagnostics address doctor shortages in rural areas. E.g., Apollo Hospitals use AI for medical imaging analysis.
Agriculture: Precision farming using AI-based weather prediction. E.g., Microsoft’s AI for Farmers Initiative helps small farmers increase yields.
Education: AI-powered platforms provide customized learning, reducing the urban- rural digital divide. E.g., Diksha platform for e-learning.

Job Displacement: AI-driven automation could replace 23% of India’s jobs by 2030, affecting over 100 million workers (WEF, 2022).
Labour Distress: Job losses, wage stagnation, and skill mismatches disproportionately impact the informal workforce, which lacks unemployment benefits.

Skill Gap: 60% of India’s workforce lacks digital literacy, making them unfit for AI-driven jobs (NSDC).
Socio-economic Divide: Rural & marginalised communities are excluded from AI benefits, worsening urban-rural and rich-poor disparities.
Gender Disparity: Women hold only 25% of India’s tech jobs (NASSCOM), and systemic barriers make AI job opportunities inaccessible to them.

Bias & Discrimination: AI algorithms may reinforce prejudices in hiring, lending, and policing.
AI Surveillance Risks: Unregulated AI surveillance raises privacy concerns (E.g., facial recognition systems in public spaces).
Social Unrest: Rising job insecurity may fuel labour protests, as seen historically in textile automation movements.

Integrate AI-specific training into the Skill India Mission with a focus on coding, data analysis, and machine learning.
Expand AI training programs through partnerships with private players like Google and Microsoft.

Enact AI Equity legislation mandating social impact assessments for AI deployments.
Provide tax incentives to companies investing in reskilling instead of mass layoffs.

Expand BharatNet to all gram panchayats by 2026 to enhance digital connectivity.
Introduce subsidised devices and data plans to improve AI accessibility for rural populations.

Pilot Universal Basic Income (UBI) in AI-affected regions based on Sikkim’s model.
Expand Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) to include digital tasks such as data annotation for AI firms.

Partner with agritech firms like CropIn to deploy AI-driven solutions for small farmers.
Collaborate with edtech companies to introduce AI-driven learning in government schools.

Establish an AI Ethics Council to oversee transparency and fairness in AI systems.
Launch public awareness campaigns modeled on Swachh Bharat Mission to educate citizens on AI.

Provide AI tool subsidies to agricultural cooperatives to benefit small farmers.
Retrain BPO workers for AI oversight roles, such as managing chatbots and AI systems.

The Union Budget 2025 focuses on AI-driven growth through the National AI Mission 2.0 and skilling initiatives. However, to prevent rising inequity and labour distress, effective execution with social safeguards, digital inclusivity, and workforce transition strategies is crucial for balanced and sustainable AI adoption.
Reference: Deccan Herald | PMFIAS: Artificial Intelligence Archives

Introduction: Briefly introduce AI adoption as a transformative force in India, highlighting its dual nature with opportunities for growth and risks of inequity/labour distress.
Body: Analyse the positive and negative impacts of AI and elaborate on the steps needed to address inequity and labour distress arising from it.
Conclusion: Reiterate AI’s potential and the need for equity-focused strategies. End with an optimistic note tied to India’s ethos.