DAW 25th March 2026, Mains Answer Writting 2027

DAW 25th March 2026, Mains Answer Writting 2027

Question

Examine the implications of AI-driven automation on employment patterns in developing countries like India. Suggest policy measures to address these challenges. (10 marks)

Model Answer

Approach:

  • Introduction

  • Briefly define AI-driven automation and contextualise it for developing economies like India (labour surplus, informal sector).

  • Highlight that AI has a dual impact: opportunity for growth and challenge for employment stability.

  • Body

  • Divide the answer into two parts:

  • First, examine implications on employment both positive (job creation, productivity, innovation) and negative (job displacement, inequality, skill gap).

  • Then, suggest policy measures focusing on skilling, social security, education reforms, MSME support, and ethical AI governance.

  • Conclusion

  • Emphasise the need for a human-centric and inclusive AI approach balancing efficiency with equity.

  • Conclude that with the right policies, AI can become a driver of employment transformation rather than displacement.

Introduction

Artificial Intelligence (AI)-driven automation refers to the deployment of technologies such as machine learning, robotics, and natural language processing to perform tasks that traditionally required human labour. For developing economies like India, characterised by labour abundance, a large informal workforce, and skill asymmetry, AI represents both an opportunity for accelerated growth and a challenge to employment stability. Its impact is thus structural, multidimensional, and distribution-sensitive. Body Implications on Employment Patterns Positive Implications

  • Job Creation in New and Emerging Sectors

  • Artificial Intelligence is generating employment in high-skill domains such as data science, AI engineering, cybersecurity, cloud computing, and analytics.

  • It is estimated that nearly 20 million new jobs could be created in India through digital technologies.

  • Additionally, new hybrid roles such as AI ethics experts, automation strategists, and human-AI interaction specialists are emerging.

  • This reflects a broader transition from labour-intensive employment to knowledge-intensive employment.

  • Productivity Gains and Economic Growth

  • AI is expected to contribute nearly $1.7 trillion to India’s economy by 2035.

  • Artificial Intelligence acts as a force multiplier by enhancing efficiency across multiple sectors of the economy.

  • It is driving improvements in areas such as smart manufacturing, financial technology, governance, and logistics.

  • Example: AI-enabled platforms like GSTN analytics and faceless tax assessment improve efficiency and compliance.

  • Transformation in Nature and Quality of Work

  • Automation reduces the burden of repetitive and routine tasks performed by workers.

  • As a result, workers are increasingly able to focus on creative, analytical, and strategic roles.

  • This leads to job enrichment and the creation of higher-value employment opportunities.

  • Example: In healthcare, AI assists doctors in diagnostics such AI radiology tools, enhancing rather than replacing jobs.

  • Boost to Entrepreneurship and Innovation

  • Artificial Intelligence democratizes access to advanced technological tools such as cloud-based AI and automation platforms.

  • This encourages the growth of startups and strengthens innovation ecosystems.

  • As a result, AI promotes job creation through the emergence of new enterprises and business models.

  • Potential for Inclusive Development

  • Artificial Intelligence has the potential to improve access to essential services for vulnerable and underserved populations.

  • In healthcare, AI enables better diagnostics and telemedicine services.

  • In agriculture, it supports precision farming and accurate weather prediction through Kisan e-mitras, e-soil etc.

  • In education, it facilitates personalized learning experiences such as DIKSHA platform.

  • AI can also empower nearly 490 million informal workers through digital platforms and improved access to opportunities.

  • Sectoral Efficiency and Public Service Delivery

  • Artificial Intelligence improves governance through AI-enabled service delivery, e-courts, and Direct Benefit Transfer (DBT) systems.

  • In the financial sector, it enhances fraud detection and promotes financial inclusion.

  • In agriculture, it contributes to improved productivity and resource efficiency.

  • Overall, AI strengthens state capacity and improves public service delivery outcomes.

Negative Implications

  • Job Displacement and Structural Unemployment

  • Artificial Intelligence disproportionately affects routine and repetitive jobs across sectors.

  • Sectors such as manufacturing, business process outsourcing (BPO), and clerical services are particularly vulnerable.

  • It is estimated that up to 60 million jobs in manufacturing could be displaced by 2030.

  • This leads to structural unemployment and significant adjustment costs in the labour market.

  • Decline in Entry-Level Employment

  • Automation of tasks such as coding, testing, and customer support has reduced the demand for entry-level jobs.

  • There is growing evidence of declining entry into AI-exposed occupations.

  • Example: Chatbots and AI assistants are replacing customer support executives in BPO sectors.

  • This weakens traditional career ladders and adversely affects youth employment prospects.

  • Labour Market Polarisation and Inequality

  • Artificial Intelligence increases demand for high-skilled workers while reducing opportunities for middle- and low-skilled workers.

  • There is a growing wage premium for workers with AI-related skills.

  • This results in widening income inequality and an increasing skill divide in the labour market.

  • Vulnerability of Informal Sector

  • Nearly 90% of India’s workforce is employed in the informal sector, which lacks job security and social protection.

  • Workers in this sector have limited access to reskilling and upskilling opportunities.

  • This leads to precarious employment conditions and livelihood insecurity.

  • Skill Gap and Workforce Readiness Challenges

  • The rapid pace of technological change is not matched by the adaptation of education and training systems.

  • A large section of the workforce lacks the necessary digital and technical skills required in an AI-driven economy.

  • This creates a structural mismatch between labour demand and supply.

  • Gender and Social Inequality

  • Women and marginalized groups are disproportionately employed in routine and low-skilled jobs, making them more vulnerable to automation.

  • The digital divide further excludes disadvantaged communities from accessing new opportunities.

  • Moreover, AI-driven growth is concentrated in urban centres and technologically advanced regions. This leads to increased rural-to-urban migration and widening regional inequalities.

  • Ethical and Governance Concerns

  • The use of Artificial Intelligence raises concerns related to algorithmic bias in hiring and performance evaluation.

  • There is also a lack of comprehensive regulatory frameworks governing AI deployment in the workplace.

  • This raises issues of fairness, accountability, and protection of labour rights.

Way Forward

  • Skilling, Reskilling and Lifelong Learning

  • There is a need to promote large-scale skilling, reskilling, and lifelong learning to prepare the workforce for an AI-driven economy.

  • Government initiatives such as the Skill India Mission and Pradhan Mantri Kaushal Vikas Yojana (PMKVY) have trained millions of youth in industry-relevant skills; these must now integrate AI, robotics, and data analytics modules.

  • The FutureSkills PRIME programme (MeitY + NASSCOM) has already enrolled over 18.5 lakh candidates in emerging technologies including AI.

  • Education System Reforms

  • The education system must integrate AI, coding, and digital literacy from school to higher education levels.

  • The National Education Policy (NEP) 2020 promotes multidisciplinary learning and emerging technologies such as AI.

  • The CBSE AI curriculum (Classes VI–XII) and YUVAi (Youth for Unnati and Vikas with AI) initiative aim to build early AI awareness among students.

  • Example: AI-enabled learning platforms under DIKSHA enhance accessibility and personalised education.

  • Strengthening Social Security Frameworks

  • Social security mechanisms must be expanded to include informal and gig workers, who are most vulnerable to automation shocks

  • The Code on Social Security, 2020 provides a framework for gig and platform workers’ welfare.

  • Schemes such as e-Shram Portal (over 29 crore registered workers) and PM Shram Yogi Maandhan Yojana (pension for unorganised workers) should be strengthened.

  • Example: Rajasthan’s gig worker welfare initiatives provide a model for state-level innovation.

  • Promoting Human-AI Collaboration

  • Policies should encourage the use of AI for augmentation rather than replacement of human labour.

  • The Economic Survey 2023–24 emphasises “AI as a complement to labour” rather than a substitute.

  • This approach ensures productivity gains while preserving employment.

  • Supporting MSMEs and Labour-Intensive Sectors

  • MSMEs contribute nearly 30% to India’s GDP and employ over 11 crore people, making them crucial for employment stability.

  • MSMEs should be supported with financial incentives, credit access, and digital infrastructure for gradual AI adoption.

  • Schemes such as Credit Guarantee Fund Trust for Micro and Small Enterprises (CGTMSE) and Digital MSME Scheme promote technology adoption.

  • Strengthening Innovation and Startup Ecosystem

  • The government should promote AI-driven entrepreneurship through initiatives such as the IndiaAI Mission (₹10,371 crore outlay) and Atal Innovation Mission (AIM).

  • India has over 1.8 lakh startups, with nearly 89% using AI technologies in some form.

  • Example: Platforms like Bhashini (AI-based language translation) and Aarogya Setu (AI-enabled health app) demonstrate real-world applications.

  • Bridging the Digital Divide

  • Expanding digital infrastructure is essential to ensure inclusive access to AI technologies.

  • The Digital India Programme and BharatNet Project aim to connect rural areas with high-speed internet.

  • Example: Bhashini platform enables AI-based multilingual access to services, promoting digital inclusion.

  • Bridging this divide will ensure that rural populations also benefit from AI-driven growth.

  • Ethical and Regulatory Framework for AI

  • A robust ethical framework is required to ensure transparency, accountability, and fairness in AI deployment.

  • The NITI Aayog’s “AI for All” strategy emphasises responsible and inclusive AI development.

  • The IndiaAI “Safe and Trusted AI” pillar focuses on bias mitigation, explainability, and governance.

  • Public–Private–Academia Collaboration

  • Strong collaboration between government, industry, and academia is essential to align skills with market needs.

  • Such collaboration will ensure a smoother and more inclusive transition to an AI-driven economy.

  • Initiatives such as Centres of Excellence for AI and Global Capability Centres (1800+ in India) promote research and innovation.

Conclusion

India must adopt a “human-centric AI” approach, combining skilling, social protection, and innovation. With targeted policies and inclusive governance, AI can become a driver of employment transformation rather than displacement, aligning with the vision of Viksit Bharat 2047.The challenge for India lies in managing this transition through inclusive policies, skill development, and ethical governance. With a balanced approach, AI can become a powerful tool for achieving sustainable and inclusive economic growth.