Al, Automation and India's Workforce

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/* ============ POLICY LENS ============ / var POL_T={1:"Make AI literacy near-universal",2:"Target reskilling, new tasks and occupation creation",3:"Turn the shortage sectors into an absorption channel",4:"Raise learning and completion together",5:"Build on women’s position in complementary work",6:"Reorganise social protection",7:"Restructure the labour subsidy",8:"Treat housing and commuting as labour-market infrastructure",9:"Support the reinstatement channel in the data economy",10:"Build continuous measurement"}; / activeLens: which part of the page the policy lens speaks to. Keys are the sections' data-lens values (regimes, explore, compare, taskmap, states, policy, figures, methodology), set by the tab on show and refined by scrolling within the open tab (Explore holds explore, compare and taskmap). */ var activeLens="regimes", lensOpen=false, lensLock=0, lensLast=""; function it(p,t){ return {p:p,t:t}; }

var LENS_NAT={head:"Exposure has risen modestly since 2012, and its quality has improved from a low base", items:[it(2,"Upskill the AI-complementary workforce in AI fluency and grow new roles in information technology, Global Capability Centres, pharmaceuticals and high-skilled manufacturing."), it(3,"Turn shortage sectors — health, elderly care, education and trade skills — into the main absorption channel for workers."), it(2,"Reskill exposed workers before losses materialise, prioritising young, urban labour-market entrants and the unemployed.")]}; var LENS_REG=[ {head:"Grow the base where AI raises productivity", items:[it(2,"Upskill in AI fluency toward higher value-added work and new roles such as forward-deployed engineers, AI validation and AI strategy."), it(3,"Health and teaching professionals are small but complementary: expand them through shortage-sector credentials."), it(4,"Build logical thinking, articulation, negotiation and adaptability early, so more young people can enter this regime.")]}, {head:"Clerical and sales work faces substitution pressure", items:[it(2,"Direct reskilling budgets at routine clerical, back-office and low-discretion technical roles rather than spreading them evenly."), it(2,"Shift task content toward judgement, client-facing and supervisory work that moves an occupation into the complementary regime."), it(2,"Target new AI-induced jobs such as data annotators and AI trainers, though some may be temporary.")]}, {head:"The balance between augmentation and substitution is still open", items:[it(2,"Train workers in judgement, verification and client engagement."), it(2,"Redesign workflows from routine execution toward oversight and exception-handling."), it(2,"Encourage AI start-ups that help firms clear adoption bottlenecks and deploy AI to raise labour productivity.")]}, {head:"Routine work is technically automatable, with or without AI", items:[it(2,"High-routine employment rose 4.8 points to 32.4% since 2012. Add judgement-intensive service trades and task modules to apprenticeships."), it(2,"Combine classroom training with supervised workplace exposure in short-term skilling."), it(3,"Grow value-added agro-processing for the low-exposure farm workforce, alongside factory employment.")]}, {head:"The largest regime is insulated from both AI and task-based automation", items:[it(3,"Target the low-income populous states with jobs in sectors such as agro-processing."), it(3,"Raise the standing of trade skills through a recognised credential system."), it(3,"Develop entrepreneurial skills among young people and ease credit, regulatory requirements and platform matching for the self-employed.")]} ]; var LENS_WOMEN={head:"For women, participation is the binding constraint", items:[it(5,"Only about 18% of women aged 20–29 are in paid work, against 79% of men. Childcare, elderly-care infrastructure, transport and safe urban housing are labour-market policy."), it(5,"Women's exposed employment is concentrated in health and teaching occupations, which are non-routine and interaction-intensive."), it(1,"Deliver AI training through the Skill India Digital Hub, with assisted enrolment at Common Service Centres.")]}; var LENS_YOUNG={head:"Young entrants carry the most routine work", items:[it(2,"Workers aged 15–24 have the highest share of high-routine employment, 39.4% against 24.2% for 55–64. Prioritise young entrants and the unemployed for reskilling."), it(2,"Include an industry-supervised capstone in AICTE-approved engineering programmes, using both domain knowledge and AI tools."), it(4,"Build durable skills early — logical thinking, negotiation, adaptability, dealing with uncertainty — and entrepreneurship.")]}; var LENS_OLDER={head:"Older workers are concentrated in low-exposure work", items:[it(3,"Most older workers are in agriculture and physical jobs; value-added sectors such as agro-processing raise their productivity."), it(3,"Recognise trade skills through credentials so that experience carries value."), it(1,"Offer AI literacy with assisted enrolment at Common Service Centres.")]}; var LENS_URBAN={head:"Urban India retains the largest complementary base to build from", items:[it(2,"One in five urban workers remains in AI-exposed, low-complementarity, routine work. Reskilling budgets should be directed at this regime rather than spread evenly across the workforce."), it(2,"48.3% of urban employment is AI-exposed, against 15.0% in rural India. Build AI fluency for information technology, Global Capability Centre, pharmaceutical and high-skilled manufacturing roles."), it(1,"Involve the private sector in funding AI skilling through CSR, delivered through the Skill India Digital Hub.")]}; var LENS_RURAL={head:"Rural work sits mostly outside AI's reach", items:[it(3,"Grow value-added sectors such as agro-processing for the low-exposure farm workforce."), it(3,"Use shortage occupations in health, care and education, plus trade skills, as the absorption channel."), it(1,"Deliver AI training with assisted enrolment at Common Service Centres.")]}; var LENS_RU={head:"Rural and urban India need different channels", items:[it(2,"Urban: direct reskilling budgets at the one in five urban workers in AI-exposed, low-complementarity, routine work."), it(3,"Rural: grow agro-processing and other value-added sectors for the low-exposure farm workforce."), it(3,"Both: make health, care, education and trade skills the absorption channel, starting with the low-income populous states.")]}; var LENS_TASK={head:"Jobs remain concentrated where AI exposure is negative", items:[it(3,"Skilled agricultural workers alone are 29.5% of jobs: value-added sectors such as agro-processing are the productivity route."), it(2,"Sales workers, at 9.1%, are the largest AI-exposed occupation and sit in the substitution-pressure regime."), it(3,"Health and teaching professionals are small but complementary: expand them throug