Human-Centred AI: Why India’s AI Moment Must Prioritise Jobs, Justice and Inclusion
As India hosts the AI Impact Summit New Delhi alongside the observance of World Day of Social Justice on February 20, the conversation around artificial intelligence is shifting from possibility to responsibility. The debate is no longer about whether AI will reshape work — that transformation is already underway — but about who benefits from it and how its gains are distributed. For a country as large and diverse as India, the stakes extend beyond technological leadership to social equity, labour rights and inclusive growth.
India’s digital expansion has positioned it at the centre of global AI adoption. The country hosts one of the largest user bases of advanced AI platforms and leads in mobile engagement with generative tools such as ChatGPT. This scale makes India a real-time testing ground for how AI interacts with education, employment and public services.
Projections suggest that by 2030, AI could generate millions of new technology jobs while simultaneously reshaping far more existing roles. The dual nature of this shift — creation alongside disruption — underscores why policy direction matters as much as innovation itself.
A human-centred AI approach begins with recognising that technology is not neutral. The way algorithms are designed, deployed and regulated influences wages, working conditions and access to opportunity. In India, where informal employment remains significant, AI adoption could either widen inequalities or help bridge them.
Optimists highlight the economic potential. AI can improve productivity across sectors including healthcare, agriculture, logistics and public administration. It can support small businesses through automation, expand digital financial inclusion and enable personalised education at scale. If paired with skilling initiatives, this transformation could strengthen India’s position in global value chains while creating new categories of employment.
Yet productivity gains do not automatically translate into social benefit. Without safeguards, automation may displace routine jobs faster than reskilling systems can respond. The experience of previous technological shifts suggests that workers in lower-income segments often face the highest transition risks. A human-centred framework therefore requires investment in lifelong learning, portable social protection and labour policies that recognise platform-based work.
Counterpoints
There is also a governance challenge. Rapid AI deployment can outpace regulatory capacity, raising concerns around data privacy, algorithmic bias and workplace surveillance. Experts argue that responsible AI must include transparency standards, accountability mechanisms and public participation in policy design.
Another tension involves global competition. Countries racing for AI leadership may prioritise speed over safeguards, fearing loss of investment. However, evidence increasingly suggests that trust and ethical design enhance long-term adoption. For India, positioning itself as a leader in inclusive AI could become a strategic advantage rather than a constraint.
Public response reflects both enthusiasm and anxiety. Young professionals view AI as an opportunity for upward mobility, while workers in routine roles worry about job security. This mixed sentiment reinforces the need for clear communication from governments and industry about transition pathways rather than abstract promises.
India’s AI moment is not simply technological; it is developmental. The country’s demographic scale, digital infrastructure and policy experimentation create an opportunity to shape global norms around inclusive innovation. Aligning AI with social justice does not mean slowing progress — it means ensuring progress is broadly shared.
The coming years will test whether AI becomes a tool for concentration of advantage or expansion of opportunity. The answer will depend on how effectively institutions integrate skills, regulation and social protection into the innovation ecosystem.
