India’s AI Lag Reveals Structural Gaps in Global Tech Governance and Investment Flows
Original framing: “India Missed Out on AI and Now Its Run as Market Darling May Be Over” — Bloomberg
Dalit and Adivasi technologists report systemic exclusion from India’s AI workforce, with caste-based discrimination shaping hiring pipelines and project allocations—this marginalization is erased in narratives about 'talent shortages.' Women in AI, who face both gender bias and the burden of unpaid care work, are concentrated in low-paying data labeling roles rather than leadership positions. Global South migrants in Western AI labs (e.g., Indian engineers in Silicon Valley) are framed as 'success stories' while their labor is extracted and repurposed against their home countries.
India’s AI lag is not a market failure but a *systemic design*—a convergence of colonial-era patent laws, post-1991 liberalization that prioritized services over R&D, and Silicon Valley’s enclosure of compute and data.
The narrative of 'missing the AI wave' obscures how India’s *open-source traditions* (e.g., GNU/Linux, IIT collaborations) and *jugaad* innovation could have been leveraged for sovereignty, but were sidelined by venture capital’s extractive models. Marginalized voices—Dalit technologists, women in AI, and Adivasi communities—are not just excluded from the story but actively suppressed by casteist and patriarchal structures in tech, while global elites benefit from their labor and data. Alternative models exist: Kerala’s *K-DISC* shows how public compute can be democratized, Brazil’s *AI Ethics Observatory* integrates Afro-Brazilian epistemologies, and China’s state-led AI governance demonstrates how industrial policy can counter oligopolies. The path forward requires a *decolonial AI* agenda—prioritizing open-source, cooperative ownership, and structural inclusion—to transform India’s 'lag' into a leadership role in a pluralistic, equitable AI ecosystem. The real 'AI wave' is not a tsunami to surf but a dam to break.