TLDR: A recent article critically analyzes India’s drive to establish AI hubs, such as Google’s initiative in Visakhapatnam and a proposed hub in Bihar. It argues that these projects, while presented as progress, risk fostering a new form of ‘data colonialism’ and technological dependence on foreign Big Tech. Concerns are raised regarding the extraction of Indian data for global models, reliance on imported hardware and cloud services, and the significant environmental footprint of data centers. The author suggests that without robust indigenous infrastructure, strong data governance, and widespread AI literacy, India’s ‘AI for Bharat’ vision may inadvertently lead to a digital colony rather than true digital sovereignty.
Across the globe, the narrative surrounding Artificial Intelligence (AI) is increasingly marked by anxiety, with widespread layoffs, corporate restructuring, and the shrinking of human roles. Major tech giants, including Amazon and Meta, have announced significant job cuts, with Amazon’s CEO Andy Jassy openly admitting in June 2025 that generative AI will ‘reduce’ corporate headcount as automation scales. In stark contrast, India is packaging the same technology as its ‘next big leap forward,’ a paradox in a nation striving for labor-intensive growth and equitable employment.
The announcement of Google’s AI Hub in Visakhapatnam this October was met with optimistic press releases, touting ’empowering India’s future,’ ‘driving innovation,’ and ‘AI for Bharat.’ However, beneath this veneer, the article suggests a familiar pattern of extraction and dependency, a phenomenon the Global South has experienced for centuries. Scholars Nick Couldry and Ulises Mejias term this ‘data colonialism’ – the extraction of human life as digital raw material for profit. India’s new AI hubs, it is argued, risk becoming ‘vast data pipelines feeding Big Tech’s global models,’ where the data of Indian citizens, institutions, and public systems power algorithms refined and monetized elsewhere, with profits and patents remaining in the global North.
The government’s rhetoric of ‘AI for Bharat’ and ‘digital sovereignty’ is questioned, as India remains heavily reliant on imported high-end semiconductor hardware and foreign cloud services for data storage. Public sector digitization projects often operate on private corporate clouds with opaque procurement contracts, leading to what the author describes as ‘dependence dressed up in nationalist language.’ The article posits that ‘hosting is not the same as owning. Collaboration is not the same as control.’
Beyond the digital realm, AI hubs carry substantial, often overlooked, environmental costs. According to the International Energy Agency (IEA), global data centers consumed approximately 415 terawatt-hours (TWh) of electricity in 2024, accounting for about 1.5% of total global demand, with projections to reach 945 TWh by 2030. The World Economic Forum estimates that a 1 MW data center can consume up to 25.5 million liters of water annually for cooling, and global water use from data infrastructure could exceed a trillion liters by 2030. While Google has pledged investments in renewable energy in India, these contributions may barely offset the strain these massive AI hubs place on India’s electricity grid and water systems, particularly in vulnerable regions like Andhra Pradesh.
The home minister’s declaration of Bihar becoming an AI hub is also critically examined. Despite sounding like a step towards inclusion for an overlooked state, the promise clashes with the reality of Bihar’s patchy internet connectivity, frequent power cuts, and low digital literacy. Building a ‘world-class AI hub’ without these fundamental infrastructures is deemed ‘less strategy and more spectacle,’ risking the extraction of value without building local capacity.
Much of India’s AI ambition is framed as ‘technonationalism’ – the belief that adopting frontier technologies signifies national strength. However, when the underlying infrastructure, data pipelines, and decision-making remain dependent on global corporations, this becomes a ‘kind of theatre.’
For India to truly lead in AI, the article advocates for reclaiming its digital foundations. This involves investing in public digital infrastructure that is open, secure, and locally accountable, rather than proprietary systems. It also necessitates building an indigenous hardware ecosystem, particularly for cutting-edge GPUs required by transformer-based AI models. Prioritizing digital and AI literacy, implementing reskilling programs for workers affected by automation, and establishing regulatory frameworks that treat data as a public resource are crucial steps. A truly sovereign approach demands algorithmic accountability, environmental transparency, and public participation in tech governance.
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India stands at a defining moment, with the choice to either remain a testing ground for external AI revolutions or to forge its own path. Resisting ‘AI colonialism’ is not about rejecting technology but about ‘reclaiming purpose’ and ensuring that India’s data, labor, and creativity serve local dignity. Without rewriting the rules, Google’s AI hub in Vizag and the proposed one in Bihar could become ‘monuments to a new kind of empire: one that doesn’t need armies, only algorithms. And this time, if we’re not careful, the empire will live inside our data.’
