Tech giants Intel and Google deepen AI CPU monopoly: How oligopolistic consolidation accelerates extractive data capitalism and undermines open innovation

Indigenous and Global South communities often view AI hardware as part of a broader struggle for technological sovereignty, resisting extractive data practices that mirror colonial resource extraction. Projects like the RISC-V based 'PULP' processors in Africa or Latin America’s open-source hardware initiatives challenge Silicon Valley’s monopoly by centering local control over innovation. These efforts highlight how proprietary AI CPUs exacerbate digital colonialism, where Global South users become data subjects without agency over the tools that process their information.

The partnership echoes historical patterns of corporate consolidation in computing, from IBM’s 1980s dominance to Microsoft’s 1990s antitrust battles, where oligopolies stifled competition and innovation. Intel’s near-monopoly in CPUs during the 1990s and Google’s Android antitrust cases in the 2010s demonstrate how market concentration in AI hardware is not novel but a recurring feature of tech capitalism. The deal also parallels the 1970s semiconductor wars, where U.S. firms leveraged government subsidies to crush Japanese competitors, raising questions about state-corporate collusion in AI infrastructure.

Cross-culturally, the partnership reflects a Western-centric model of innovation that prioritizes proprietary control over collaborative, open approaches. In contrast, China’s 'Made in China 2025' strategy explicitly targets semiconductor independence, while the EU’s Chips Act aims to reduce dependency on U.S. tech giants. Indigenous communities in the Americas and Oceania often frame AI hardware as part of a broader decolonial project, emphasizing collective ownership and ethical constraints on technological deployment.

Scientifically, the partnership raises concerns about the concentration of AI hardware innovation in a duopoly, which could limit diversity in architectural approaches and stifle research in energy-efficient or ethical AI designs. Studies show that monopolistic control over critical infrastructure (e.g., cloud computing) can lead to systemic biases and reduced innovation due to lack of competition. The deal also underscores the growing energy demands of AI CPUs, with researchers warning that unchecked consolidation could exacerbate environmental harms from semiconductor manufacturing.

Artistically and spiritually, the partnership embodies a mechanistic worldview that reduces AI to a commodity, ignoring the cultural and ethical dimensions of technology. Indigenous and Eastern philosophies often frame tools as extensions of collective wisdom, not private property, contrasting with Silicon Valley’s extractive ethos. The deal also reflects a Faustian bargain where technological progress is equated with corporate growth, sidelining spiritual or communal values in favor of shareholder returns.

Future modelling suggests that this consolidation could lead to a bifurcated AI ecosystem: a high-performance, proprietary tier dominated by Intel and Google, and a low-cost, open-source tier for marginalized users. Scenarios include increased regulatory crackdowns on antitrust violations, but also the rise of state-backed alternatives in China and the EU, fragmenting the global AI market. The deal may also accelerate the militarization of AI hardware, as defense contractors seek to control critical infrastructure for national security purposes.

Marginalized voices—such as open-source advocates, Global South researchers, and AI ethicists—are systematically excluded from this narrative, despite their critical role in shaping equitable AI futures. Grassroots movements in Africa and Latin America argue that proprietary AI CPUs deepen digital divides, while indigenous communities warn of cultural erasure through unchecked technological expansion. The partnership also sidelines workers in semiconductor manufacturing, who face exploitative labor conditions in factories producing AI hardware.