Tech Giants Race to Monetize AI Agents: How Big Tech’s Financial Infrastructure Locks in Extractive Economic Models

Indigenous financial systems prioritize reciprocity and ecological sustainability over growth, contrasting sharply with the extractive logic of AI-driven monetization. The push to embed AI agents in transactions risks further dispossession by treating data as a commodity to be exploited, mirroring historical patterns of resource extraction. Traditional knowledge systems often view money as a means to an end (e.g., communal harmony), not an end in itself, which is incompatible with the Silicon Valley ethos of perpetual accumulation.

The race to control financial infrastructure mirrors past monopolies like the Bank of England or the East India Company, where private entities shaped monetary systems to serve elite interests. The 19th-century gold standard and Bretton Woods system similarly embedded Western financial dominance, suggesting this 'AI money' push could replicate those power asymmetries. The lack of historical reflection in the narrative obscures how these corporations are repeating patterns of enclosure and control over economic life.

In Africa, mobile money systems (e.g., M-Pesa) have democratized financial access but also created new dependencies on corporate platforms, raising questions about who benefits from 'AI money.' In India, the Reserve Bank’s push for a digital rupee faces resistance over privacy concerns, highlighting cultural skepticism toward algorithmic control over transactions. Latin American cooperatives have experimented with community-controlled digital currencies, offering a counter-model to Big Tech’s centralized approach.

Research on algorithmic governance (e.g., Zeynep Tufekci’s work on platform power) shows how technical systems embed political choices, often invisibly. Studies on high-frequency trading reveal how AI-driven markets can amplify volatility and systemic risk, a dynamic likely to intensify with AI agents. The scientific literature on digital feudalism (e.g., Cory Doctorow) warns that platform monopolies could lead to 'enshittification' of economic life, where users and even AI agents become trapped in extractive ecosystems.

Artists like Hito Steyerl critique how digital systems commodify human experience, reducing life to transactional data points. Spiritual traditions often frame money as a test of ethical living (e.g., *dana* in Buddhism, *zakat* in Islam), which clashes with the amoral logic of AI-driven profit maximization. The push to monetize AI agents risks turning even creativity and care into extractive transactions, eroding non-commercial values.

Scenario modeling suggests that by 2035, AI agents could control 30-50% of digital transactions, creating a 'shadow economy' beyond state oversight. This could lead to a bifurcated financial system where elites use AI-driven wealth generation while the majority faces algorithmic debt traps. Without public alternatives, these corporations may become the de facto central banks of the digital age, with unchecked power to shape economic reality.

Low-income communities and racial minorities are disproportionately targeted by predatory fintech algorithms, which AI agents could scale globally. Gig workers and freelancers, already exploited by platform capitalism, face further precarity as AI-driven pricing and wage-setting systems remove human agency. The narrative excludes voices from the Global South, where digital colonialism is already reshaping economies without local consent or benefit-sharing mechanisms.