The traditional corporation thrives on order. It needs predictable demand, stable supply chains, enforceable contracts, reliable labor markets, and incremental innovation. Factories run on schedules. Retail depends on foot traffic and seasonal patterns. Banks require functioning courts and solvent counterparties. The entire edifice of mid-to-late 20th-century corporate capitalism was built on the assumption that relative stability—punctuated by manageable recessions—would allow capital to compound over decades. Chaos was a risk to be hedged against, not a business model.
A new class of oligarchs has inverted that logic. They have discovered that certain forms of systemic disruption generate outsized returns precisely because they destroy the conditions under which ordinary corporations compete. Pandemics empty the streets and funnel commerce through a handful of digital platforms. Wars generate torrents of real-time data and multi-billion-dollar government contracts for predictive systems. Artificial intelligence, trained on the disorder these shocks produce, then locks in the advantage by automating decision-making at scales no traditional firm can match. The result is not merely higher profits for a few companies. It is a structural migration of power away from the ordered, competitive, regulated corporate world toward platform monopolies, cloud rents, and algorithmic control.
Jeff Bezos and Amazon extracted tens of billions from the COVID-19 lockdowns. Peter Thiel’s Palantir has turned the battlefields of Ukraine, Gaza, and successive Middle East conflicts into both training grounds and revenue engines for its AI platforms. These outcomes are not accidents of timing. They reflect powerful incentives and, in the case of several key figures, an explicit ideology that celebrates monopoly, disruption, and the transcendence of older constraints. What is emerging looks less like free-market capitalism and more like the technofeudalism described by Yanis Varoufakis or the surveillance capitalism diagnosed by Shoshana Zuboff—systems in which a small number of owners extract rents from the rest of society while the public absorbs the costs of permanent instability.
Pandemic as Shock Therapy: Amazon’s Windfall
When COVID-19 forced populations into isolation in early 2020, physical retail collapsed almost overnight. Shopping malls emptied. Restaurants closed. Supply chains for ordinary goods fractured. Into that vacuum stepped Amazon. Its warehouses, delivery networks, and cloud infrastructure became the default operating system of daily life for hundreds of millions of people. The company’s revenue and profits soared. Jeff Bezos’s personal fortune, already immense, expanded by tens of billions of dollars in a matter of months. Analyses from the period documented that Bezos added roughly $75 billion to $100 billion to his net worth during the acute phase of the pandemic. One widely cited calculation showed his wealth increasing by the equivalent of more than $10 million per hour while Amazon warehouse workers received hazard pay that, on an hourly basis, amounted to less than a dollar in many cases.
This was not simply a company responding nimbly to changed consumer preferences. It was a classic instance of what Naomi Klein has long called the shock doctrine. In The Shock Doctrine, Klein mapped how elites exploit moments of collective disorientation—wars, natural disasters, economic collapses, or public-health emergencies—to push through transformations that expand private power and shrink the public sphere. During the pandemic she identified a specifically high-tech variant she termed the “Screen New Deal.” Under the cover of emergency, governments and corporations accelerated a shift toward remote work, telehealth, remote education, contactless payments, and pervasive digital monitoring. The privileged could isolate in relative comfort while relying on the very platforms that were simultaneously consolidating control over data, logistics, and communication. Amazon, Google, and others positioned themselves as indispensable partners to states scrambling to manage the crisis. Public money, regulatory forbearance, and urgent demand flowed toward firms already positioned to monetize isolation.
Amazon did not create the virus. It did not need to. Its pre-existing scale, its ownership of critical logistics infrastructure, and its dominance in cloud computing through Amazon Web Services allowed it to convert societal shock into permanent market share. Traditional retailers that depended on physical stores, stable consumer patterns, and competitive pricing were hollowed out. The ordered world of brick-and-mortar competition—imperfect, often exploitative, but still plural—was partially dismantled. In its place rose a more centralized system in which Amazon extracts commissions from third-party sellers, controls vast flows of behavioral and logistical data, and operates the computational layer on which an increasing share of the economy depends.
Yanis Varoufakis has argued that platforms of this type no longer function as conventional markets at all. They operate as digital fiefs. Sellers pay for access to the platform’s audience and fulfillment network. Consumers generate continuous streams of data with every search, click, and purchase. The platform owner collects rents rather than competing on equal terms with rivals. The pandemic dramatically accelerated this shift by collapsing many of the remaining alternatives. What looked like efficient adaptation was, in structural terms, the transfer of economic power from a relatively competitive commercial sphere into a more hierarchical, rent-extracting one.
The human cost was unevenly distributed. Amazon hired hundreds of thousands of additional workers to meet surging demand. Many of those workers labored under intense algorithmic monitoring, productivity quotas, and elevated risk of infection. Reports documented outbreaks in warehouses even as the company’s market capitalization climbed into the trillions. Hazard pay was temporary and modest relative to the wealth created. The contrast illustrated a broader pattern: the same shock that produced extraordinary returns for platform owners imposed intensified precarity on the labor force that kept the system running.
War as Data Engine and Revenue Stream: Palantir’s Model
If pandemics delivered Amazon its decisive breakthrough, sustained geopolitical conflict has performed a similar service for Palantir. Co-founded by Peter Thiel with early backing from the CIA’s venture capital arm In-Q-Tel, the company specialized from the beginning in integrating disparate data streams for intelligence and military purposes. Its core platforms—Gotham, Foundry, and later the Artificial Intelligence Platform—were designed to fuse satellite imagery, signals intelligence, open-source information, and other sources into actionable operational pictures. Over time these tools have been deployed in Ukraine, in support of Israeli military operations, and within U.S. targeting systems including Project Maven.
Palantir’s commercial trajectory has tracked the intensity of conflict. The company has secured multi-billion-dollar agreements with the U.S. Department of Defense, including an Army enterprise arrangement potentially worth up to $10 billion over a decade. It entered a formal strategic partnership with Israel’s Ministry of Defense in early 2024 for “war-related missions,” expanding the use of its software during operations in Gaza and beyond. Reporting has linked Palantir tools to targeting processes that compress the time between identification and strike—what company executives have described as optimizing the “kill chain.” In Ukraine, officials and executives have stated that Palantir software has been responsible for a significant share of targeting decisions. Similar patterns appear in other theaters.
CEO Alex Karp has been unusually candid about the company’s orientation. He has framed its technology as providing democratic states with decisive advantages against authoritarian adversaries and has celebrated periods of elevated geopolitical tension as moments of growth. The company’s stock has responded accordingly. Conflict is not treated as an unfortunate external condition to be endured; it is an environment in which the product is validated, refined, and sold at premium prices.
Peter Thiel’s own writings supply an ideological frame. In a widely discussed 2014 essay and subsequent lectures, he argued that competition is for losers. Successful businesses, he maintained, should aim for monopoly because perfect competition drives profits toward zero while monopoly allows the durable capture of value. Capitalism, in this view, is not synonymous with competition; the two are in tension. The goal is to escape the brute struggle of rivals and secure a position from which rents can be extracted over long periods.
Palantir’s trajectory fits the logic. Wars and security crises generate the messy, high-stakes data sets that improve AI models. Governments under pressure pay for tools that promise faster, more precise decision-making. Traditional defense contractors, constrained by slower procurement cycles and political oversight, are less agile. Palantir presents itself as the data-driven alternative. Chaos becomes the medium in which the monopoly advantage is demonstrated and locked in.
Critics, including Varoufakis, have pointed to the feedback loop this creates. Algorithms trained on the movements of populations under bombardment can later be marketed for civilian “emergency management,” border control, or urban policing. The same firms that profit from kinetic conflict expand their domestic footprint in surveillance and administrative systems. Cloud capital accumulated in war zones migrates into the everyday governance of peaceful societies.
From Disaster Capitalism to Technofeudalism and Surveillance Capitalism
Naomi Klein’s framework remains foundational. The shock doctrine describes a recurring pattern in which crises are used to impose transformations that would face democratic resistance under ordinary conditions. The pandemic and successive wars have functioned as successive shocks. Each has further concentrated wealth and infrastructural control in a small set of technology platforms while stressing or displacing traditional corporate forms that depend on relative social stability, physical presence, or competitive markets.
Varoufakis pushes the analysis further with the concept of technofeudalism. In his account, the decisive historical shift is from profit extracted through the production and sale of commodities in competitive markets to rent extracted through ownership of cloud capital and algorithmic platforms. Amazon does not merely sell goods; it owns the digital space in which buying and selling increasingly occur and takes a substantial cut. Palantir does not merely analyze data; it constructs systems upon which governments and corporations become dependent. Artificial intelligence intensifies the dynamic because the leading models require concentrations of compute, proprietary data, and capital that only a handful of players can assemble. The result is a new hierarchy in which platform owners function more like feudal lords extracting tribute than like classical capitalists competing on price and quality.
Shoshana Zuboff supplies the behavioral and epistemic layer. In The Age of Surveillance Capitalism and subsequent work, she describes a system that claims human experience as free raw material, transforms it into behavioral data, manufactures prediction products, and sells those products into markets that shape future behavior. The ultimate goal, she argues, is not merely to predict what people will do but to automate them. Artificial intelligence represents the continuation and expansion of this logic with new technical means. When these capabilities are fused with state power through contracts, data-sharing arrangements, and dual-use technologies, the outcome is an asymmetry of knowledge and power that ordinary democratic institutions are poorly equipped to check.
These three diagnoses—shock doctrine, technofeudalism, and surveillance capitalism—are complementary rather than contradictory. Crises create the openings. Platform ownership converts those openings into durable rent streams. Surveillance and prediction technologies convert human life itself into the raw material of the new accumulation regime. AI is the force multiplier that promises to make the arrangement self-reinforcing.
Ideology, Incentives, and the Flight from Order
It is possible to describe these developments as the unintended consequence of technological change and geopolitical accident. That description is incomplete. Structural incentives are powerful, but ideology and deliberate strategy amplify them. Thiel’s insistence that competition is for losers is not an isolated remark; it is consistent with a broader Silicon Valley current that treats disruption as both inevitable and desirable. Accelerationist tendencies within the tech elite hold that technological progress, particularly in AI, should be pushed forward as rapidly as possible, with social dislocation accepted as the necessary price. In this worldview, the ordered corporate capitalism of the late 20th century—with its labor protections, regulatory agencies, antitrust constraints, and incremental product cycles—appears as an obstacle to be overcome rather than a system to be preserved.
The practical effect is a migration of economic power away from firms that require social stability toward those that can monetize instability. Amazon’s logistics and cloud empire expands when people cannot safely leave their homes or when other commercial channels are disrupted. Palantir’s valuation and contracts rise when conflicts generate data and demand for predictive targeting. Leading AI laboratories and hyperscale cloud providers absorb capital and talent that might otherwise flow into more distributed forms of innovation or into industries that still depend on physical production and stable employment. Traditional corporations that once dominated their sectors find themselves becoming customers or dependents of the new platform lords.
Thiel has at times expressed skepticism about AI’s centralizing tendencies, describing it in one talk as potentially “communist” in its concentration of power in a few large systems. Yet the company he co-founded and continues to influence is a primary beneficiary of precisely that concentration in the military and intelligence domains. The tension is revealing. Public warnings about authoritarian risk coexist with private and corporate strategies that advance the very infrastructures of control being cautioned against.
The Human and Institutional Costs
Ordinary people experience the transition as intensified precarity layered on top of older forms of exploitation. Warehouse and delivery workers during the pandemic faced elevated health risks and algorithmic discipline. Soldiers and civilians in conflict zones become data points in systems they neither control nor fully understand. Workers across a widening range of occupations confront the prospect of AI-driven displacement without corresponding social insurance or democratic voice in the design of the systems replacing them. Public institutions—schools, hospitals, police departments, military commands—become clients of the same platforms that shape information flows, behavioral prediction, and administrative decision-making.
The older corporate order, for all its well-documented flaws, operated within a framework of nation-states, labor law, antitrust precedent, and competitive pressure that imposed some limits on pure concentration. The emerging system concentrates knowledge, computational capacity, and infrastructural control in fewer hands while externalizing social, ecological, and political costs. Data centers consume enormous quantities of electricity and water. Surveillance expands into more domains of life. Democratic oversight lags behind technical capability. The capacity for collective self-determination shrinks as more decisions are delegated to proprietary algorithms whose training data and objective functions remain opaque.
Klein, Zuboff, and Varoufakis, despite differences in emphasis and political orientation, converge on a common warning. Without deliberate political intervention aimed at the ownership and governance of these infrastructures, the logic of shock, rent extraction, and behavioral prediction will continue to erode the space for democratic agency. The ordered corporate world is not being reformed; it is being superseded by something more hierarchical and less accountable.
Historical Parallels and the Stakes of the Present
History offers partial analogies. Previous transitions of economic power—from agrarian to industrial, from industrial to managerial capitalism—were accompanied by political struggle over the terms of the new order. Labor movements, regulatory states, and democratic institutions emerged in response to the concentrations of power that industrial capitalism created. The current transition is occurring with unusual speed and under the cover of successive emergencies that make democratic deliberation more difficult. The tools of prediction and control are more sophisticated than those available to earlier elites. The fusion of private platform power with state security apparatuses is tighter.
The oligarchs who profit from chaos do not need to orchestrate every pandemic or every war. Structural incentives and ideological predisposition are sufficient. Platforms that scale with disorder will systematically outcompete those that depend on order. AI systems that train most effectively on the data of crisis will improve fastest during crises. Governments under pressure will purchase the tools that promise restored control. The result is a self-reinforcing cycle that moves society away from the relatively ordered, if imperfect, corporate capitalism of the late industrial era toward a more hierarchical, algorithmically mediated arrangement.
Whether one prefers the language of technofeudalism, surveillance capitalism, or simply the rise of a new oligarchy, the empirical pattern of the last half-decade is clear. Pandemics enriched Amazon and accelerated the concentration of commercial infrastructure. Wars have enriched Palantir and accelerated the fusion of AI with military decision-making. Artificial intelligence is the force multiplier that promises to make the new arrangements durable. The corporatized world that required relative stability is being displaced by one that thrives on its opposite.
The question is no longer whether disruption can be highly profitable for a narrow set of actors. That has been demonstrated. The question is whether the broader public will continue to accept a future in which the primary beneficiaries of chaos also control the predictive systems, the data infrastructures, and the administrative tools through which society responds to the next shock. The evidence from the pandemic and from successive conflicts suggests that the answer is being written in real time—by the platforms that claim to be solving the very problems their business models help amplify.
The ordered world is not returning by itself. The oligarchs of chaos have little incentive to restore it. Any alternative will require political organization capable of contesting the ownership and purpose of the infrastructures now being built. Without that contest, the transition from corporate capitalism to platform oligarchy will continue under the banner of technological inevitability, and the costs will continue to be borne by those least able to exit the systems being constructed around them
The choice is still open, but the window is narrowing with every new crisis that is converted into private infrastructure and every new algorithm that learns from the disorder of the last.
