The BomaliQ Corporate Platformization Risk Index
A measure of the unhedged financial liability of tokenization exposure.
I recently attended Carissa Véliz’s webinar for the publication of her book “Prophecy: Predictions, Power, and the Fight for the Future, from Ancient Oracles to AI.” Somehow, it reminds me of all the fluff and deceptive promises of neuromarketing, a topic I studied during my PhD and in the years that followed. Neuromarketers used the same lever of fear to impose a future they were eager to see, where the brain, and nothing else, was the definitive oracle to predict consumer behaviour. Investing in fMRI and other EEG systems to probe neuronal firing in consumers’ brains exposed to the latest yogurt packaging was a precondition for success for all retailers and consumer goods companies. Does anyone remember this period? Does anyone still use neuromarketing methods to drive their business operations? Your silence speaks volumes about the situation.
Meanwhile, decision-makers are still obsessed with anticipating and predicting the future to conduct and manage the present. The market has addressed this vivid need for prophecies and crystal balls through services that are more or less valid and reliable, ranging from strategic intelligence and behavioural economics to the least avowable yet popular fortune-telling. Ironically, the more control we try to exert over reality, the more reality escapes us, creating new material conditions that demand new surveillance strategies. As true as madness requires believing that the same causes will produce different outcomes, the infinite cycle of control and prediction inexorably produces the same conditions of anxious unknow.
At BomaliQ, we approach the big claims of radical transformation from the past with suspicion and instead consider change a long, steady process rather than a series of deep, unprecedented disruptions. Therefore, rather than paying tons of money to try to figure out the future, we believe that looking at the past we know is a more intelligent and reliable way to navigate the present.
Although it sounds ironic, to say the least, or even completely crazy and counterintuitive to champions of capitalism, the current state of the SaaS, cloud, and AI industry is taking a shape that has already happened in the past: the Kolkhoz—the cooperative agricultural enterprise in the former Soviet Union where peasants pooled their land, livestock, and equipment into a single industrial-scale collective farm.
We regularly refer to the state of the tech industry as the Silicon Kolkhoz (attentive readers would have noticed that the very name of this insights series is… Silicon Kolkhoz!), and this article is no exception. We will show how kolkhozes extracted value in the USSR and how this blueprint is now unfolding in the tech industry, capturing a bit more value every day from SaaS client enterprises.
Davai poydyom!
The Cardsharps, Caravage (around 1594). "The New Cheaters: How AI Tokenization Has Reinvented Price Asymmetry."
Historical blueprint of the Silicon Kolkhoz
Contrary to the feudal system that Yanis Varoufakis uses as a historical comparison for the current tech industry, value extraction in the Soviet system did not occur post-production through traditional tithe or monetary tax but was woven directly into the very architecture of labour and tooling. There are three lessons to learn from this historical parallel.
Lesson 1
In Stalin’s USSR, the Kolkhoz did not own its heavy production tools. Tractors, harvesters, and complex machinery belonged to the State, which consolidated them into centralized entities called Machine and Tractor Stations (thereafter: MTS). To plow and harvest, the Kolkhoz was forced to rely on its regional MTS. Instead of leasing machinery for cash, the MTS demanded payment in kind, extracting a fixed share of the harvest (often between 20% and 30%). Attentive readers (yes, again. That’s just the university professor in me coming out, ignore me) would have noticed that this MTS system is the precursor to modern hyperscalers (AWS, Azure) and agentic platforms (ServiceNow Action Fabric, Salesforce Agentforce). Today’s terrestrial capitalists (as opposed to cloud capitalists) mirror the Kolkhoz: they lack the means to execute AI computation independently—Nvidia hardware is too expensive, and foundational LLMs are inaccessible. Consequently, they must call upon the platform’s “tractors” and pay a volumetric toll computed via tokens and execution assets—the return of the MTS infrastructure toll.
Lesson 2
The Kolkhoz peasant did not receive a fixed salary. The mechanism of exploitation worked in reverse. As soon as the harvest was complete, the Soviet State took priority through compulsory deliveries. It purchased a share of the yield at artificially low State-set prices, amounting to de facto confiscation. What remained after the State’s share and the MTS toll was distributed among the peasants using a point system called Trudoden (i.e., labour-day). Often, after infrastructure deductions, the remainder was zero. The peasant had worked all year for nothing. In today’s tech market, the agentic AI platform positions itself as an intermediary, optimizes the operational flow, and takes its cut first via commissions and API fees. The client enterprise (the terrestrial capitalist) absorbs operational costs, payroll, and liabilities, while the actual profit margin is siphoned at the source by the technological infrastructure.
Lesson 3
To avoid starvation, Kolkhoz peasants were permitted to cultivate a minuscule private plot of land around their homes for subsistence, such as a vegetable garden or a few chickens. Observing that these tiny private lots were highly productive and kept the peasantry alive, the Soviet State decided to tax them heavily. Peasants were required to pay a fixed tax in meat, milk, eggs, and cash—calculated not on their actual yield but on the physical size of their plot—a tax levied directly on their remaining autonomy. This is what the SAP-Nvidia OpenShell framework or Microsoft’s custom agent environments (Joule Studio) represent in today’s tech market. If a client enterprise attempts to emancipate itself by developing proprietary AI agents on its own local servers and open-source models, the platform moves to encircle that space. It enforces security licenses, governance audit gateways, and paid enterprise connectors. Autonomy is permitted, but only at an integration tax that keeps it linked to the broader ecosystem.
Back to the future
Why are terrestrial capitalist enterprises entering the Silicon Kolkhoz, only to be trapped in a cycle of panoptic surveillance and aggressive automation? Ed Zitron called out the Rot-Com Bubble, in which corporate leadership and venture capital try to hide the structural collapse of the overleveraged SaaS business model amid AI-driven disruption in software.
Between 2018 and 2022, private equity firms—blinded by the Zero Interest Rate Policy—piled into software, with SaaS acquisitions reaching $250 billion in 2021 alone. They bought thousands of niche SaaS companies with debt, operating under the delusion that recurring revenue would grow forever. But they were wrong. Today, the era of hyper-growth in software is over. Net Revenue Retention is plummeting, growth has flatlined, and private equity is sitting on tens of billions of dollars of overvalued SaaS companies it cannot sell or take public.
In this context, Gen AI is not a technological miracle but a financial panacea for a desperate tech elite. It gave venture capital a new narrative to inflate valuations, gave hyperscalers a way to offload over-allocated infrastructure, and gave struggling SaaS CEOs a marketing shield. The narrative that AI agents will seamlessly replace software is a myth designed to mask structural decay. While LinkedIn commentators perpetuate the narrative that AI is destroying SaaS, the tech industry is using the hype of magical automation to force traditional client corporations into deeper layers of dependency.
This operation depicts a besieged ecosystem in which legacy empires are burning through cash and debt. The Silicon Kolkhoz weaponizes AI hype to ensnare traditional enterprises deeper within its ecosystems, turning your corporate workflows into a platform-tethered utility where you pay per token for on-demand intelligence. It is time for traditional client corporations to stop buying marketing fluff and to see the algorithmic frontline as a highly leveraged, brutalist war for economic resources, in which they are currently bankrolling the losers.
Intelligence on tap
The shift from per-seat licensing to consumption-based tokenization is a predatory move to escape the physical limits of human scale. In the traditional SaaS model, revenue is tied to a physical reality: if a client company has 500 customer service agents, Salesforce or ServiceNow can sell only 500 seats. When an economy slows, a client company freezes hiring or lays off 10% of its workforce, and the SaaS provider’s revenue shrinks instantly. SaaS Net Revenue Retention is currently collapsing as corporate clients reduce seat counts to save money. The eternal growth story of SaaS hit a physical wall: they ran out of human heads to monetize.
SaaS companies cannot let this happen without reacting.
By shifting the billing model from “per seat” to “per token” and charging a micro-tax on every API call, search, prompt, click, or database query, the agentic AI platforms decouple their revenue from the number of human employees. Under this new paradigm, an agentic AI platform doesn’t need 500 human users to make money—in fact, it prefers fewer humans. Why? Because a single human agent can only click a mouse or answer a customer query so many times a day. Human labour has physical ceilings, biological needs, and contractual hourly limits. Conversely, an autonomous software agent can run thousands of automated tasks, cross-database searches, and algorithmic prompts per minute.
Every time an automated agent “checks” an invoice... Cha-ching! Token tax!
Every time it queries an LLM to draft an email... Cha-ching! Token tax!
Every time it pings an internal CRM to update a customer profile... Cha-ching! Token tax!
By replacing a fixed monthly human-seat fee with a variable, hyper-frequent transaction fee, the platform ensures that even if a company downsizes its staff, its tech bill can increase exponentially. The actions running through the platform are de facto limitless, and so is the potential revenue extracted from the client company.
Do the math. When a B2B platform convinces an enterprise to replace 100 middle managers with 500 autonomous agents, it drastically increases the volume of transactions on its network. While a human manager reviews an invoice once, an automated agent can query an ERP database 50 times a minute to optimize that invoice, cross-referencing it with 10 different microservices.
Software offered controllable operational costs. Tokenization turns it into a predatory utility—like electricity or water during a drought—where the vendor controls the meter, changes the price per token at whim, and profits from the sheer volume of digital friction. The platform is no longer incentivized to make software simple or efficient for a human user. It is now financially incentivized to maximize algorithmic friction. The more complex, chatty, and recursive an AI agent is—looping through prompts, re-evaluating data, and pinging APIs—the more money the platform extracts from the client’s balance sheet.
This is why companies like Klarna proudly declare they are cancelling their SaaS contracts: they realize that remaining tethered to a token-based B2B platform is a form of financial suicide. They are trying to build their own independent wells rather than paying a SaaS giant for every drop of water.
So, what?
At BomaliQ, we are not the diagnostic pathologist standing over the corpse of the tech industry, performing an autopsy to blow up marketing fluff and expose the macroeconomic reality. Instead, our research aims to map and score the Corporate Platformization Risk Index (CPR Index) to provide traditional client corporations with a measure of the unhedged financial liability of tokenization exposure. While traditional companies’ CFOs celebrate cutting human headcount, thinking they are optimizing their bottom line, our CPR Index proves they are trading a controllable cost for a highly volatile variable cost.
That is why our CPR Index:
Turns a macroeconomic critique into a practical corporate governance tool and analytical framework. We give a CHRO a tangible metric to monitor their organization’s dependence on agentic AI platforms and prevent operational and financial risks.
Looks inward at the client corporation. We focus on sovereign human capital governance and on how traditional client corporations can protect their operational culture, data sovereignty, and workforce from being turned into an agentic platform-tethered unit of production.
Connects financial metrics (ARR, TVPI, BDCs, debt) to the geopolitical and human friction on the ground to evaluate how intersecting political forces create operational vulnerabilities for a business.
Conclusion
Surrendering its operational logic to a B2B platform running on tokens is like handing over the keys to its cash flow. The vendor controls the token’s price, dictates the architecture that consumes those tokens, and effectively installs a digital water meter on every pulse of the company’s daily operations. Don’t be this company. Start measuring your exposure to tokenization and platformization.
About the Author & BomaliQ
This insight is authored by Mathieu Lajante, PhD, founder and principal scientist of BomaliQ Inc.
BomaliQ provides specialized strategic intelligence for the algorithmic frontline, helping corporate leaders navigate the behavioural and political frictions of corporate platformization.
Nature of Intelligence
The insights provided in this publication are based on the stress-testing of publicly available industry reports, market data, and proprietary analytical frameworks. This content is intended for informational and strategic signalling purposes only. While every effort is made to ensure the accuracy of the analysis, the algorithmic frontline is a volatile environment.
Limitation of Liability
The BomaliQ Silicon Kolkhoz does not constitute professional consulting advice, legal counsel, or a formal business diagnosis. Readers should not make critical strategic decisions based solely on this newsletter without a rigorous, organization-specific assessment. BomaliQ Inc. and Mathieu Lajante shall not be held liable for any business outcomes or losses resulting from the use of this general intelligence.