The Tax State After Labor

The economy is becoming more legible to machines and less legible to states. That inversion is the fiscal problem.

The modern state was built on a paradox it never had to explain.

It governed millions of people it could not directly observe, their incomes, transactions, assets, and behavior mostly hidden inside households, firms, and private relationships. It taxed a vast and opaque economy. And yet it funded itself, for most of a century, at rates that built welfare states, militaries, infrastructure systems, and public research capabilities that no previous political form had achieved.

It could do this because of a single administrative invention that most people experience as tedium: the paycheck.

The wage was not only the mechanism through which workers received income, as this series has argued. It was the mechanism through which the state could find workers at all.

The payroll system was one of the most effective information machines ever built into a capitalist economy.

Employers reported wages before workers filed returns. Taxes were deducted at source. Social insurance contributions moved automatically. The state did not need to chase income because the employment relationship itself was a standing disclosure requirement.

What is coming under stress in the AI economy is not only a tax rate problem, or even a conventional tax base problem. It is an information problem. The wage worked as a fiscal instrument because production was legible. It moved through employers, who were registered, accountable, and already processing payroll. Output had addresses. The state knew where to look.

AI reorganizes production in ways that make it progressively less legible to that architecture, not by fraud, not by evasion in the ordinary sense, but by structural drift. The economy is becoming more legible to machines and less legible to states. Call it the legibility inversion. That is the problem at the center of the fiscal question.

And it arrives at the worst possible moment: when states must fund the management of surplus populations, the stabilization of legitimacy, and the transition costs of an economy remaking itself, all while the payroll-based revenue system that funded everything is quietly losing its grip.

The Payroll System as Information Architecture

To understand what is being lost, it helps to understand what the payroll system actually was.

Modern fiscal states were built on a series of compounding information advantages. Wages were visible by design: they moved through registered entities with legal obligations to report. The employer became an unpaid arm of the revenue authority. The state’s information asymmetry, it must know what you earned before it can tax it, was solved, for wage earners, not by auditing but by delegation. The counterparty to the wage transaction already had independent legal duties to report it.

This made collection extraordinarily efficient. Evasion required collusion between employer and employee, which the threat of audit on both sides largely suppressed. The information was timely, deducted before the worker ever handled the full sum. And it was comprehensive: payroll covered not only income tax but social insurance, health contributions, unemployment premiums, and pension levies. The fiscal state built its entire welfare architecture on top of this infrastructure. The dependence persists: personal income taxes and social security contributions still supply roughly half of all tax revenue across the OECD, and in the United States, individual income and payroll taxes together account for about 85 percent of federal receipts. [1]

E. P. Thompson’s account of industrial time-discipline, the way the clock-time of wage labor reorganized the moral experience of daily life, captures one dimension of the payroll system’s power. But it also reorganized the state’s administrative capacity. The wage did not merely train workers to inhabit time differently. It trained the state to find its citizens through the employer, which meant the state could fund public goods without building a surveillance apparatus capable of reaching every private transaction directly. [2]

That is the arrangement now under stress. Not because employers are hiding wages more aggressively. But because the relationship between output and employment is loosening, and with it the coverage of the fiscal information architecture that depended on it.

The Inversion

The AI economy is producing an asymmetry the tax state is not built to handle: the economy is becoming more legible to algorithmic systems and less legible to fiscal states.

Consider what the large platform and AI companies know about economic activity. They see transactions before they become taxable events. They process payments before they become reportable income. They observe labor before it becomes employment: gig work, creator revenue, freelance contracts, platform selling. They hold the data on which the productive system increasingly depends. Their systems can classify, route, price, and rank economic actors in real time at enormous scale.

The state, by contrast, must wait. It waits for annual returns. It waits for audit cycles. It waits for treaty negotiations with other jurisdictions. It builds enforcement capacity measured in years while the transactional infrastructure it is trying to reach moves in milliseconds.

This is not only a matter of speed. It is a matter of architectural position. The fiscal problem is not that the state has lost money. It is that the state has lost position. The payroll state sat inside the main transaction of industrial capitalism: employer, worker, wage, withholding, contribution, benefit. The fiscal system was embedded directly in the relationship that organized production. The AI economy moves the decisive transaction elsewhere. The platforms sit between economic actors and their markets. They own the intermediary layer where value is generated, recorded, and routed before it ever surfaces in a form the fiscal state can reach. A payment processed through a platform’s rails, attributed to IP held in one jurisdiction, routed through a cloud layer in another, and sold to users in a third has already passed through more private information architecture than most tax authorities will ever inspect.

The problem is not opacity in general. Someone can see the economy very clearly. It is just no longer the public authority.

AI intensifies this because it concentrates value further upstream. The surplus of synthetic production accumulates in compute estates, model IP, cloud infrastructure, and the interface layer through which users and markets interact. These are not factories with a fixed address. They are positional assets whose value is real but whose location is a question of legal architecture, not physical geography.

The OECD’s Pillar Two global minimum corporate tax, a floor of fifteen percent, was the most serious international attempt to slow base erosion. It was designed for the platform era. The AI era may make it look modest. The gap between where value accumulates and where states can extract it is not a consequence of inadequate rate-setting. It is a consequence of mismatched architectures. [3]

The Paycheck Thins

While the surplus migrates upward into structures the state cannot easily reach, the base it can reach is contracting.

Labor’s contribution to production does not need to collapse for the payroll-based fiscal system to weaken. It only needs to drift. Firms producing the same output with fewer junior employees are not dramatic events. They are allocation decisions spread across thousands of hiring cycles, quietly not replacing people who leave, compressing workflows that previously required several people into one, using AI to eliminate the first-draft function that once justified the entry-level hire.

Each individual decision is invisible at the macro level. The cumulative effect is an erosion of the coverage of the payroll system, not a cliff, but a slope. The early-career employment decline in AI-exposed occupations that opened this series, around sixteen percent relative to less-exposed peers, reads differently from a fiscal seat. If that decline holds across professions and cohorts, it lands where payroll was historically most complete: formal, reported, mid-tenure employment in professional and analytical roles.

The gig economy was the preview. Platform work replaced employment contracts with contractor arrangements, which are structurally less covered by payroll systems. Self-employment, project-based work, creator monetization, and informal service provision all represent forms of labor that the fiscal architecture treats less cleanly: more evasion, more underreporting, more reliance on the individual’s own disclosure rather than the counterparty’s.

AI does not only add to this by eliminating some jobs. It adds to it by making the surviving work less structurally legible to payroll. The worker who supervises AI outputs rather than producing first drafts, the professional whose billing is now half what it was because clients do their own AI-assisted analysis first, the contractor whose project work has fragmented across platforms: none of these appear as unemployment. They appear as reduced coverage.

The state built its obligations around an economy where stable employment was the normal condition of working-age adults. That assumption is becoming less true every year, not through rupture but through structural drift.

The State Inherits What Firms No Longer Need

The fiscal problem after labor is not only that revenue weakens. It is that expenditure pressure rises as revenue weakens.

A private firm can reduce headcount and improve its margin. It can automate junior workflows, compress the professional layer, optimize for output per employee. From the firm’s perspective, these are efficiency gains. From the state’s perspective, they are cost transfers.

The displaced junior analyst, the professional whose billing rate has compressed, the credential-holder who cannot find the entry-level role that was supposed to follow from the education the state subsidized: they do not disappear from the political system. They remain citizens. They still require healthcare, housing, income support, and public order. Their claims on the state do not diminish because the economy has decided it needs less of them.

The economy may need fewer workers. The state does not need fewer citizens.

This is the fiscal expression of the surplus-human problem the previous essay described. Containment, transfers, credential extension, therapeutic systems, platform participation, is not free. It has to be funded. And it has to be funded from a system whose principal revenue base is the employment relationship, which is simultaneously the relationship being compressed.

The state that manages an AI economy is being asked to spend more on its surplus population while extracting less from the system producing the surplus. That is not merely a fiscal tension. It is a structural contradiction that no rate adjustment can close.

The Ground That Cannot Be Offshored

States will adapt. They always do, imperfectly and belatedly. The fiscal history of capitalism is partly a history of states chasing value wherever it migrates: from agricultural rents to industrial capital to platform revenues to whatever comes next.

The emerging logic of post-labor taxation follows a single thread: find what cannot be moved, and tax it.

Compute is the most promising candidate, for the same reason land was the original tax base. The AI compute estate, chips, data centers, energy systems, cooling infrastructure, fiber corridors, is physically anchored in ways that the mobile IP and transfer-pricing structures of the platform era were not. A data center cannot be relocated to Ireland through a licensing agreement. It requires land, grid access, water, permits, and a long-term capital commitment to a specific geography. It is visible, assessable, and immovable.

And it matters fiscally not only because it is hard to move. It matters because it can be measured. Compute has meters: energy draw, chip deployment, data-center capacity, inference volume, cloud contracts. The payroll system succeeded because wages were countable at the point of payment. A post-labor fiscal system will need an equivalent point of measurement, some machine-readable proxy for synthetic production. The question is not only where value is created. It is where value becomes visible enough to claim.

Measuring where computation happens is not the same as deciding computation should be taxed. The meter locates synthetic production. It does not settle what the state ultimately reaches, whether rents, profits, revenues, or transactions. Reading the two as one invites the crude version of the idea, a flat charge on raw compute, when the harder move is locating synthetic production at all.

Several European countries have introduced or are considering data-center energy levies, framed sometimes as carbon pricing, sometimes as infrastructure contributions from systems that impose significant costs on local grids and water supplies. The fiscal logic beneath both frames is identical: extract from the physical substrate of synthetic production because that substrate has an address.

Digital services taxes, levies on revenues generated from users in a jurisdiction regardless of where the firm books profit, represent a cruder instrument, one that the United States has consistently opposed when applied to American firms. But they contain the same insight: if profit can be located anywhere, tax the consumption it depends on, which cannot be moved.

The most ambitious proposals involve taxing compute capacity directly, a severance levy on AI capability operated within a jurisdiction, analogous to the resource extraction taxes applied to oil or minerals. The precedent for this framing is Norway’s sovereign wealth fund: the premise that petroleum rents belong partly to the public because petroleum is a common inheritance, and that private extraction from common inheritance carries a public obligation. The inheritance grammar proposed earlier in this series for post-wage income applies here to the fiscal question: AI surplus is built on public science, public law, public infrastructure, and collective data. Extracting it without a public return is not merely inefficient. It is private appropriation from a civilization-built asset base. [4]

Sovereign AI fund proposals, in various forms across Europe, the Gulf, and parts of Asia, represent the ownership version of this logic: rather than taxing AI surplus after private accumulation, the state acquires equity stakes in AI infrastructure as a condition of market access, subsidization, or regulatory clearance. The state becomes a co-owner rather than a creditor.

None of these instruments is fully formed. Each generates its own political economy of resistance. Tax too aggressively and the infrastructure migrates. States compete for data centers with subsidies and streamlined permitting, which creates a race to the bottom that can leave the public net-negative on extraction. Tax the wrong surface, revenues rather than surplus, transactions rather than value, and dominant firms absorb the cost while smaller actors cannot.

The danger of bad extraction is not only fiscal inefficiency. It is that the tax reproduces the concentration it claims to correct. Complex, compliance-heavy levies favor the largest firms, which can absorb administrative costs and structure around whatever instrument the state deploys. A poorly designed AI tax can become another form of the barriers to entry that already make the compute estate inaccessible to most actors.

The Objection From History

The obvious objection is that none of this is new. States have taxed novel economic forms before. They taxed railroads, factories, oil, corporations, financial income, and eventually platforms. Fiscal systems lag transformations and then catch up. Why should AI be different?

The objection deserves a real answer, because it is half right. States will adapt here too; the previous section is a catalogue of the early attempts. What the objection misses is that AI weakens two fiscal architectures at once. It weakens payroll visibility from below, because less production has to pass through stable employment. And it weakens corporate territoriality from above, because more surplus accumulates in mobile IP, cloud contracts, model access, and interface control. The state is squeezed from both directions: the worker becomes less legible as a worker, while the surplus becomes less locatable as profit.

Every previous fiscal adaptation chased value after it moved. This one has to rebuild the instrument by which value becomes visible at all. Railroads had track. Factories had chimneys. Oil had wells. The payroll system had the employment contract. The AI economy’s equivalents exist, but they report to private systems first.

The sharper form of the objection presses harder: employers were themselves conscripted once, turned into unpaid arms of the revenue authority, and platforms, payment processors, marketplaces, and cloud providers can be conscripted the same way. That is correct, and it is the likely path. But it concedes the mechanism rather than defeating it. The state has not lost the information in principle. It has lost the position from which the economy once reported itself without being asked, and rebuilding that position means turning a set of transnational, privately governed intermediaries into instruments of collection, as payroll once turned the employer.

That is a different kind of problem, and rate-setting does not solve it.

The Fiscal Constitution of AI

Underneath the technical questions, compute levies, energy surcharges, digital services taxes, transfer pricing enforcement, sovereign wealth funds, is a political question the fiscal crisis will eventually force into the open.

What does the public get from a system that has learned to produce without needing as many of the public as it once did?

This is not, at base, a question about tax rates. It is a question about the relationship between production and membership. The progressive income tax was not only a revenue instrument. It was a political statement about the relationship between individual success and collective conditions, an acknowledgment that no wealth was purely private in origin. Payroll taxes funding social insurance were not only premiums. They were a statement about shared risk across the working population, a translation of the wage relationship into a social contract with temporal structure: you contribute while you can, you claim when you cannot.

The fiscal state after labor will need to make comparable political statements about AI surplus. Not because the old statements were always correct, or because the institutions they built were always efficient, but because a productive system that extracts large surplus without paying for the collective conditions it depends on, public science, public infrastructure, educated workforces, stable political environments, the accumulated data of millions of private lives, is extracting from civilization without returning to it.

The fiscal constitution of the AI era is already being written, badly and in fragments. Energy levies, minimum taxes, transfer pricing rules, digital services taxes, sovereign fund proposals: these are early drafts. They will require many revisions. The largest firms will extract carve-outs. The political process will lag the economic transformation. The instruments will be crude relative to the complexity of what they are trying to reach.

That is how fiscal constitutions have always been written. The income tax was crude in its first versions. Payroll taxes took decades to reach their mature form. Corporate taxation still has not resolved the question of where profit is located in a multinational firm, a question the platform economy made worse and the AI economy is making harder still.

But the question the fiscal state is now asking is sharper than it has been in decades. Not: how do we tax income? That question assumed a world where income was attached to labor, and labor was attached to employment, and employment was attached to a jurisdiction. All three of those attachments are loosening simultaneously.

The sharper question is: who owns the ground?

This series has already answered it. In agrarian economies the ground was land: visible, immovable, taxable. In industrial economies it was capital. In the AI economy it is compute, expensive to build, slow to replicate, physically anchored, and the precondition for synthetic production. The state that can establish a public claim on what synthetic production generates from a publicly built inheritance has a revenue base. The state that cannot will be left funding containment with instruments designed for an economy that no longer exists.

But locating the ground is the easier half of the problem.

The harder half is the one this essay began with.

The wage was the state’s information system as much as its tax base. It made citizens legible to fiscal authority, social insurance systems, and democratic institutions. The AI economy makes citizens more legible to platforms and less legible to states.

The fiscal reconstitution of the AI era is ultimately about reversing that inversion, not to restore the old information architecture, which will not come back, but to establish a new one capable of translating synthetic production into public revenue.

Whatever instruments emerge, levies, funds, equity stakes, minimum taxes, they will only work if the state can see what it is taxing. The payroll system did not succeed because its rates were clever. It succeeded because it made the economy report itself.

That is the rebuild the fiscal state actually faces. Not a new rate, and not even, in the end, a new base. A new sensor.

The state that learns to read synthetic production will fund itself inside the AI economy.

The state that does not will govern an economy it can no longer see.

Notes

[1] OECD, Revenue Statistics 2025, OECD Publishing, 2025: in 2023, social security contributions accounted for 25.5 percent and personal income taxes for 23.7 percent of total tax revenues on average across OECD countries. https://www.oecd.org/en/publications/revenue-statistics-2025_3a264267-en.html. For the United States: Congressional Research Service, “Overview of the Federal Tax System in 2024,” R48313: in fiscal year 2023, the individual income tax generated 49 percent and payroll taxes 36 percent of federal revenue. https://www.congress.gov/crs-product/R48313

[2] E. P. Thompson, “Time, Work-Discipline, and Industrial Capitalism,” Past & Present 38 (1967): 56-97. Thompson’s account of the moral transformation of time under industrial capitalism captures how the wage reorganized not only compensation but the entire temporal architecture of social life, including, as a secondary consequence, the administrative legibility of workers to fiscal institutions.

[3] OECD, Tax Challenges Arising from the Digitalisation of the Economy, Global Anti-Base Erosion Model Rules, Pillar Two, 2021. https://www.oecd.org/tax/beps/tax-challenges-arising-from-the-digitalisation-of-the-economy-global-anti-base-erosion-model-rules-pillar-two.htm

[4] On the Norwegian precedent: Norway’s Government Pension Fund Global, established 1990, now manages approximately $1.7 trillion in assets accumulated from petroleum revenue. The inheritance framing, that common assets generate a public claim, is the conceptual precedent for applying similar logic to AI-generated surplus. On the emerging framework for AI-era public finance: Anton Korinek and Lee Lockwood, “The Future of Tax Policy: A Public Finance Framework for the Age of AI,” Brookings Institution, February 2026, drawing on their working paper of January 8, 2026. https://www.brookings.edu/articles/future-tax-policy-a-public-finance-framework-for-the-age-of-ai/. On the state-as-co-owner model: the European Commission’s InvestAI initiative, announced February 2025, targets 200 billion euros in mobilized public-private AI investment, including a 20 billion euro facility for AI gigafactories structured as a layered fund with a public first-loss tranche; the Commission’s technological sovereignty package of June 2026 proposes a European equity capacity to take stakes in strategic technology firms.