AI and the New Economic Order (3/3)

June 2025 

Navigating an Unstable Equilibrium

Whether AI fulfills its transformative promise or falls short of expectations, one reality is undeniable: the current system is under strain. The distribution of technological gains is profoundly unequal, institutions are ill-equipped to manage the pace of change, and public trust is fraying. What is at stake is not merely economic efficiency or innovation, but the very foundations of the social contract that underpins liberal capitalism.

We are entering a pivotal phase in the evolution of the global economy. On one trajectory lies the idealistic promise of a more productive, automated, and abundant future, where artificial intelligence augments human capabilities and unlocks new forms of value. On another, less stable path, lurk the risks of institutional drift, growing inequality, and political fragmentation. These are not certainties, but plausible outcomes in a system undergoing rapid transformation.

To navigate this inflection point wisely, policymakers and business leaders must confront three uncomfortable truths. First, productivity gains alone are not sufficient to ensure broad-based prosperity. Without deliberate mechanisms for inclusion, through wages, taxation, or public goods, growth can compound inequality rather than mitigate it. Second, the prevailing logic of shareholder capitalism may be ill-suited to an AI-driven economy, where marginal costs fall, labor demand shifts, and value creation becomes increasingly decoupled from employment. Rethinking incentives, governance, and the role of firms in society will be essential. Third, and most critically, existing institutional frameworks—fiscal, legal, and social, are not yet calibrated to the speed or scale of AI’s impact. In their absence, technological progress could just as easily deepen existing fractures as it could catalyze renewal.

The path forward will demand both imagination and restraint. Imagination to envision alternative economic models, shared ownership of AI systems, universal digital dividends, or the creation of public AI infrastructure. Restraint to avoid the excesses of speculative capital and unchecked technological deployment. Most of all, it will require political courage: to redefine the purpose of growth, to reimagine the role of work, and to affirm that the future must be shaped not by algorithms alone, but by human judgment, dignity, and design.

Who Captures the AI Dividend?
As artificial intelligence begins to reshape the contours of modern capitalism, a central question emerges with renewed urgency: who captures the dividend? While AI promises to generate vast economic surplus through efficiency gains, cost reductions, and new capabilities, its distribution is neither automatic nor equitable. The value it creates must ultimately be claimed, and where it flows will depend less on the technology itself than on the political economy that governs its allocation.

At the heart of this contest are two primary actors: capital owners and the state. On one side stand shareholders, venture capitalists, sovereign wealth funds, and institutional investors, those best positioned to extract returns by controlling the platforms, data, and intellectual property at the core of the AI economy. On the other side are governments, ideally representing the broader public, who wield the tools of taxation, regulation, and redistribution. The tension between these forces will shape the long-term equilibrium of the AI era, determining whether it leads to a more inclusive prosperity or entrenched inequality.

The State as Redistributor: Taxing the AI Dividend

In one scenario, governments confront the dislocations of AI head-on by raising taxes on corporations, capital gains, and autonomous systems. These revenues fund a stronger social safety net, universal basic income, lifelong education, and public investment in AI infrastructure. This pathway reasserts the state's role as arbiter of equity and counterweight to capital concentration. It envisions a 21st-century welfare state, equipped not only to redistribute income but to manage technological disruption.

The political implications are profound. A shift toward welfare capitalism could revive progressive movements and social democratic parties, especially in high-income democracies. Inequality becomes a policy target, not an unfortunate externality. However, this model is fragile without international cooperation. In a hypermobile capital environment, unilateral tax hikes risk capital flight and regulatory arbitrage. Global firms may offshore profits, restructure supply chains, or relocate entirely. To mitigate this, multinational tax pacts, like those proposed by the OECD, become vital.

The upside is macroeconomic stability. In a deflationary world where work contributes less to income, redistribution helps preserve demand, social cohesion, and political legitimacy. But if taxation is seen as punitive, innovation could slow, especially in frontier industries. The balance between inclusion and dynamism will be difficult to strike, and harder still to sustain.

Politically this model is under challenge and it seems its on its way out, given the massive antiglobization movement around the world

Passive Drift, Active Capital: The Risks of Fiscal Abdication

A second, more passive trajectory is beginning to emerge across parts of Europe. In this scenario, governments, paralysed by politics or constrained by ideology, resist undertaking the structural reforms demanded by an increasingly automated economy. Rather than rethinking fiscal foundations, they cling to legacy tax regimes and post-industrial welfare models. Early warning signs are already visible.

Europe’s fiscal architecture remains heavily dependent on labour taxation. In most EU countries, over half of public revenues still come from wage-based taxes, even as automation steadily displaces routine work in manufacturing, logistics, and services. In Germany and Italy, labour’s share of national income is declining, underscoring a broader transition: value is now generated by capital, data, and algorithms, yet tax systems remain designed for an industrial past. Despite growing debate around digital and AI taxation, few jurisdictions have developed robust mechanisms to capture revenues from intangible assets or autonomous systems.

Demographic pressures intensify the strain. Countries like Italy, Greece, and Germany are ageing rapidly, with the EU’s old-age dependency ratio projected to climb from 34% in 2022 to 57% by 2050. Pension obligations and healthcare costs are rising, but automation has yet to deliver the productivity gains necessary to offset these burdens.

Public debt is creeping upward. Italy’s debt hovers around 137% of GDP; France’s approaches 112%. Fiscal consolidation efforts have largely stalled amid post-pandemic fatigue and political gridlock. The reactivation of the Stability and Growth Pact has yielded little more than cosmetic compliance. Incrementalism prevails over reinvention.

This institutional inertia is eroding public trust. Confidence in national governments and parliaments remains fragile in economies marked by high debt, slow growth, and rising inequality. Populist parties, from Germany’s AfD to France’s Rassemblement National, are gaining momentum, fuelled by the perception that governments are no longer capable of managing economic and technological transitions with competence or fairness.

Absent bold fiscal restructuring and institutional renewal, Europe risks drifting into a scenario where automation magnifies structural weaknesses instead of mitigating them. The gradual erosion of tax capacity, welfare solvency, and political legitimacy may not spark immediate crisis, but it steadily undermines the state’s ability to deliver on its core promises.

As public budgets tighten, long-term investments in infrastructure, climate resilience, and digital transformation are increasingly financed not by governments, but by sovereign wealth funds, institutional investors, and large asset managers. From Norway’s Government Pension Fund to firms like BlackRock and Allianz, these actors now co-finance major projects, often through public-private partnerships or EU-backed vehicles such as InvestEU and the Green Deal.

This shift reflects pragmatic adaptation to fiscal constraints. These investors bring capital, expertise, and operational scale. Yet their rising influence also presents challenges. Investment decisions are guided by internal mandates and market logic, not democratic deliberation. As such, these entities are increasingly acting as de facto economic stewards, shaping Europe’s economic trajectory without formal public accountability.

This model can be effective, capital is mobilised, infrastructure is built, and innovation proceeds. But without robust public frameworks to govern distribution, the financial returns from key sectors, particularly AI, data infrastructure, and green technology, risk being captured by a narrow set of institutional stakeholders. In a continent already marked by regional inequality and populist discontent, the perception that critical economic decisions are outsourced to unelected, often transnational actors could deepen mistrust.

The political consequences are foreseeable. Populist movements gain strength across the spectrum. Nationalist sentiment intensifies. Demands for economic sovereignty, “national AI strategies,” digital protectionism, and data localization begin to dominate policy debates. What begins as passive governance risks ending in political and economic fragmentation.

State-Enabled Capitalism: Public Goals via Private Capital

A third scenario offers a more hybrid approach. Rather than extracting value solely through taxation or relinquishing authority to unfettered markets, governments assume the role of strategic enablers, partnering with private capital to co-invest in long-term national priorities. This is the model of state-enabled capitalism.

In this evolving framework, public institutions define strategic priorities—green energy, digital infrastructure, workforce reskilling and use tools such as guarantees, concessional capital, and blended finance to de-risk private investment. In turn, institutional investors, pension funds, ESG-aligned asset managers, and sovereign wealth entities increasingly deploy patient capital: funding with longer time horizons, moderate return expectations, and an emphasis on long-term impact.

Elements of this model are already visible. In the UK, the UK Infrastructure Bank is partnering with pension funds to channel capital into renewable energy, transport, and regional development. Temasek, Singapore’s state investment company, has co-invested with institutional partners in Indian and Southeast Asian clean energy projects, often taking early-stage risk in exchange for long-term national strategic value. CDPQ (Caisse de dépôt et placement du Québec), one of Canada’s largest pension funds, has pioneered a climate-aligned infrastructure strategy, focusing on 20+ year investments in sustainable transport and decarbonisation. In Africa, the Sustainable Infrastructure Foundation and Africa50, backed by the African Development Bank, are structuring blended finance platforms to crowd in global institutional capital for public-interest infrastructure.

In the United States, programs like the Department of Energy’s Loan Programs Office and the Inflation Reduction Act’s clean energy incentives blend public risk capital with private investment, catalyzing long-term innovation. Even under a market-oriented policy regime, there is growing bipartisan recognition of the need to institutionalize long-horizon investment vehicles, including emerging conversations around federal development banks and public wealth funds at the state level.

Together, these developments signal a pragmatic shift from ad hoc stimulus or ideological retrenchment toward durable financial architectures that align public direction with private commitment over multi-decade horizons.

This approach allows governments to tap market efficiencies while maintaining a degree of strategic oversight. It also circumvents some of the political resistance that often accompanies redistributive tax regimes. Yet the model is not without trade-offs. As governance migrates from parliaments to investment committees, transparency can erode. Citizens may benefit materially from upgraded infrastructure or expanded services, but find themselves distanced from the decisions that shape their collective economic future. The boundary between democratic governance and technocratic administration begins to blur.

In its most optimistic form, state-enabled capitalism aligns innovation with inclusion and capital with conscience. At its worst, it risks evolving into a form of soft elite rule, efficient, stable, and fundamentally post-democratic.

Fiscal Sovereignty in the Age of AI

All three scenarios reveal the central tension of the AI era: labor’s declining role in value creation threatens to undermine the tax structures that underpin modern states. As wages stagnate and traditional employment contracts erode, income tax bases shrink. Governments must therefore decide whether to tax capital more heavily, partner with it strategically, or relinquish authority altogether.

The path forward will vary by country, ideology, and institutional capacity. But all roads lead through a common chokepoint: fiscal sovereignty. If states cannot retool how they finance themselves in an AI-transformed economy, their ability to shape outcomes will diminish.

Moderating Realities and the Most Likely Path

Despite dramatic forecasts, AI’s economic transformation is likely to be uneven, gradual, and path-dependent. Most firms are still in early stages of adoption. Regulatory complexity, managerial inertia, and organizational bottlenecks will constrain full deployment. Many jobs are bundled with interpersonal or physical tasks that resist automation. And in key sectors, healthcare, education, defense, AI will augment rather than replace human labor.

In this context, Scenario 3, state-enabled capitalism, offers a realistic adaptive path. It avoids the fiscal risks of Scenario 2 and the political headwinds of Scenario 1. But its success hinges on one condition: that capital remains mission-aligned, publicly accountable, and transparently governed.

If not, the AI dividend will flow to the few, while the many are left to bear the burden of adjustment.

The rise of AI presents an opportunity to rethink not only economic systems, but societal goals. Beyond productivity and growth, the real prize is resilience: the capacity of institutions to absorb shocks, adapt equitably, and preserve legitimacy. Whether through redistribution, public-private alignment, or fiscal innovation, the central task is the same, ensuring that the future remains a public good, not a private windfall.

In that lies the true strategic challenge of the AI age. Not building smarter machines, but building fairer systems. Not extracting more value, but distributing it with purpose. And not fearing displacement, but designing inclusion.