Can AI Replace Markets?

A (Market) Socialist Response to Carlo L. Cordasco

My friend Carlo Ludovico Cordasco has recently offered two very rich and thought-provoking blog posts on AI and the knowledge problem. His argument has the merit of moving beyond simplistic dichotomies, exploring, in a very intellectually honest way, whether and how AI could replicate, or even in the end replace, the economic functions traditionally fulfilled by markets. In particular, he focuses on the role of markets in knowledge discovery and error correction, and raises doubts about whether AI can match markets in these crucial areas.

What strikes me about Carlo's analysis is how closely it aligns with a market socialist perspective, one that sees markets not as sacred, but as contingent institutional tools that can be supplemented, simulated, or partially replaced if and when better mechanisms arise. In fact, many of the challenges Carlo raises, and the hybrid solutions he envisions, fit comfortably within the framework proposed by Oskar Lange and others who sought a synthesis of planning and decentralised feedback.

Decoupling Normativity from Mechanism

One of Carlo’s key insights is that any normative standard of optimal allocation must be independent of markets themselves. Whether we adopt Pareto efficiency, a utilitarian social welfare function, a Rawlsian max-min principle, or a capabilities-based approach, these standards are defined in terms of outcomes, rather than in terms of institutional forms. Markets may approximate well those outcomes under certain conditions, but they are not normatively privileged in themselves.

This is precisely the starting point of Oskar Lange’s contribution. Lange acknowledged the informational value of markets but did not take them as axiomatic. Instead, he proposed using simulated price signals within a central planning system, guided by surplus-and-shortage feedback, to mimic the coordination function of decentralised markets (Lange, 1936).

This argument resonates with broader traditions in institutional economics and decision theory, from Herbert Simon’s (1957) notion of bounded rationality (which calls for satisficing within complex, information-poor environments), to Albert & Hahnel (1991) participatory planning, which seeks decentralised yet coordinated economic processes based on iterative feedback and shared goals rather than strict competition. Similar lines of thinking appear in Pat Devine's (1988) negotiated coordination, where democratic participation at the point of production plays a central role in allocating resources without relying solely on markets.

Lange’s collaborator, Włodzimierz Brus, later deepened this framework by emphasising the institutional and political preconditions for meaningful economic coordination, arguing that planning systems must incorporate decentralisation, responsiveness, and democratic oversight if they are to function effectively (Brus & Laski, 1989). Brus’ later work critically assessed the failures of actually existing socialism, proposing a more pluralist and democratic form of economic management within a broadly socialist vision.

Importantly, these contributions were not mere technocratic tweaks to capitalist economics. They stemmed from a Marxist tradition concerned with overcoming the anarchy of production, abolishing exploitation, and democratically controlling the surplus. Lange, Brus, and others attempted to address a core tension in Marx’s legacy: how to preserve collective ownership and coordination without succumbing to inefficient and ineffective bureaucratic centralisation. Their proposals sought to realise a post-capitalist rationality, in which production serves social needs, not private accumulation.

Moreover, historical experiments like Project Cybersyn in 1970s Chile, an attempt to use early cybernetics for real-time economic coordination (Medina, 2011), and Yugoslavia’s system of worker-managed firms within a market socialist structure (Horvat, 1982) show that efforts to blend planning, participation, and market feedback signals are not new. What was missing then, computational capacity, real-time data, and advanced prediction, AI may now begin to supply.

AI as Augmented Planning?

Carlo is right to emphasise the two core engines of market coordination. The contribution to knowledge discovery, with agents revealing dispersed and often tacit knowledge through transactions; the error correction capability, with misjudgements punished through loss, prompting revision or exit.

He doubts whether AI can yet match markets in the second function. But he also grants that AI is increasingly effective at the first, discovering types, forecasting demand, and running micro-experiments at scale.

That brings us to the crux of the argument: we don’t need to abolish markets to acknowledge that AI can shift the boundaries of where and how they are needed. As Lange anticipated, if informational conditions change, the case for market reliance changes too.

And those conditions are changing. AI-based planning is no longer theoretical: recommender systems already allocate attention and goods in digital media and online platforms; large multinational companies rely on sophisticated OR algorithms and to forecast and optimise production planning, inventory management and routing of goods across global supply chains (Phillips & Rozworski, 2019); smart energy grids adjust production and consumption in real time based on predictive models. These are not thought experiments: they are partial, algorithmically mediated planning systems embedded in market economies.

From a Marxist perspective, this opens a new frontier in the critique of political economy. If AI can alleviate information constraints that once necessitated markets, and if we can design institutions that discipline economic activity around social needs rather than profitability, then the socialisation of economic coordination becomes a practical question, not a utopian dream.

Toward a Patchwork Future?

Carlo ends by suggesting a likely institutional future: a patchwork of mechanisms. In some segments of the economy, especially those marked by near-zero marginal costs, such as synthetic media or digital goods, scarcity is disappearing, and with it, the informational role of prices. In those domains, AI may well coordinate allocation better than markets, using algorithms, queues, or open-access protocols.

But in other areas, scarcity persists, and so does the need for price-based feedback. Even here, however, AI can complement markets by improving discovery, forecasting bottlenecks, and highlighting inefficiencies faster than human actors can.

A particularly relevant field of study is algorithmic mechanism design, which explores how multiple AI agents can engage in resource allocation through incentive-aligned protocols. In distributed algorithmic mechanism design, agents interact directly to reach equilibria without centralised control, suggesting that coordination and error correction could emerge from peer-based feedback rather than traditional markets.

Conclusion: A Langean Reframing?

So perhaps the right question is not whether AI can replace markets, but under what conditions AI might augment or partially substitute for them. Carlo's skepticism about AI's ability to replace error-correcting feedback is well-taken. But his framework opens up, rather than forecloses, the possibility of a market socialist synthesis: one in which we preserve the disciplinary role of markets where needed, while exploring algorithmic tools to expand the range of feasible and desirable coordination.

This isn’t a rejection of markets, but a call to reimagine them: as tools we can refine, not temples we must defend. And from a Marxist point, this is not a nostalgic call for bureaucratic planning. It is a forward-looking vision: one in which production is democratically directed, technologically enhanced, and ecologically bounded: socialism recalibrated for the digital age.

References:

Albert, M., & Hahnel, R. (1991). The Political Economy of Participatory Economics. Princeton University Press.

Brus, W., & Laski, K. (1989). From Marx to the Market: Socialism in Search of an Economic System. Oxford University Press.

Devine, P. (1988). Democracy and Economic Planning: The Political Economy of a Self-Governing Society. Polity Press.

Horvat, B. (1982). The Political Economy of Socialism: A Marxist Social Theory. M.E. Sharpe.

Lange, O. (1936). On the Economic Theory of Socialism. Review of Economic Studies, 4(1), 53–71.

Medina, E. (2011). Cybernetic Revolutionaries: Technology and Politics in Allende's Chile. MIT Press.

Phillips, L., & Rozworski, M. (2019). The people's republic of Walmart: How the world's biggest corporations are laying the foundation for socialism. Verso Books.

Simon, H. A. (1957). Models of Man: Social and Rational. Wiley.