City Research Online

Abstract

Within the fourth industrial revolution, generative artificial intelligence (AI) is widely heralded as the solution to stagnant productivity growth in advanced economies. Governments, corporations, and economists predict substantial economic gains from AI adoption, with estimates suggesting trillions in additional GDP. This article challenges the assumption that AI-driven productivity growth will automatically benefit workers. We argue that the concept of productivity obscures a prior distributional question: who captures the gains from increased output? To address it, we distinguish between zero-sum productivity, whose gains accrue to capital owners, and positive-sum productivity, in which the gains are broadly shared. Drawing on recent evidence, we identify three factors that undermine the prospects for positive-sum outcomes: corporations’ tendency not to share productivity gains with workers, AI’s threat to knowledge workers previously protected by specialised expertise, and the uncertain and uneven effects of AI across organisations. The decoupling of wages from productivity since the 1970s, alongside the growth of rent-seeking, suggests that AI may intensify existing inequalities rather than resolve them. Whether the gains are shared is not settled by the technology but depends on institutions and policy. We advocate a human-centric approach that requires active state intervention through industrial policies that incentivise job creation, meaningful work design, and the equitable distribution of productivity rewards.

Publication Type:	Article
Additional Information:	© The Author(s), 2026. Published by Cambridge University Press on behalf of The University of New South Wales. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial Non-Derivative License (CC BY NC ND). The non-commercial use, distribution or reproduction in other forums is permitted, provided that no alterations are made and the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. The written permission of Cambridge University Press or the rights holder(s) must be obtained prior to any commercial use and/or adaptation of the article.
Publisher Keywords:	artificial intelligence, employment, labour markets, pay, productivity
Subjects:	H Social Sciences > HB Economic Theory H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HF Commerce
Departments:	School of Policy & Global Affairs School of Policy & Global Affairs > Department of Sociology & Criminology
SWORD Depositor:	Symplectic Administrator

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