A leading economist who won the Nobel Prize for his research into labour market dynamics has cautioned policymakers and investors against expecting artificial intelligence to resurrect the robust productivity growth that characterised Western economies in past decades. Christopher Pissarides, whose academic work examines how automation reshapes employment, contends that the window for sustained rapid economic expansion has likely closed, regardless of technological advancement.
The implications of this assessment extend far beyond academic debate. Governments across the developed world, including those in the European Union and United Kingdom, have invested considerable political capital in the premise that AI breakthroughs will unlock new sources of economic dynamism. This optimism has underpinned policy decisions affecting everything from technology regulation to workforce planning. For Southeast Asian policymakers watching these developments, the scepticism from an influential voice like Pissarides suggests the need for calibrated expectations about AI's transformative potential in their own economies.
Pissarides points to a fundamental constraint limiting AI's economic impact: substantial portions of the workforce operate in sectors where artificial intelligence cannot easily intervene. According to his analysis, approximately 40 percent of jobs in the United Kingdom and similarly large proportions in the United States exist in areas such as nursing, care work, and hospitality services where human interaction, judgment, and physical presence remain irreplaceable. These sectors, which often employ significant numbers of workers, cannot realistically experience the kinds of productivity surges that technology evangelists envision.
The economist's position directly contradicts the narrative promoted by prominent technology executives. Jensen Huang of Nvidia and Sam Altman of OpenAI have publicly proclaimed that artificial intelligence will deliver transformative consequences for employment and economic output. Their pronouncements have influenced investor sentiment, corporate strategy, and governmental technology policy across multiple continents. Pissarides, speaking from his position at the London School of Economics, offers a more measured perspective grounded in rigorous economic analysis rather than technological enthusiasm.
Crucially, Pissarides observes that empirical evidence supporting AI-driven productivity acceleration remains elusive. Despite years of high-profile AI deployments and billions in venture capital funding, measurable productivity gains at the macroeconomic level have not materialised as forecast. This absence of concrete results undermines the case for expecting a productivity renaissance comparable to the computing revolution of the 1980s and 1990s, when digital technologies fundamentally reorganised business operations and created entirely new industries.
The historical comparison proves instructive. The personal computer era and subsequent internet revolution genuinely transformed productive capacity across nearly all economic sectors, from manufacturing to services. The productivity improvements were broad-based, sustained, and eventually reflected in rising living standards across developed economies. Current AI applications, while impressive in specific domains such as language processing and image recognition, have not yet demonstrated comparable breadth or depth of economic transformation. Pissarides expresses profound scepticism that artificial intelligence will replicate this historical performance.
The economic stagnation affecting Western developed economies has created acute policy challenges with significant political consequences. Slow productivity growth translates into weak wage increases for ordinary workers, constraining household purchasing power and fuelling discontent with existing political arrangements. This dynamic has contributed to the fragmented political environment across Europe and North America, where traditional parties struggle to command stable electoral coalitions. Policymakers have therefore seized upon AI as a potential solution, hoping technological breakthroughs might restore the economic growth that could ease political tensions through rising incomes.
However, Pissarides argues this hope rests on shaky foundations. Even in sectors most exposed to AI applications—such as finance, software development, and professional services—the productivity improvements necessary to generate the growth rates optimists project appear unrealistic given current technological capabilities. The concentration of potential AI benefits in a relatively narrow range of industries means economy-wide productivity acceleration faces steep obstacles. For Malaysia and other middle-income countries, this reassessment carries important implications for technology policy and long-term development strategy.
Pissarides delivered these arguments during a July 6 lecture at the Royal Economic Society conference in Newcastle, framing his remarks with characteristic academic caution. He acknowledges genuine uncertainty about artificial intelligence's future trajectory, avoiding the categorical pronouncements favoured by some commentators. Nevertheless, his assessment that rapid, sustained productivity growth has become permanently unlikely represents a significant departure from official optimism. For developing economies in Southeast Asia considering how to position themselves in a rapidly changing technological landscape, this scepticism from a distinguished economist merits serious consideration.
Bank of England Governor Andrew Bailey represents the institutional perspective that AI might yet prove transformative, though he has recently cautioned that the technology's economic benefits will take considerable time to manifest in growth statistics. This apparent contradiction—simultaneously viewing AI as potentially game-changing while acknowledging long delays before observable impact—reveals the uncertainty clouding official policy discussions. Bailey's hedged position suggests even technology optimists within policymaking circles recognise the risk that AI may disappoint expectations.
For Southeast Asian economies monitoring these debates, the divergence between technology enthusiasm and economic scepticism creates both challenges and opportunities. Nations cannot afford to ignore AI development, given its importance to future competitiveness. Yet Pissarides's caution argues against restructuring entire economies around assumptions of imminent AI-driven transformation. A more pragmatic approach, combining continued technology investment with realistic expectations about near-term productivity gains, may better serve long-term development objectives.
