Christopher Pissarides, a Nobel Prize laureate who has devoted his career to studying automation's effect on labour markets, delivered a sobering assessment of artificial intelligence's capacity to transform economic fortunes. The distinguished economist argues that policymakers and technology executives harbour unrealistic expectations about AI's ability to reverse decades of economic sluggishness, particularly affecting Europe and other advanced economies where productivity gains have become increasingly scarce.
The stakes surrounding this debate are considerable for the region and beyond. Governments and multinational corporations have invested heavily in AI infrastructure and development, banking on breakthrough productivity gains to address structural economic challenges that have plagued the West. This optimism partly stems from historical precedent: the computing revolution of the 1980s and 1990s unleashed transformative productivity improvements that powered sustained growth and rising living standards. However, Pissarides warns that expecting similar dynamics from contemporary AI technology amounts to wishful thinking rather than economic analysis.
Central to Pissarides' argument is a straightforward empirical observation: large segments of the labour market simply cannot be disrupted by AI. Speaking at the Royal Economic Society conference in Newcastle on July 6, the London School of Economics professor noted that approximately 40 per cent of jobs in the United Kingdom remain largely insulated from artificial intelligence's reach. He highlighted sectors such as nursing and hospitality, where human interaction, physical presence, and contextual judgment remain irreplaceable. These industries will therefore struggle to achieve meaningful productivity improvements through automation, regardless of technological advances elsewhere in the economy.
This analysis carries profound implications for Southeast Asian economies, which increasingly compete for investment and talent in a globalised world. If Western productivity growth remains anaemic, demand for regional exports may weaken, affecting growth trajectories across the Association of Southeast Asian Nations. Malaysian policymakers monitoring AI adoption should consider whether their own labour-intensive sectors—tourism, hospitality, healthcare, and domestic services—will similarly resist automation gains that enthusiasts predict.
The productivity paradox Pissarides identifies echoes earlier warnings from across the economics profession. Despite billions invested in AI research and deployment, tangible evidence of widespread productivity acceleration remains elusive. Tech executives such as Nvidia's Jensen Huang and OpenAI's Sam Altman have made sweeping claims about AI's transformative potential, yet corporate earnings and macroeconomic data have yet to reflect revolutionary productivity breakthroughs. Pissarides directly challenges this disconnect between hype and observable reality, suggesting that gap will persist rather than narrow.
For growth rates to reach the levels techno-optimists envision, productivity improvements would need to concentrate overwhelmingly in sectors already most exposed to AI—particularly finance and professional services. The mathematics becomes stark: even dramatic productivity gains in these relatively small employment sectors cannot generate economy-wide growth acceleration when they represent limited shares of total employment. Pissarides suggests this concentration of potential benefits makes economy-wide transformation impractical, undercutting the case for AI-driven renaissance.
The economist's scepticism about future productivity growth carries worrying political ramifications that resonate throughout Western democracies. Sluggish productivity has coincided with stagnant real wages, squeezed public budgets, and compressed social mobility—conditions that have fuelled populist backlash and political polarisation. If policymakers cannot credibly promise renewed growth and improved living standards through technological advancement, they must confront harder distributional choices about how existing resources are allocated. That political difficulty may partly explain why governments and tech firms remain invested in AI optimism despite mixed early evidence.
Bank of England Governor Andrew Bailey represents the countervailing view within policymaking circles. He has suggested AI may ultimately prove transformative for economic growth, though he acknowledges meaningful lag before productivity gains fully materialise in official statistics. This divergence between Pissarides and policymakers like Bailey reflects genuine uncertainty about AI's long-term trajectory. Neither position can be definitively ruled out based on current evidence, though Pissarides' empirical focus on actual labour market exposure provides grounding that some optimistic scenarios may lack.
Malaysia and other developing Southeast Asian economies occupy a unique position in this debate. Rather than assuming AI will replicate Western automation patterns, regional leaders might strategically leverage labour advantages in AI-resistant sectors while simultaneously developing technological capabilities. Countries that can capture high-value AI development activities without surrendering competitive advantages in hospitality, tourism, and personal services could achieve growth that surpasses stagnant Western performance. The key distinction lies in recognising that AI's uneven effects across sectors create opportunities for differential positioning, not uniformly transformed productivity.
Pissarides' warning also highlights an overlooked dimension of AI adoption: implementation costs and workforce transition challenges. Even sectors theoretically exposed to AI face practical constraints in deploying technology effectively. Training requirements, system integration complexity, and need for human oversight all slow the pace of actual productivity improvement relative to technological possibility. These friction costs may permanently suppress the return on AI investment relative to earlier computing waves, constraining aggregate growth even in sectors most amenable to automation.
Looking forward, the debate between Pissarides and AI enthusiasts will likely continue shaping policy responses. Central banks weighing interest rate adjustments, governments considering AI investment incentives, and corporations planning workforce strategies all implicitly resolve this question. However, Pissarides suggests placing faith in rapid AI-driven growth constitutes a policy mistake with consequences extending far beyond economic statistics. By acknowledging that productivity growth may remain structurally constrained regardless of technology, policymakers can focus on distributional fairness and realistic capacity enhancement rather than pursuing illusory growth miracles.
