Christopher Pissarides, the 2010 Nobel Prize laureate in economics, has delivered a sobering assessment of artificial intelligence's capacity to revitalise flagging Western economies. Speaking to Bloomberg News, the London School of Economics professor challenged the prevailing narrative promoted by technology executives and policymakers who view AI as a potential cure for decades of sluggish economic performance. His intervention represents a significant counterpoint to the bullish predictions that have dominated recent policy discussions across Europe, North America, and increasingly in Asia-Pacific markets.
The backdrop to this debate reflects genuine anxiety about long-term economic stagnation. Developed economies have experienced a marked deceleration in productivity growth since the 1990s, creating cascading consequences for living standards, wage growth, and public finances. This sluggishness has fuelled political instability and contributed to the erosion of middle-class purchasing power, particularly in Europe. Governments and corporations have seized upon AI as a potential game-changer—a technological force analogous to the computer revolution that could restore the robust growth trajectories of earlier decades. This optimism underpins much contemporary economic policymaking and corporate investment strategy.
Pissarides's research specialises in understanding how automation reshapes labour markets and employment dynamics. Drawing on this expertise, he presented a detailed empirical argument during a July 6 lecture at the Royal Economic Society conference in Newcastle. His central claim: approximately 40 per cent of jobs in the United Kingdom and United States would remain substantially insulated from AI's productive capabilities. He cited sectors including nursing and hospitality as prime examples where AI cannot realistically displace human labour or dramatically enhance productivity, given the interpersonal and manual skill requirements inherent in these fields.
The mathematician's scepticism extends beyond simple sectoral analysis. He questioned whether even substantial productivity gains in the most AI-exposed sectors—particularly finance, technology, and advanced manufacturing—could generate the kind of economy-wide growth that contemporary optimists envisage. To achieve the growth rates cheerleaded by technology leaders like Nvidia's Jensen Huang and OpenAI's Sam Altman would require productivity explosions not just in pockets of the economy but across broad swathes of activity. This mathematical reality, Pissarides argued, makes such scenarios implausible rather than merely unlikely.
Critically, Pissarides noted the absence of measurable productivity improvements attributable to AI in current economic data. Despite years of investment and hype, tangible productivity gains remain elusive. This observation directly contradicts claims from prominent technologists who suggest AI will fundamentally alter economic trajectories. The disconnect between promotional narratives and observable reality forms the crux of his argument: if AI were delivering transformative productivity benefits, evidence would already be visible in national accounting figures and corporate profitability metrics.
His comparison to the computer revolution of the 1980s and 1990s proves instructive for understanding his measured scepticism. That earlier technological transition genuinely did reshape production processes across multiple sectors simultaneously, generating sustained productivity improvements and enabling genuine economic acceleration. AI, by contrast, appears narrower in application and more limited in its capacity to fundamentally restructure how economies function. Pissarides expressed doubt that AI would match those historical precedents, despite the technology's undeniable sophistication and potential applications.
For Malaysian policymakers and business leaders, Pissarides's analysis carries particular relevance. Southeast Asia has positioned itself as both a beneficiary and participant in the AI revolution, with countries like Singapore, Malaysia, and Thailand developing digital economy strategies around emerging technologies. However, if rapid productivity gains prove elusive even in developed economies with advanced technological infrastructure, the implications for developing markets warrant careful consideration. The assumption that AI adoption automatically generates growth may require recalibration.
The uncertainty surrounding AI's trajectory adds another layer of complexity to Pissarides's argument. He explicitly acknowledged that predicting technological futures involves inherent unpredictability. Yet his core contention rests on a fundamental observation: even under optimistic scenarios, the structural constraints of modern economies—particularly the large proportion of labour-intensive services resistant to automation—mean rapid growth restoration appears inconsistent with realistic assessments.
Bank of England Governor Andrew Bailey represents the competing perspective within policymaking circles. While acknowledging that AI implementation requires time before economic impact materialises, Bailey has suggested the technology "may well ride to the rescue" for growth prospects. This more hopeful framing reflects institutional incentives to project confidence in future economic trajectories, yet it stands in tension with Pissarides's empirically grounded scepticism.
The implications extend beyond academic debate. If Pissarides proves correct, governments may need to recalibrate expectations for future living standards, productivity gains, and tax revenue growth. This realisation could necessitate different policy approaches to managing social expectations, funding public services, and addressing inequality. The assumption that technology automatically solves economic challenges—what might be called technological determinism—may require replacement with more realistic frameworks acknowledging structural economic constraints.
Pissarides concluded that societies should accept the possibility that "the days of fast productivity growth are over, whatever we do." This resignation reflects not technological pessimism but rather honest assessment of economic realities. Rather than pursuing miraculous solutions through artificial intelligence, this perspective suggests energy might be better directed toward managing mature economies more sustainably, distributing available growth more equitably, and developing social frameworks suited to lower-growth realities that increasingly characterise developed economies.
