Christopher Pissarides, a 2010 Nobel laureate in economics renowned for studying how automation reshapes employment, has delivered a sobering assessment of artificial intelligence's economic prospects. Speaking to Bloomberg News, the London School of Economics professor argued that hopes pinned on AI to revitalise productivity growth may prove misplaced, suggesting instead that the exceptional expansion of previous decades belongs firmly to the past.
Pissarides's intervention cuts across the prevailing optimism sweeping Silicon Valley and government chambers alike. Technology executives and policymakers have increasingly looked to AI as a potential saviour for flagging economic performance, particularly as Western nations grapple with growth rates substantially lower than those recorded throughout the late twentieth century. This weakened trajectory has constrained fiscal flexibility, complicated policy decisions, and contributed to an increasingly volatile political environment where wage stagnation fuels public discontent.
The economist's scepticism rests partly on empirical observation. Despite months of widespread AI deployment and investment, concrete evidence of productivity improvements remains elusive. This apparent disconnect between technological fanfare and measurable economic impact troubles Pissarides, who questions the sweeping claims made by prominent figures such as Nvidia chief Jensen Huang and OpenAI founder Sam Altman regarding AI's transformative employment effects.
At the Royal Economic Society conference in Newcastle on July 6, Pissarides presented a more granular analysis of AI's limitations. His central argument hinges on labour market reality: approximately 40 percent of jobs in the United Kingdom exist outside AI's current reach. Nursing, hospitality, and similar service-sector roles remain fundamentally resistant to automation, meaning workers in these fields will derive no productivity advantage from the technology. This structural constraint fundamentally undermines scenarios where AI drives economy-wide growth comparable to historical norms.
For Southeast Asian policymakers observing this debate, Pissarides's framework offers crucial perspective. Malaysia, like other developing economies, has positioned AI adoption as central to competitiveness strategies. Yet if even advanced Western economies cannot expect transformative productivity gains, the assumption that AI will accelerate development in emerging markets warrants careful re-examination. The dynamics differ markedly when labour markets remain less saturated with capital and automation already.
Pissarides acknowledged that some sectors will experience genuine AI-driven productivity improvements. Finance, technology services, and data-intensive industries should logically benefit from computational advances. However, he stressed that even achieving substantial gains across these concentrated sectors would prove insufficient to restore the robust growth rates that characterised the 1980s and 1990s. That era benefited from broader, economy-wide transformations as computing technology diffused across organisations and industrial processes fundamentally reorganised. Current AI developments, while impressive in narrow applications, lack comparable universality.
The economist's framework inverts the dominant narrative circulating among technology enthusiasts and some policymakers. Rather than questioning whether AI will be powerful enough to require workforce retraining and social safety net expansion, Pissarides essentially asks whether we should expect productivity growth at all. This reframing carries profound implications for budget planning, retirement security assumptions, and intergenerational wealth distribution across developed and developing economies alike.
Bank of England Governor Andrew Bailey represents the contrarian position within the policymaking establishment. He has indicated that AI possesses game-changing potential for economic expansion, though he cautiously notes that quantifiable impacts will emerge only gradually. Bailey's recent suggestion that AI might "ride to the rescue" for struggling growth trajectories reflects conventional central bank optimism, yet Pissarides's detailed labour market analysis provides a more rigorous counterweight to such hopes.
The implications extend beyond academic disagreement. If Pissarides proves correct, Western governments pursuing growth-focused fiscal strategies may face disappointment, potentially forcing difficult recalibrations of expectations around taxation, pension obligations, and social expenditure. The sluggish growth environment already complicates policy trade-offs and has contributed measurably to political fragmentation as voters express frustration with stagnant real wages despite technological advancement.
For Malaysia and regional peers, the stakes involve development strategy recalibration. Nations banking heavily on AI-driven leapfrogging to advanced-economy status might consider more modest assumptions about technological salvation. Pissarides's work suggests that sectoral focus matters enormously—identifying genuinely AI-exposed industries versus those requiring sustained human labour becomes critical for realistic planning.
The Nobel laureate's caution also highlights uncertainty as a defining feature of technological forecasting. While emphasising his own analytical doubts, Pissarides acknowledged that AI's ultimate trajectory remains fundamentally unknowable. This epistemological humility contrasts sharply with the certainty pervading some technology sector pronouncements, suggesting that prudent policymakers should plan for multiple scenarios rather than anchoring assumptions to Silicon Valley's most optimistic projections. The question facing governments, particularly in emerging markets, involves building resilience and adaptability into economic models rather than betting economic futures on any single technological solution delivering predetermined outcomes.
