The United States has long relied on low-cost labour as a key driver of economic growth. From slavery in the 18th and 19th centuries to industrial immigration in the 20th century, and now automation and artificial intelligence (AI) in the 21st century, the American economy has repeatedly sought ways to maximise output while minimising labour costs.

The economic rationale is clear: reducing labour costs increases competitiveness, enables higher production, and ultimately helps sustain consumer demand through lower prices. At various points in history, industries have depended on different forms of low-cost labour, whether through forced labour, immigrant workforces, or automation. These transitions have often resulted in short-term efficiency gains but also structural adjustments that reshaped industries and labour markets.

As the global economy moves towards increasing automation, it is useful to assess whether AI and robotics will replicate past patterns, effectively becoming the new form of “cheap labour.” Examining this historical pattern provides insight into how cost-efficient labour sources have driven American economic expansion—and how future technological advancements may redefine work itself.

Slavery and Economic Expansion

The earliest and most extreme form of cost-cutting labour in the U.S. was slavery, which played a significant role in agricultural production—particularly in cotton, tobacco, and sugar. The productivity of enslaved labour allowed the U.S. to export raw materials at highly competitive prices, establishing the South as a key supplier to the British and Northern textile industries.

By the mid-19th century, cotton accounted for more than half of all U.S. exports, with production exceeding one million bales per yearial valuation of enslaved workers was immense; by 1860, they represented the largest single financial asset in the U.S., exceeding the combined value of railroads, factories, and banks . In economavery provided an ultra-low-cost workforce** that enhanced agricultural productivity, allowed capital accumulation, and drove early industrial growth in textiles.

However, despite its economic efficiency, slavery had structural limitations. It was concentrated in agriculture rather than industrial production, and its forced nature constrained consumer purchasing power within the enslaved population. As industrialisation progressed, economies reliant on wage labour and consumer markets outperformed those dependent on coerced labour, which lacked incentives for productivity improvements. The abolition of slavery in 1865 removed this labour source, requiring the economy—particularly in the South—to transition towards new models of employment.

Industrialisation and Immigrant Labour

Following the Civil War, the U.S. shifted towards an industrial economic model, which required an expanded workforce in manufacturing, infrastructure, and resource extraction. Between 1870 and 1914, over 20 million immigrants arrived in the U.S., many of whom took up positions in factories, steel mills, coal mines, and railroads . These industries requinumbers of workers** but also sought to maintain low wage costs to remain globally competitive.

The use of European and Asian migrant labour allowed industrialists to expand operations while keeping production costs low. For instance, Chinese workers formed the majority of labourers on the Transcontinental Railroad, where they were paid less than white workers yet performed the most dangerous tasks . The rail network enabled efficiansportation, facilitating the U.S. economy’s expansion into the Western territories.

Similarly, in manufacturing hubs like New York and Chicago, newly arrived immigrants staffed textile mills and steel plants. These workers provided an inexpensive, scalable workforce, helping the U.S. become a dominant force in global manufacturing. Between 1880 and 1910, industrial output in the U.S. tripled, due in part to the availability of low-cost labour .

However, this reliance on immigrant labouo periodic economic adjustments. By the 1920s, concerns about wage suppression and employment competition led to immigration restrictions, such as the 1924 National Origins Act, which reduced the flow of workers from certain regions. As the domestic workforce became more expensive, industries began to explore automation and offshore production as alternative cost-saving strategies.

Mid-20th Century: The Bracero Programme and Globalisation

Labour shortages during World War II prompted the U.S. to adopt structured guest worker programmes, most notably the Bracero Programme (1942–1964). This initiative brought millions of Mexican workers to the U.S. for agricultural and infrastructure jobs, ensuring continued productivity while many American workers were enlisted in the military.

Braceros provided low-cost, seasonal labour, helping the U.S. maintain stable food prices and agricultural exports . However, as wage demands grew in the post-war period, te on temporary foreign workers gave way to technological investments in mechanised farming. The mechanical cotton picker, introduced in the 1940s, significantly reduced the need for manual labour in cotton fields .

The latter half of the 20th century also saw **globalisation*labour markets. As domestic wages rose, businesses outsourced manufacturing to countries with lower labour costs, particularly in Asia and Latin America. This shift allowed U.S. firms to reduce production expenses, offering consumers cheaper goods while maintaining profitability. However, it also led to industrial job losses, particularly in regions dependent on manufacturing, such as the Midwest (“Rust Belt”) .

21st Century: Automation, AI, and the Future of Labour

As automation advances, businesses increasingly view AI and robotics as a means to replace or supplement human labour. The rationale remains the same: reduce costs, increase efficiency, and enhance productivity.

For instance, Amazon warehouses now employ over 750,000 robots, handling logistics, sorting, and packaging at lower costs than human workers . In transportation, companies are developing self-driving trucks to potentia long-haul drivers, a key sector where labour costs constitute a major expense. A McKinsey Global Institute report estimates that by 2030, up to 30% of current work hours could be automated, primarily in routine and repetitive tasks.

The economic benefits of AI-driven automation include:

  • Lower operational costs for improving profit margins.
  • Increased production capacity, with 24/7 automated systems.
  • Potential consumer price reductions, as supply chain efficiency improves.

However, just as past transitions from cheap labour sources led to short-term dislocation, automation poses challenges in workforce adaptation. Some studies indicate that robot deployment has already contributed to wage stagnation and job displacement in sectors such as manufacturing and logistics .

From an economic perspective, the key policy question is how to manage the transition. Historicalggest that investment in skills training, innovation incentives, and labour market flexibility will be crucial in ensuring that AI contributes to overall economic prosperity without exacerbating unemployment.

The Recurring Pattern of Cost-Driven Labour Models

The U.S. economy has consistently sought the most cost-efficient labour model—from slavery and migrant workforces to outsourcing and automation. While each shift has produced economic gains, it has also required structural adjustments, particularly in labour markets.

AI and robotics represent the latest evolution in this pattern, offering businesses significant productivity gains. However, history suggests that long-term economic success depends on balancing efficiency with workforce adaptability. As policymakers and businesses navigate this transition, the focus will need to be on maximising automation’s benefits while mitigating its disruptive effects on employment and wages.

Ultimately, the question is not whether cheap labour—human or artificial—will continue to shape the economy, but rather how best to integrate these efficiencies into a sustainable growth model.