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Studying critiques of human capital theory, particularly through the work of Michel Foucault, raises important questions about the relationship between capitalism, labor, and productivity. Foucault argued that under neoliberal systems individuals increasingly become viewed as forms of capital whose value is measured by productivity and economic returns (Foucault, 2008). Critics of neoliberal capitalism suggest that firms operating within shareholder-driven models may prioritize efficiency and profitability objectives, sometimes creating tensions between capital accumulation and worker welfare.
Recent comments by Standard Chartered Group Chief Executive Officer Bill Winters have renewed debate regarding the changing role of human labor in the workplace. Winters stated that the bank's strategic direction was focused on replacing some “lower-value human capital” with investment and technology (Reuters, 2026). Following public discussion around the statement, he later reassured staff that employees remained highly valued within the institution.
His remarks raise several important questions:
• Why has human capital seemingly lost some of its competitive advantage to technology, particularly artificial intelligence (AI), in sectors such as banking?
• Why is AI increasingly attracting investment?
• Why is technological innovation perceived as generating greater value?
This article attempts to explore these questions through perspectives drawn from critiques of human capital theory, labor economics, and technological change.
We are currently living through a period of disruption driven by technological advancement, particularly AI. This is not the first time economies have experienced such transformation. During the Industrial Revolution, mechanization altered production systems significantly. In agriculture, for example, the introduction of machinery such as combine harvesters dramatically reduced labor requirements while increasing productivity. Although some workers became displaced, others adapted through reskilling or movement into new economic sectors.
Similar developments appear to be occurring today. AI and technological innovation are changing how organizations allocate resources and structure their workforce.
Returning to the Standard Chartered example, the argument being made is not necessarily that humans are becoming irrelevant. Rather, organizations are increasingly reallocating investment toward roles that complement technological systems and away from tasks that can be automated.
This raises important questions regarding the future job market, particularly for new entrants into the financial sector. Automation increasingly allows institutions to perform operations with leaner workforce structures. What factors are driving this trend?
One explanation is the evolution of AI itself. Earlier forms of automation performed relatively narrow tasks. However, current generations of AI technologies can execute more sophisticated activities with minimal human intervention. Modern applications can process information, generate written outputs, summarize complex documents, and support decision-making processes.
From an economic perspective, firms evaluate technologies based on productivity and value generation. Comparative studies and organizational assessments increasingly indicate that AI can perform some tasks rapidly and at scale (Brynjolfsson & McAfee, 2014).
AI's major comparative advantage lies in processing speed and scale. Human intelligence often performs optimally when given sufficient time for reflection, analysis, and collaboration. For example, developing a new concept traditionally involves extensive research, consultation, and discussion before decisions are reached. Such processes may take days or weeks.
By contrast, AI systems can rapidly process and synthesize large quantities of information, enabling certain tasks to be completed more efficiently than traditional workflows.
Globalization also contributes to this transition. Financial institutions now operate through increasingly integrated systems connecting global headquarters with regional and domestic markets. Technology facilitates these interconnected operations efficiently.
However, this raises another question:
Where will human involvement remain essential?
Human contribution is likely to remain particularly important in areas involving judgment, ethical reasoning, accountability, creativity, and strategic oversight. While AI can support tasks, humans remain responsible for determining goals, interpreting broader contexts, and taking responsibility for outcomes.
Many emerging opportunities are therefore likely to involve technology-related skills. Those possessing competencies in areas such as data science, software development, AI systems management, and digital innovation may be positioned advantageously within future labor markets.
This trend has important implications for educational institutions and training systems. Universities and other learning institutions may need to strengthen programs aligned with emerging technological value chains and future workforce demands.
Career choices are also influenced by broader social factors. Research suggests that gender disparities within science, technology, engineering, and mathematics (STEM) fields often arise from multiple factors including social norms, access to opportunities, educational exposure, and role models rather than inherent differences in capability (UNESCO, 2023).
In Zambia and many other countries, technology-related sectors continue to exhibit gender imbalances. Increasing inclusion in these fields may therefore become increasingly important.
The broader message emerging from workforce restructuring is that training systems cannot remain static. Curriculum development needs to respond pragmatically to labor market changes.
Where skills become scarce, labor market theory suggests that individuals possessing those skills may command higher compensation due to demand exceeding supply (Becker, 1964). Organizations invest in competencies that generate productivity and competitive advantage.
However, concerns remain regarding how benefits from technological transformation will be distributed.
If technological gains primarily benefit capital owners while labor displacement increases inequality, questions of social justice and development emerge. Policymakers and regulators may therefore have an important role in ensuring that technological progress contributes to inclusive development rather than widening disparities.
This calls for think tanks, policymakers, and development institutions to critically examine emerging labor market trends and their social implications.
From the perspective of factors of production, firms allocate resources toward areas expected to maximize returns. Economic theory suggests that resources generally move toward higher-value uses in pursuit of efficiency and optimization (Pareto, 1906).
Nevertheless, labor market transitions are rarely straightforward. Workers affected by restructuring experience different outcomes depending on opportunities for retraining, labor market conditions, and the transferability of their skills.
Reskilling therefore becomes essential.
For example, in appraisal processes AI may assist with initial screening, data synthesis, and pattern recognition. Human intelligence remains critical in defining evaluation criteria, exercising judgment, and making final decisions.
Humans and AI should therefore be viewed less as competitors and more as complementary systems.
Humans possess comparative advantages in areas such as accountability, ethical reasoning, emotional intelligence, and decision-making under uncertainty.
For graduates and young professionals entering the workforce, this transition presents opportunities as well as challenges. Building competencies in technological tools and digital systems may provide a significant advantage.
According to Rogers' Diffusion of Innovation Theory, early adopters frequently benefit from emerging trends because they adapt more quickly to change (Rogers, 2003).
Those who understand and embrace technological transformation may therefore become early beneficiaries of evolving labor market conditions.
Technological change is unlikely to stop because of existing power structures. Capital tends to move toward areas where value and returns are perceived to be highest.
However, humans should not lose agency in this process.
The challenge is not whether technology should advance; technological progress is inevitable.
The real challenge is determining how societies can ensure that innovation strengthens rather than weakens human inclusion, dignity, and opportunity.
References
Becker, G. S. (1964). Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education. University of Chicago Press.
Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W.W. Norton.
Foucault, M. (2008). The Birth of Biopolitics: Lectures at the Collège de France, 1978–1979. Palgrave Macmillan.
Pareto, V. (1906). Manual of Political Economy.
Reuters. (2026). Standard Chartered CEO comments on AI, investment, and human capital.
Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press.
UNESCO. (2023). Women in Science Report.
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