Human intelligence and AI: expanding the boundaries of strategic adaptability
By Lorenzo Bona
In an age increasingly characterized by the disruptive advent of artificial intelligence (AI), it is easy to reduce the concept of intelligence to mere computation, prediction, or optimization. Yet, human intelligence is something fundamentally different: in simplified terms, it could be seen as a unique mechanism, socially and individually relevant, that allows errors, mistakes, and failures to occur, and more importantly, enables learning from them.
It is this capacity for adaptive learning through trial, error, and interaction that makes human intelligence a cornerstone of socio-economic life. Across economic thought, human intelligence has been interpreted in different ways, reflecting distinct assumptions about decision-making and economic behavior.
Four Economic Perspectives
In this light, four main lines of reasoning appear particularly influential in socio-economic studies and relevant for business strategies: the human capital approach, the rational choice logic, the behavioral economics framework, and the Austrian economics perspective.
Although they differ in emphasis, these four lines of reasoning collectively seem to portray human intelligence as adaptability to constraints, uncertainty, and change. Rather than viewing intelligence as mere computational power, these perspectives appear to converge, to a large extent, on the idea that intelligence is largely a social trait that enables humans to cooperate more efficiently and adjust effectively to challenging and evolving economic environments.
In other words, each of these perspectives appears to highlight the strategic relevance of adaptation, and a possible way to express this is as follows:
Human Capital → Adaptive Capacity
Intelligence can be viewed primarily as the ability to learn new tasks and re-skill when conditions change.
Education and training programs allow individuals to be better prepared to respond adequately to changing technologies and labor markets.
Adaptation occurs mainly through: Investment in capabilities (for example, via education or training programs) that enhance long-term flexibility and productivity.
Rational Choice → Adaptive Optimization
Intelligence can be largely interpreted as the ability to adjust choices in response to changes in prices, incentives, and constraints.
Individuals adapt by reallocating resources efficiently when circumstances shift.
Adaptation occurs mainly through: Rational and optimal adjustment to new information and changing incentives.
Behavioral Economics → Adaptive Adjustment Under Limits
Intelligence can, in large part, be understood as shaped by bounded rationality, reflecting situations of decision-making under conditions of imperfect information.
Consequently, humans tend to rely heavily on heuristics and rules of thumb to navigate complex environments.
While shortcuts may lead to biases, they often function as practical adaptations.
Adaptation occurs for the most part through: Context-dependent strategies under pressure rather than perfect optimization.
Austrian Economics → Adaptive Discovery
Intelligence can be largely conceived as encompassing both individual and collective dimensions: at an individual level, it is expressed through entrepreneurial alertness – the capacity to discover opportunities and revise plans under under conditions of uncertainty and dispersed knowledge, drawing on situational and context-specific knowledge; at a collective level, intelligence functions as a process that interprets dispersed knowledge and uncertainty, giving rise to spontaneous, self-organizing, and evolving structures such as markets and other adaptive systems (e.g., customs and social norms).
Markets themselves function as adaptive and self-organizing systems coordinating many limited intelligences through prices and competition.
Adaptation usually occurs through: Entrepreneurial alertness, experimentation, and learning from market feedback.
Human Intelligence as a Dynamic Mechanism
Taken together, these perspectives suggest that human intelligence is best understood as a dynamic capacity for adaptation, not a static or purely calculative ability. Its uniqueness lies in embracing mistakes as part of the learning process, enabling individuals, groups, and societies to experiment, reorient strategies, and discover new opportunities in the face of uncertainty. Human intelligence is therefore not only a cognitive skill but also a social and economic mechanism that drives learning, resilience, and progress.
Human Intelligence and AI: Concluding Insights
AI and Society
AI can be seen as a largely computational mechanism – extremely efficient at performing specific tasks, processing vast amounts of data, and optimizing predefined objectives, whose effects may appear increasingly reflected in the rapid expansion of automation in work contexts, reshaping – and in some cases challenging the viability of – established economic roles and professions.
However, rather than being seen as a threat that could replace human intelligence, AI can be understood as a tool to extend it, freeing individuals to focus more fully on strategic sense-making, creativity, and entrepreneurial discovery.
From this perspective, the central challenge is not to resist AI, but to ensure two things:
That the potential of AI is fully exploited to improve productivity, efficiency, and innovation.
That social, economic, and institutional arrangements evolve in ways that allow human adaptability to continue driving progress.
By combining the computational power of AI with the adaptive, learning-oriented, and entrepreneurial capacities of human intelligence, societies appear better positioned for possible discoveries of new opportunities that allow them to expand their ability to navigate uncertainty, leverage technological advances, and foster sustainable economic growth
AI and Business
On the other hand, from a business strategy perspective, firms that embrace experimentation, curiosity, and continuous learning – particularly in response to AI-enabled opportunities – appear better equipped to increase their chances of securing a lasting competitive edge
Practically speaking, to achieve this advantage, firms could accelerate the integration of human intelligence and AI by, for example:
forming or expanding cross-functional teams that bring together professionals such as AI analysts and business strategists to co-create strategic plans;
running small-scale pilot projects to experiment and learn before scaling initiatives;
continuously integrating market and AI-derived feedback into decision-making to adapt rapidly to change.