RESEARCH / DOMAIN 3

Culture evolves when environments change

Core question: How do organizations adapt when environmental conditions change?

Thesis

Organizational culture is not an independent force. It is an adaptive response to environmental conditions. When technology changes the environment, culture inevitably evolves. Artificial intelligence represents the most significant environmental change introduced into modern organizations since the arrival of the internet, creating new patterns of behavior, collaboration, learning, and value creation. The organizations that thrive will not attempt to preserve culture unchanged; they will intentionally shape the environments that produce the cultures they need.

Introduction

Culture is one of the most discussed and least understood concepts in modern organizations. Leaders frequently describe culture as a set of values, beliefs, traditions, or behaviors that define how work gets done. Entire industries have emerged around measuring culture, improving culture, and protecting culture. Yet organizations continue to discover that culture shifts whenever significant environmental changes occur, regardless of their intentions.

The challenge lies in how culture is commonly viewed. Organizations often treat culture as a fixed asset that can be preserved through communication campaigns, leadership messages, or value statements. Research suggests a different perspective. Culture is not static. It is an adaptive response to the environments in which people operate.

Domain 1 established that technology changes environmental conditions. Domain 2 demonstrated that intelligence changes the nature of work itself. Together, these conclusions lead to a broader realization: when environments change and work changes, culture changes as well.

Throughout history, major technological shifts have altered the conditions under which people operate. New tools create new capabilities. New capabilities produce new behaviors. New behaviors eventually become new norms. Over time, these norms accumulate into what organizations recognize as culture.

Artificial intelligence accelerates this process because it changes not only the tools people use, but the intelligence available to them. As intelligence becomes more accessible, scalable, and integrated into everyday work, organizations will experience new forms of learning, collaboration, decision-making, and innovation. The result is not simply technological transformation. It is cultural evolution.

This emerging reality introduces a new organizational environment—one increasingly defined by Humanᴬᴵ collaboration, Collective Cognition, and interconnected Agent Ecologies. Understanding how culture responds to these environmental shifts may become one of the defining leadership challenges of the AI era.

The question for leaders is not whether culture will evolve. The question is whether they will intentionally guide that evolution or simply react to it.

Culture as an adaptive system

Few thinkers have influenced organizational change theory more than Kurt Lewin. His observation that behavior is a function of both the person and the environment—often summarized as B = f(P,E)—remains one of the most important frameworks for understanding cultural evolution.[1] Lewin famously observed, “If you want truly to understand something, try to change it.”[2] Embedded within this statement is a deeper insight: behavior is rarely changed by intention alone. Behavior changes when the conditions surrounding it change.

This principle becomes increasingly relevant in an AI-enabled world. Organizations often attempt to change culture through messaging, training, or values campaigns. Yet people ultimately respond to the realities of their environment: incentives, tools, workflows, relationships, information flows, and expectations. Change those conditions and behavior begins to shift naturally.

Edgar Schein extended this perspective by defining culture as “a pattern of shared basic assumptions learned by a group as it solved its problems of external adaptation and internal integration.”[3] Adaptation is not a byproduct of culture. Adaptation is one of culture's defining characteristics.

Peter Senge reinforced this view through his work on learning organizations. Senge argued that long-term organizational success depends upon an organization's ability to continuously learn and adapt in response to changing conditions.[4] Learning, adaptation, and environmental responsiveness are therefore not separate disciplines. They are interconnected mechanisms through which culture evolves.

Taken together, these perspectives suggest that culture should be understood as an adaptive system. It evolves in response to environmental conditions. It reflects how people collectively respond to the opportunities and constraints surrounding them. Most importantly, it cannot remain unchanged when the environment itself is transformed.

Corporate epigenetics: environments shape culture

A useful analogy can be found in biology.

Genes provide the blueprint for an organism, but genes alone do not determine outcomes. Environmental factors influence how genes are expressed. Nutrition, stress, activity, and other environmental conditions can activate or suppress biological processes without altering the underlying genetic code. This phenomenon is commonly described through the field of epigenetics.

Organizations exhibit a similar pattern.

Values, mission statements, and leadership principles provide a form of organizational DNA. They establish aspirations and possibilities. Yet these elements alone do not determine how culture is expressed in practice. The surrounding environment plays a critical role.

This perspective can be described as Corporate Epigenetics: the idea that environmental conditions influence the expression of organizational culture, behaviors, and capabilities over time.

Consider two organizations that share similar values but operate under different conditions. One rewards collaboration, experimentation, and learning. The other rewards efficiency, predictability, and risk avoidance. Although both organizations may claim to value innovation, their cultures will likely evolve in very different ways.

The same principle applies to technology. New tools alter communication patterns. New workflows change relationships. New sources of information influence decisions. New incentives shape behavior. Over time, these changes become embedded in organizational norms and expectations, creating new cultural expressions.

Culture, therefore, is not independent of infrastructure. It emerges from infrastructure. It reflects the cumulative effects of systems, processes, incentives, relationships, and technologies operating together within a shared environment.

When leaders seek to change culture without changing the environment, they often encounter resistance and frustration. When they redesign the environment itself, cultural evolution becomes far more likely.

Collective cognition and the new environment

Historically, organizations relied on individual expertise and hierarchical decision-making to solve complex problems. Intelligence was largely constrained by human capacity. Knowledge existed within people, teams, and organizational structures.

AI begins to alter these constraints.

As organizations gain access to intelligent systems, a new form of capability emerges: Collective Cognition. Rather than relying solely on individual expertise, organizations can increasingly draw upon networks of humans and intelligent agents working together to create, refine, and apply knowledge.

This shift is important because culture is heavily influenced by how organizations learn. When learning becomes faster, more distributed, and more accessible, behavior changes. When behavior changes, culture evolves.

The environment itself begins to change. Human expertise is no longer the sole source of intelligence. Organizations become Humanᴬᴵ systems operating within increasingly sophisticated Agent Ecologies, where people, agents, workflows, systems, and information interact to generate value.

These new environments create new incentives, new relationships, and new patterns of collaboration. They also create the conditions for Behavior Activation, where new capabilities encourage new actions, which in turn reinforce new habits and norms. Over time, these patterns compound into cultural change.

Technology as a driver of cultural evolution

History provides numerous examples of technology acting as a catalyst for cultural transformation.

The Industrial Revolution fundamentally altered how work was organized. Factory systems replaced many forms of distributed craftsmanship. Standardized processes created new management structures. Hierarchical organizations emerged to coordinate increasingly complex operations. New technologies did not simply change production methods; they changed organizational culture.

The computer revolution introduced a different shift. Information could be created, stored, and shared at unprecedented scale. Knowledge work expanded. Decision-making became increasingly data-driven. Organizational structures evolved to support more specialized expertise and greater information access.

The internet accelerated these trends further. Communication became instantaneous and global. Teams could collaborate across geographic boundaries. Communities formed independently of physical location. New expectations around speed, transparency, and connectivity reshaped how organizations functioned.

Sociologist Manuel Castells captured this relationship when he argued that “technology does not determine society, nor does society script the course of technological change. Technology is society.”[5] Technology and culture evolve together because each continuously shapes the other.

In each case, technology altered environmental conditions. As those conditions changed, behavior changed. As behavior changed, culture evolved.

Artificial intelligence represents the next stage in this historical progression.

AI as a new environmental force

Most discussions about AI focus on productivity, efficiency, automation, or job displacement. While these topics are important, they may overlook a more fundamental reality.

AI changes the environment in which work occurs.

For much of modern history, expertise was constrained by human capacity. Information had to be located, interpreted, synthesized, and applied by individuals or teams. Knowledge often accumulated slowly and remained unevenly distributed across organizations.

AI changes those constraints.

Information becomes more accessible. Expertise becomes more scalable. Learning cycles accelerate. Decision support becomes increasingly available. Workflows become more adaptive. The cost of accessing intelligence begins to decline.

These changes influence far more than efficiency. They influence behavior.

Domain 2 argued that intelligence changes work. As intelligence becomes more available, work itself evolves. Roles change. Expectations change. Decision-making changes. Collaboration changes. New forms of value creation emerge.

Thomas Davenport's work on analytics, artificial intelligence, and organizational performance consistently argues that the greatest value of AI comes from augmenting human capabilities rather than replacing them.[6][7] This perspective aligns closely with the Humanᴬᴵ model explored throughout this manifesto.

As intelligence becomes embedded throughout workflows, organizations experience something larger than automation. They experience Performance Compounding. Human capability, organizational learning, intelligent systems, and workflow optimization begin reinforcing one another in accelerating cycles of improvement.

As a result, AI becomes more than a tool.

It becomes an environmental condition.

And because culture responds to environmental conditions, culture will inevitably evolve alongside AI adoption.

Humanᴬᴵ and cultural evolution

The emerging organization will not be composed solely of humans. Nor will it be composed solely of intelligent systems.

It will operate as a Humanᴬᴵ environment in which people and intelligent agents work together to create value.

This distinction matters because culture has traditionally been understood as a human phenomenon. Organizational norms emerged through interactions between people. Knowledge transfer occurred through human relationships. Learning depended on human experience. Decision-making relied primarily on human judgment.

Humanᴬᴵ systems introduce a new dynamic.

Agents participate in workflows. Intelligent systems contribute recommendations. Knowledge becomes continuously available. Expertise becomes increasingly distributed across networks of humans and machines.

These changes create new patterns of behavior. Individuals can accomplish more independently. Teams can coordinate more effectively. Organizations can learn more rapidly. Innovation can emerge from combinations of human creativity and machine intelligence.

The resulting culture may differ significantly from traditional organizational models. Adaptability may become more important than specialization. Learning may become more important than information ownership. Collaboration may increasingly involve both human and non-human participants.

As these patterns become normalized, they will shape the next generation of organizational culture.

Intentional adaptation versus accidental adaptation

Every organization will experience cultural change as AI becomes embedded within work. The critical difference will be whether that change occurs intentionally or accidentally.

Organizations that approach AI primarily as a technology deployment may find themselves reacting to unintended consequences. Employees may resist new workflows. Expectations may become unclear. Existing incentives may conflict with new capabilities. Culture may fragment as different groups adapt at different speeds.

By contrast, organizations that recognize AI as an environmental transformation can take a more deliberate approach.

They can redesign workflows alongside technology adoption. They can align incentives with desired behaviors. They can invest in learning systems that support adaptation. They can establish new norms for human-agent collaboration. Most importantly, they can intentionally shape the environment that will ultimately shape culture.

This perspective shifts the role of leadership. Leaders are not merely responsible for implementing technology. They are responsible for designing the conditions in which cultural evolution occurs.

The future belongs not to organizations that resist change, but to organizations that guide it.

Conclusion

Culture has never been static. Throughout history, shifts in environment have reshaped how people work, learn, communicate, and create value. Organizational culture emerges from these adaptations, reflecting the ongoing relationship between people and the conditions in which they operate.

Domain 1 demonstrated that technology changes environments. Domain 2 demonstrated that intelligence changes work. Domain 3 suggests the inevitable conclusion: when environments change and work changes, culture changes.

Artificial intelligence represents one of the most significant environmental changes organizations have encountered. As intelligent systems become embedded within everyday work, new patterns of behavior, learning, collaboration, and innovation will emerge. These changes will reshape organizational culture regardless of whether leaders actively manage them.

The organizations that thrive will recognize a simple but powerful truth: culture cannot be preserved by holding environments constant. Culture evolves because environments evolve. Success will belong to those who intentionally design environments where humans and intelligent systems can adapt, learn, and create value together.

The architects of the edge will not be those who merely adopt AI. They will be those who understand how to redesign environments, activate new behaviors, and guide cultural evolution. In doing so, they will help build organizations capable of thriving in a future shaped by Humanᴬᴵ collaboration, Collective Cognition, and continuously expanding intelligence.

In the age of AI, the future of culture is not resistance.

The future of culture is intentional adaptation.

References

[1] Lewin, K. (1936). Principles of Topological Psychology. New York: McGraw-Hill.

[2] Lewin, K. (1947). "Frontiers in Group Dynamics." Human Relations, 1(1), 5–41.

[3] Schein, E. H. (2010). Organizational Culture and Leadership (4th ed.). San Francisco: Jossey-Bass.

[4] Senge, P. M. (1990). The Fifth Discipline: The Art and Practice of the Learning Organization. New York: Doubleday.

[5] Castells, M. (2010). The Rise of the Network Society (2nd ed.). Oxford: Wiley-Blackwell.

[6] Davenport, T. H., & Ronanki, R. (2018). "Artificial Intelligence for the Real World." Harvard Business Review, 96(1), 108–116.

[7] Davenport, T. H., & Kirby, J. (2016). Only Humans Need Apply: Winners and Losers in the Age of Smart Machines. New York: Harper Business.

[8] Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. New York: W. W. Norton & Company.

[9] Toffler, A. (1970). Future Shock. New York: Random House.

[10] Schein, E. H. (1996). "Three Cultures of Management: The Key to Organizational Learning." Sloan Management Review, 38(1), 9–20.

[11] Castells, M. (2009). Communication Power. Oxford: Oxford University Press.

[12] Lewin, K. (1951). Field Theory in Social Science. New York: Harper & Row.

[13] Weick, K. E., & Quinn, R. E. (1999). "Organizational Change and Development." Annual Review of Psychology, 50, 361–386.