PhD. student Mengyuan SHEN from School of Management Fudan University, argues that AI and humans are not rivals but co-evolving partners in an endless race for survival and progress. The challenge isn’t to outpace machines but to harmonize our creativity and ethics with their precision and power. In this new era, evolution is collective and adaptability, not dominance, is the ultimate strength.

Evolving Artificial Intelligence: Co-evolutionary dynamics are reshaping business and society by Mengyuan Shen.

Throughout history, humans have reinvented themselves through the breakthroughs of the Industrial Revolution. In the 18th century, the invention of the spinning Jenny marked the beginning of the first Industrial Revolution. The 19th century saw the widespread use of electricity and the invention of the internal combustion engine, ushering in the age of electricity. Driven by advances in atomic energy, computers, space technology, and bioengineering, the 20th century saw the emergence of the third Industrial Revolution.

Today, the fourth industrial Revolution, led by artificial intelligence (AI), is rapidly unfolding. We stand at a crossroads between innovation and tradition: the relationship between humans and AI is no longer just between creator and creature. The interplay between human cognitive accumulation and machine learning iterations is redefining the concept of progress. We are at a moment in history where we are co-evolving with machines. This symbiotic dynamic is creating a synchronized and balanced niche between humans and technology. “Will AI replace us?” has lost urgency. Instead, we urgently ask: How can we harness this coevolution to serve the common good?

In Through the Looking-Glass by British author Lewis Carroll, the Red Queen tells Alice: “Now, here, you see, it takes all the running you can do to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!” In a dynamic world, life must stay in motion to adapt and survive. In the rapid evolution of digital code and silicon-based intelligence, it is only by exploring new visions – reshaping industries, leadership and innovation – that we can move beyond mere competition and realize our innate drive for constant evolution.

Learning from Nature – The Red Queen Theory and Human-AI Relations

In Through the Looking-Glass, although the Red Queen drags Alice through mountains and valleys, they never really leave the starting point. Leigh Van Valen, an evolutionary biologist, has found that a species’ ability to survive does not inherently improve over time; Instead, extinction risk between species remains random. In 1973, Van Valen introduced the “Red Queen theory” into biology to construct coevolution between species through a dynamic perspective.

The theory explains the randomness of extinction by saying that when one species increases its ability to adapt and reproduce, it puts pressure on other species in the same ecosystem. To survive, competing species must evolve. As a result, species in an ecosystem constrain each other, resulting in minimal relative evolutionary change. The rate of evolution of a species must be consistent with its co-evolving system to ensure inter-generational survival.

Since then, the Red Queen theory has been expanded. Barnett’s research shows that in organizational ecology, competition drives growth: organizations adapt to the competitive environment by competing with each other to achieve better evolution and development. Conversely, organizations that fail to adapt to the new competitive logic run the risk of collapsing under external pressures.

In nature, plants and animals have evolved characteristics to adapt to environmental changes through natural selection. In human history, our evolution has paralleled the evolution of tools. From this perspective, the human drive to augment AI – and the self-improvement of AI through machine learning – represents an inevitable sociological “natural selection.”

Consider the competitive coexistence between prey and predator: slow rabbits are eaten by wolves, fast rabbits survive, and wolves must run faster to avoid starvation. This reflects an evolutionary process of co-adaptation. Similarly, less intelligent AI products gradually fade out of the market, while advanced AI products flourish. In order to get rid of the anxiety of “machines      being replaced”, humans strive to improve their intelligence. As a result, there has been a co-adaptive evolution between humans and artificial intelligence.

New Competitive Logic – Competition and Collaboration Between Human and Machine Intelligence

Robots and workers have long competed on production lines. In China, the reform and opening up policy triggered the second wave of economic globalization. Within two decades, farmers from all over the country had flocked to the Pearl River Delta, turning farmland into a manufacturing hub. However, rising labor costs have eroded the region’s competitive advantage. With the development of robotics and artificial intelligence, the revolution of “machines replacing humans” has intensified.

From a human perspective, low-end manufacturing moved west, with workers moving to less automated industries. Labor resources have been redistributed, and human resources have been applied with higher value. Emerging manufacturing powers later used the robot revolution to regain their competitive edge, reabsorb displaced workers, and fuel economic growth.

From a machine point of view, the robotics industry in the Pearl River Delta fills the labor shortage. Machine learning and pattern recognition technologies enable smarter operations, ensuring the dominance of AI in industrial hubs around the world. With the advantages of round-the-clock productivity, low cost and standardized output, artificial intelligence occupies more roles.

In this race, both human and artificial intelligence are evolving. As Ray Kurzweil in The Singularity Approaches, the collective intelligence of AI could go beyond mere external augmentation to become a catalyst for human evolution within. As stated in Xunzi·Jiebi: “How does one comprehend the Dao? Through the mind.” AI’s ability to analyze massive data sets, optimize processes, and produce creative output forces us to emphasize uniquely human traits – critical thinking, creativity, and meticulous judgment – to complement the precision of machines.

In auto manufacturing, giants such as Toyota and General Motors have long pursued efficiency through lean manufacturing. Today, they integrate artificial intelligence algorithms to optimize supply chains and assembly lines. The role of humans has shifted from repetitive tasks to overseeing automated networks. A similar trend is occurring in the electronics industry: Foxconn has adopted robots to address labor shortages, but humans are still essential for adaptable, intuition-driven tasks.

In addition to manufacturing, AI will reshape services. Banks deploy algorithms to detect fraud and streamline operations, shifting the role of humans from day-to-day processing to advanced analysis and decision-making. In healthcare, diagnostic AI helps doctors; In retail, smart logistics optimizes delivery. The story is clear: AI augments human capabilities, not replaces them. In this rapid evolution, survival depends not on dominance, but on homeostatic equilibrium – the Red Queen balance in which humans and AI constantly improve their strengths to avoid being eliminated.

Beyond Silicon – Threats and Reflections in Adaptation

The future of human-AI interaction is both exciting and worrying. Breakthroughs such as brain-computer interfaces and immersive virtual reality blur the lines between human cognition and machine processing. However, challenges loom.

On May 12, 2017, WannaCry ransomware attacked Windows systems worldwide and later spread to Android devices. More than 150 countries were affected: critical data in China was encrypted, British hospitals came close to collapse, and hundreds of thousands of people were harmed. If such attacks wreak havoc today, imagine their impact on a fully AI-integrated future where everyone carries or merges with AI devices.

The challenges of AI are multifaceted. Cyberattacks, algorithmic bias, information silos, and data privacy require strong governance and ethics. Moreover, AI risks widening social divisions. As AI becomes indispensable, those without access to cutting-edge education or technology risk being left behind.

These challenges force us to ask deeper questions: In an age where machines are collaborators, not just tools, how do we balance efficiency with safety, ethics, fairness, and human dignity? These issues are redefining AI governance and business ethics, prompting a reevaluation of security protocols, leadership models, and collaboration frameworks.

Today’s leaders must not only allocate resources, but also foster an environment where human creativity and machine intelligence work together. This requires a shift in mindset towards adaptability, ethical governance and inclusiveness, focusing on how humans and machines collaborate, innovate and connect.

Tesla embodies this balance. By integrating AI into production and design, it optimizes batteries and streamlines the supply chain. However, its success also depends on workforce development: retraining programs enable employees to manage and innovate in an AI-enhanced environment. Tesla’s model shows that AI integration can drive operational excellence while fostering a culture of learning.

In healthcare, IBM Watson analyzes global clinical data to help make treatment decisions and improve diagnostic accuracy. Its real strength lies in collaboration: combining data-driven insights with the nuanced judgment of doctors to ensure effective, compassionate care.

In the financial sector, JPMorgan Chase has deployed AI to detect fraud, enhance customer service and reduce errors. However, human analysts and managers remain critical in interpreting AI-generated data and strategic decisions.

The co-evolution of humans and AI goes beyond technology or leadership, it shapes the society we aspire to build. Business leaders must ensure that technological advances do not widen social disparities or undermine dignity. Organizations and individuals must innovate relentlessly to ensure that progress is a collaborative pursuit of collective well-being rather than a zero-sum game. As AI systems learn and evolve, we must reconfigure social, ethical, and governance paradigms to promote a future of symbiosis between silicon-based intelligence and humans.

The Path Ahead – Embracing Collective Evolution

The evolution of AI is not an end point, but a new beginning for human labor – a threshold that requires adaptability, innovation, and a redefinition of human nature. From an evolutionary perspective, survival does not depend on current fitness, but on future fitness. The lesson of the Red Queen is clear: To thrive in a world of constant innovation, humanity must maintain its creative passion, constantly evolving to avoid obsolescence.

Lessons from manufacturing, health care, finance, and retail show that human ingenuity and machine efficiency are not locked in a battle for dominance, but in an endless parallel evolutionary process.

There are many moments in history that force us to reimagine our potential. Just as computers revolutionized our understanding of information, AI will redefine intelligence, creativity, and collaboration. Although imperfect and unsolved, artificial intelligence has surpassed any previous tool in human history. The promise of AI lies in its ability to force us to look beyond our limitations, harness the potential within us, and work together to create a better, more equitable future.

Useful links:

• Link up with Mengyuan Shen on LinkedIn
• Read a related article: AI for Common Good: The tug-of-war for control and conscience
• Download this and other articles in the special issue June 2025 Global Voice magazine
• Discover School of Management Fudan University, China
• Apply for the International MBA at Fudan.

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