We find ourselves at a critical juncture in the economic evolution at which we must define the relationship between humans and technology. Nearly every industry

and every type of work will be actively disrupted by technology advances, if they haven’t been already. We have seen, for example, the impact robotics has made on augmenting physical labour in our workforce and how artificial intelligence (AI) has enhanced knowledge work.

As new technologies continue to be adopted into our workplaces, we are forced to confront questions about how to move workers up the value chain alongside innovation, and moreover, to solve for how we will centre humanity in the further development of AI.

It is our view that over time, AI and other automation technologies have the potential to make work more human — not less — by freeing up time and energy for workers to focus on uniquely human capabilities such as creativity and judgment. That is, if leaders value, nurture and prioritize these skills.

For far too long, leaders have focused on developing technology at the expense of human intelligence — and even humanity itself. As a result, we are often presented with the false dichotomy that the future of work is either human or machine, but cannot be both. However, the next era of leadership will in fact centre around unlocking, creating and leveraging human intelligence in the workplace in relationship with technology, rather than in competition. To do so effectively, it is imperative for leaders to gain a better understanding of the strengths and limitations of each.

Artificial intelligence: made in our likeness

There is no doubt that much of the fear regarding the technological disruption of our workforce is real. Headlines abound about how AI is ‘coming for’ most workers today, with many experts projecting profound job loss. It’s not that we don’t believe AI will disrupt the way we work, but we do believe that many of these fears are overstated.

The fact is, just like tech innovations that came before it, in many cases the strengths of AI are limited without the application of human intelligence alongside them. To understand this better, let’s begin to unpack where AI’s strengths begin and end.

In effect, AI serves as a simulation of various aspects of human intelligence processes, but carried out by machines, especially computer systems, with the goal of enabling them to perform tasks such as visual perception, speech recognition, decision-making and language translation. Its processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction.

Despite the digital revolution transforming how businesses operate, the expected surge in productivity has been elusive.

The backbone of AI is machine learning, a subset of the technology that focuses on developing computer programs that can access data and use it to learn for themselves. Foundational to machine learning is the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Many leaders often confuse generative AI advancements such as ChatGPT (which create new content based on vast amounts of broad datasets) with machine learning (such as facial recognition), which considers data patterns and provides predictive analysis within a particular context or domain.

AI excels when large datasets of past behaviours are available and can appear intelligent within this confined context. When these parameters are met, AI’s capabilities boast significant advantages in data processing, pattern recognition and automation. The unparalleled ability to process and analyze vast amounts of data reaches far beyond human capability and enables organizations to derive meaningful insights for better decision-making, innovation and competitive advantage.

Likewise, pattern recognition through machine learning helps to reveal patterns and anomalies with remarkable accuracy, which is crucial in various applications from financial fraud detection to diagnostic imaging in healthcare. By recognizing these patterns, AI can also predict outcomes, allowing organizations to anticipate and respond proactively to future scenarios.

And lastly, the automation of performing repetitive tasks more quickly, accurately and tirelessly than human workers is transforming industries. This automation ranges from simple tasks such as data entry to more complex processes such as manufacturing and quality control. By automating routine tasks, AI allows humans to focus on higher-level, creative and strategic activities, leading to increased productivity and innovation. This point is critical for leaders to understand if they are to implement the technology in ways that are effective for businesses and their people.

Why technology needs humans

While AI promises to usher in a new era of productivity based on its capabilities, leaders are confronted with what is known as the ‘productivity paradox.’ This term encapsulates the curious observation that despite the exponential growth in technology and innovation, productivity growth — particularly in developed economies — has not kept pace. This paradox is a critical puzzle for business leaders to solve, one that demands a nuanced understanding and strategic response.

At its core, the productivity paradox challenges the conventional wisdom that advancements in technology directly translate to increased productivity and, by extension, to economic growth. Yet, since the late 20th century, despite the digital revolution transforming how businesses operate, the expected surge in productivity has been elusive.

This discrepancy raises important questions about the nature of technological progress and its real-world impacts. First and foremost, it underscores the complexity of technology adoption and challenges the idea that simply investing in the latest tools and platforms is a panacea for productivity challenges. Instead, it proves that it must be effectively integrated into workflows, and employees need to be adept at leveraging these tools to enhance their work. The human element — how individuals interact with technology — plays a pivotal role in unlocking productivity gains. To combat this paradox, leaders must realize where humans excel over machines. In the realm of technology and human capability, the core insight that has emerged with resounding clarity is that human intelligence is fundamentally characterized by its depth in emotion, context and judgment. This contrasts starkly with AI, which, despite its advancements, remains inherently linear, sterile and heavily reliant on vast repositories of historical data, so far incapable of replicating these subtle dimensions of human cognition.

When it comes to forming predictions and making decisions, the distinction between the two forms of intelligence is quite remarkable. Leaders seeking to unlock both would be wise to consider how to leverage each strength appropriately within their strategic decision-making process.

Emotion: Human intelligence thrives on a rich tapestry of emotions and the ability for discernment, enabling individuals to experience and interpret the world in a profoundly complex manner. Emotions are not mere responses to stimuli; they are intricate processes that influence -, creativity, empathy and social interactions. The ability to feel joy, sorrow, love and fear adds a layer of depth to human understanding that AI, in its current form, cannot grasp. Furthermore, emotional intelligence allows humans to navigate social complexities, build relationships and make decisions that consider the well-being of others — aspects that algorithms and machine learning processes cannot authentically replicate.

Context: Another cornerstone of human intelligence encompasses the ability to understand the nuances of different situations and adjust behaviour accordingly. Humans can discern subtle cues such as cultural norms, body language and the emotional state of others, to interpret situations with more sensitivity and understanding. This contextual awareness that comes naturally to humans enables a flexible and adaptive approach to problem-solving, compromise and interaction, which AI struggles to emulate despite its ability to process and analyze data at an unprecedented scale. Ultimately, AI’s interpretation of data is still confined to the parameters set by its creators and lacks the ability to perceive the intricacies of real-world scenarios beyond its programmed experience

Judgment: Deeply intertwined with emotion and context is judgment, or the capacity to make considered decisions. Human judgment involves weighing various factors, including ethical considerations, potential outcomes and impact on others, to arrive at decisions that are not only logical but also morally sound. This aspect of human intelligence reflects the ability to think critically, reflect on past experiences, and project potential futures. AI, by its nature, is bound by algorithms and predictive models that rely solely on historical data. It simply lacks the capability to make value-based judgments or to understand the moral and ethical implications of its actions based not on what was, but what is and could be.

While it represents a monumental leap in technology’s capacity to process information and automate tasks, AI falls short of replicating the essence of human intelligence that is critical to sound and ethical decision-making. Moreover, its reliance on past data means it operates with a retrospective view, lacking an understanding of the present moment’s dynamic and ever-changing nature.

As leaders, the opportunity for technological advances to positively reshape the way we work is dependent on our ability to reframe and invest in human intelligence as a complementary and equally valuable resource to AI. We must demonstrate this through a willingness and enthusiasm to upskill the workforce to keep pace with change and by centring humans in our approach to leveraging innovation.

At the heart of all of this change is the imperative for leaders to lead differently. That is the only way they will acquire and retain the talent needed to meet the potential of the technology age, stay relevant in their market and positively impact the world we live in.

This article is an adapted excerpt from the book, Essential: How Distributed Teams, Generative AI, and Global Shifts Are Creating a New Human-Powered Leadership (Wiley, 2025). It originally appeared in the Spring 2025 issue of the Rotman Management Magazine. If you enjoyed this article, consider subscribing to the magazine or to the Rotman Insights Hub bi-weekly newsletter.