In the rush to embrace artificial intelligence, we’ve overlooked a fundamental truth: what we call “AI” isn’t truly intelligent. What we have instead is “Artificial Diligence” – a powerful but fundamentally different capability that both complements and contrasts with real human intelligence.
My journey toward this realization began a few years before ChatGPT entered the mainstream vernacular. My son, a computer science graduate student, had developed “desAIner” in 2020 – a generative AI tool that created intentionally “bad,” imperfect images to assist fashion designers.
For his research, he trained an image generation model on 513 fashion images from clothing collections, producing surreal, imperfect design visualizations. His hypothesis was that designers could use it as creative stimuli.
I had the unique opportunity to witness this research, providing my first meaningful exposure to generative AI’s capabilities and limitations. What struck me then – and resonates even more deeply now – was how his work showed that human designers transformed algorithmic outputs into aesthetic inspiration.
One designer in the study noted: “I can see, like, that would be a striped skirt, there’s a top with like more color around the sleeves… I can see this as a jumping off point.” This transformation – from synthetic computational output to real human inspiration – reveals an essential distinction between artificial diligence and human intelligence.
To navigate our AI-empowered future effectively, we need clarity about what these systems can and cannot do. It is important to keep in forefront key limitations of artificial diligence:
1. Computing Without True Contemplation: Implications for Decision-Making
Today’s AI systems can compute with remarkable consistency but without contemplation. They process vast amounts of information without understanding its meaning or significance. In my son’s study, the AI tirelessly generated a multitude of design variations without any real understanding of fashion’s purpose, cultural significance, or emotional resonance.
In David Copperfield, Charles Dickens wrote, “I never could have done what I have done without the habits of punctuality, order, and diligence, without the determination to concentrate myself on one subject at a time.” Current AI systems have punctuality and order in abundance; however, they lack the conscious determination and purposeful concentration that define human achievement.
For leaders, this means recognizing that while AI can process information consistently, it cannot contemplate meaning or purpose. Creating space for human contemplation – for asking “why” and “to what end” – remains essential for meaningful innovation and ethical deployment of technology.
2. Accelerating Business Processes Without Actual Insight: Finding the Balance
AI systems can dramatically accelerate processes without understanding or developing actual insight. They process information at superhuman speeds but cannot understand the deeper relationships, contexts, or implications of what they process.
In the desAIner study, designers valued how the system accelerated ideation: “It makes it more efficient, because then you’re not like mulling it over… when you’re wanting to crank out a collection.” Yet the system had no insight into why certain designs might resonate with people or what makes a design culturally significant versus merely novel.
Miguel de Cervantes recognized in Don Quixote that “Diligence is the mother of good fortune,” but he understood that human diligence involves purpose and direction that mere acceleration lacks. Leaders must ensure that acceleration doesn’t come at the cost of insight, that speed doesn’t replace understanding and momentum doesn’t impede discussion of implications. The right balance of efficiency and effectiveness is key.
3. Learning Logic Without Lived Experience: The Real Data Gap
AI systems learn patterns from examples without the lived experience that gives those patterns meaning. They process statistical relationships in data without understanding the real-world contexts, physical realities, or real-world human experiences behind that data.
The generative AI desAIner learned visual patterns from fashion images without ever feeling fabric, understanding cultural contexts, or experiencing how garments interact with human bodies. Its learning was purely logical, divorced from the lived experience that gives fashion its function, meaning and purpose.
This limitation means AI systems often develop what is called “brittle” understanding – knowledge that appears comprehensive but breaks down when confronted with novel situations or contextual nuances. For business leaders, this highlights the importance of integrating human experiential knowledge into AI-driven processes.
4. Leveraging Innovation Without Human Intuition: Creative Collaboration Strategies
While AI systems represent remarkable technological innovations, they lack the intuition, imagination, and inspiration that drive truly creative breakthroughs. They can recombine existing elements in novel ways but currently cannot imagine what has never existed or be inspired by beauty, meaning, or purpose.
In my son’s research, it was the human designers who brought intuition and imagination to the process, seeing potential in surreal images that the Generative AI itself could never understand or envision. The desAIner provided novel visual elements, but only the human designers could imagine how these elements might be transformed into meaningful, wearable designs.
Confucius advised that “The expectations of life depend upon diligence; the mechanic that would perfect his work must first sharpen his tools.” AI systems are remarkable tools, but they require the sharpening stone of human intuition, imagination, and inspiration to achieve their full potential.
While the limitations of current AI systems are real and significant, it is important to recognize that the field is not standing still. Researchers and practitioners are actively working to address some of these gaps. For example, explainable AI (XAI) seeks to make machine learning models more transparent, helping users understand how and why an AI system arrived at a particular decision. This work aims to inject a degree of “contemplation” and accountability into AI processes, supporting more informed human oversight.
Similarly, multimodal learning—where AI systems are trained to process and integrate information from diverse sources such as text, images, audio, and even sensor data—represents a step toward more holistic understanding. These systems attempt to bridge the gap between raw computation and contextual awareness, moving AI closer to grasping the nuances of real-world experience, even if true lived experience remains uniquely human.
Despite these advances, the four core distinctions above remain relevant. Technological efforts do not erase the need for human insight, creativity, and ethical judgment, but they do offer promising avenues for making AI a more effective and trustworthy collaborator.
The path forward isn’t one where artificial diligence represented by AI replaces human intelligence, but where the two work in concert, each complementing the other’s strengths. The fashion designers who participated in the study understood this balance intuitively. They valued Generative AI not as a replacement for their creativity but as a tool that “gives me a fashion base, without giving me something super intelligible… It gives me a visual clue.”
This balance – where artificial diligence of AI provides vast amounts of raw material while human intelligence provides interpretation, refinement, and direction, perhaps represents the most promising relationship between these complementary capabilities.
As leaders, we must perform proper due diligence on what AI’s artificial diligence can and cannot deliver before making strategic decisions about its implementation. This means:
Let’s call artificial intelligence what it is – artificial diligence – not to diminish its remarkable capabilities, but to understand how best to leverage AI alongside the uniquely human qualities of contemplation, insight, experience, and imagination. By thoughtfully combining AI’s artificial diligence to assist real human intelligence, we can build organizations and a future where technology amplifies, rather than subdues, our creativity, wisdom, and sense of purpose.
In a 2024 3M commissioned survey, with 10,000 respondents spanning ten countries, results show that the global public largely views AI as a tool for problem solving. The public also knows the problems they want solved – human health and health of the planet usually rank high. Solving these challenges will require a strong interplay between intelligence and diligence in both artificial and real human form.
The question isn’t “Will AI replace human intelligence?” but rather “How can artificial diligence and human intelligence work together to design and create something greater than either could alone?”
It is our due diligence on artificial intelligence that will determine whether we fashion a future of augmented human potential or diminished human relevance.
Thinkers50 Limited
The Studio
Highfield Lane
Wargrave RG10 8PZ
United Kingdom
Thinkers50 Limited
The Studio
Highfield Lane
Wargrave RG10 8PZ
United Kingdom
Thinkers50 Limited
The Studio
Highfield Lane
Wargrave RG10 8PZ
United Kingdom
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