I am currently in Rome, Italy, and was inspired to explore the question: What does AI have in common with Michelangelo?
When we think of Michelangelo, we appreciate that he was an incredible Italian artist, sculptor, and poet of the High Renaissance. He was born on March 6, 1475, in Florence and spent most of his active life in Rome, and lived until 1564. He was blessed to live to the age of eighty-eight, a rarity in those times.
The first comparison is that both Michelangelo and AI use tools that amplify human capability. Michelangelo used chisels, pigments, scaffolds, and mastered form to make marble and plaster into beautiful masterpieces, especially David. David is a study in anatomy and proportion — and it was sculpted from a single block of marble others had abandoned as “unworkable.”
AI is a set of computational tools (models, data, pipelines) that extends what humans can design, create, predict, or automate. AI is rich in both craft and technique, and like Michelangelo, getting AI right requires deep skills. A data scientist or engineer must master feature engineering and chisel deeply to ensure an AI model is balanced, attentive to detail, and that the outcomes appear lifelike.
This same technique can be compared to Michelangelo’s crafting of David, which at the time symbolized courage, intellect, and mastery of light, and texture. Michelangelo made the statue almost life-like – a triumph of both art and science. David redefined sculpture, inspiring generations to view the human body as a reflection of divine beauty and human potential.
Another comparison is the iterative aspects of AI and Michelangelo learning his craft from apprenticeship, where he had to spend endless hours with studies and sketches to master his craft. From a data scientist or an AI engineering perspective, AI systems are trained iteratively, and each retraining enables practitioners to learn by doing, experimenting, and continually refining AI models. In other words, iterative apprenticeship is a relevant comparison to achieving great outcomes.
A third comparison is that both AI and Michelangelo are creative, yet grounded in rules. Michelangelo worked within anatomical rules, perspective, and materials, yet produced novel, expressive work. AI produces surprising outputs but within the constraints of data, architectures, and objective functions.
A fourth comparison is that both AI and Michelangelo had debates about authorship and ethics. Renaissance patrons, workshop assistants, and restoration controversies raised questions about ownership and authenticity. AI raises similar debates: who owns generated work, what counts as original, and how to manage bias and misuse. In the field of AI, issues on copyright and “fairness” abound, fueling tensions that are unprecedented. For example, Tilly Norwood is an AI-generated actress who has outraged Hollywood.
A fifth comparison is that both Michelangelo and AI have had significant impacts on culture and legacy. Michelangelo’s works changed art, religion, and public imagination for centuries. AI is already reshaping everything as we know it – industries, labor, creativity, and societal norms. AI’s long-term cultural impact is already evident in labor shifts well underway, fueling shifts in skills and educational systems, etc.
The most important comparison is the risk of misuse and the need for stewardship and advancing ethical, purposeful outcomes. Art can easily be manipulated for propaganda. Several sculptors and painters in the 16th–17th centuries created replicas of David (some in bronze, others in marble). These were not always intended as forgeries, but they sparked debates about originality and ownership of artistic genius. Florence’s government even banned unauthorized copies of David at one point, fearing it would cheapen the symbol of the Republic.
AI needs governance, ethics, and stewardship to avoid harms (bias, privacy violations, misinformation). AI currently does not have sufficient aligned safeguards that balance both innovation and safety. International jurisdictions are evolving at different rates, and rather than coming together rapidly, countries like the USA are polarized against the EU’s AI advancing pro-safety positioning.
In July 2025, Premier Li Qiang proposed establishing a global cooperation organization for AI development and governance. He emphasized that “overall global AI governance is still fragmented” and urged for a “framework that has broad consensus as soon as possible.” At the same event (World AI Conference in Shanghai), China released an action plan for global AI governance, inviting governments, international organizations, companies, and researchers to collaborate. China has promoted the idea that AI should remain under human control, be treated as a public good, and not become the preserve of a few powerful countries or corporations.
Even though many centuries have passed between the Renaissance period and our AI era, some rich comparisons and analogies can still be discovered.
As I head to Florence to see Michelangelo’s masterpiece, David, I will be appreciating not only his timeless greatness but also applauding our global AI data scientists who take on each model design like it’s a precious sculpture of art which can be molded, refined, and reshaped.
One of our core values at SalesChoice is “we make data sing.”
Michelangelo also liked to sing, and he wrote over 300 poems and sonnets, many of which explore love, art, faith, aging, and beauty. Many of his poems were set to music during his lifetime by Renaissance composers, and he had an ear for rhythm, melody, and musical expression.
In summary, we continue to be craftsmen advancing our world’s masterpieces from paint, clay, to bits and bytes – creative development continues to inspire and challenge us in new art forms. We want to ensure our AI art forms bring harmony and not discord, as we will be leaving indelible imprints for generations to come.
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