Python has become the most popular language for using AI, and its creator believes that there’s an interesting reason why this is the case.
Guido van Rossum, who created Python in 1991 and served as its “Benevolent Dictator For Life” until 2018, has offered a compelling theory about why his language has become the dominant tool for artificial intelligence development. In a recent discussion, van Rossum drew a fascinating connection between Python’s human-centric design philosophy and its supremacy in the age of AI. His insight suggests that the same qualities that made Python accessible to human programmers have made it surprisingly learnable for AI systems.
“You still need to write code, and Python is still a fantastic tool to write code,” van Rossum explained. “Because Python is very human friendly, that almost automatically makes it also AI friendly because the same brain cells that help us interpret human language and generate human language also help us understand programming languages, because the languages have been designed to sort of put all kinds of things that are similar to human languages.”
Van Rossum elaborated on this linguistic parallel with a specific example: “I mean, ‘if’ and ‘for’ are keywords that weren’t chosen randomly.” This observation highlights a fundamental aspect of Python’s design—its keywords and syntax were deliberately selected to mirror natural language patterns and human reasoning. The choice of words like “if,” “for,” “while,” and “in” wasn’t arbitrary; these terms directly correspond to how people think and communicate about logical operations.
Drawing his argument to its logical conclusion, van Rossum predicted: “So I expect that AIs will just learn to work with whatever language works well for humans.” This statement reframes Python’s dominance in AI not as a historical accident or the result of superior technical features, but as an inevitable consequence of how both human and artificial intelligence process symbolic information.
The implications of van Rossum’s observation extend beyond Python itself. His theory suggests that as AI coding assistants like Claude Code and Cursor become more sophisticated, the programming languages that thrive will be those designed with human cognition in mind. This could explain why Python, despite being slower than compiled languages like C++ or Rust, has become the lingua franca of machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. The language’s readability and intuitive syntax make it easier for AI models—which are trained on vast repositories of human-written code—to understand, generate, and manipulate.