Difference between a classical algorithm and an AI software

Simone Raponi : 12 November 2025 22:01

In the digital age we live in, artificial intelligence (AI) is gaining increasing attention. But what distinguishes a classical algorithm from AI software?

In this article, we’ll explore the differences between these two concepts in a simple and accessible way, even for those who aren’t computer experts.

Classical algorithm

A classical algorithm can be described as a series of precise, sequential instructions that a computer follows to solve a given problem. For example, imagine a classical algorithm for sorting a list of numbers in ascending order. One of the classical (but inefficient) methods we study in college is called “Bubble Sort,” which compares pairs of adjacent elements and swaps their order if they aren’t already sorted. This process is repeated until all the elements in the list are sorted.

Classical algorithms are used in various fields, such as mathematics, physics, and traditional programming.

AI Software

AI software is based on artificial intelligence, which aims to create systems capable of autonomous learning and adaptation. Take speech recognition, for example. AI software like Siri or Google Assistant can understand human language, recognize voice commands, and provide appropriate responses. These systems use machine learning algorithms, such as neural networks, to analyze sound patterns and translate them into understandable words and commands.

Main differences between a classical algorithm and an AI software

Below are some of the most notable differences between a classical algorithm and AI software:

• Adaptability : A classical algorithm is static and must be explicitly programmed to handle specific situations; it cannot adapt or learn autonomously. In contrast, AI software can dynamically adapt and learn from data.

Example : Autonomous vehicles use AI software to learn from driving experiences and improve their navigation capabilities over time.

• Data-driven decisions : While a classical algorithm strictly follows the instructions provided, AI software can analyze large amounts of data, identify patterns, and make decisions based on this information.

Example : Search engines use AI algorithms to understand user queries, analyze web content, and provide the most relevant search results.

• Problem complexity: Classical algorithms are effective at solving well-defined problems with clear rules. In contrast, AI software can tackle complex problems that require the application of nonlinear logic.

Example : AI software can be trained to recognize images of animals and distinguish between different species.

• Learning: A classical algorithm lacks the ability to learn on its own. On the other hand, AI software can be trained on input data to improve its performance and optimize results.

Example : Recommender systems use machine learning to learn from users’ preferences and suggest relevant products or content to them.

In short, classical algorithms and AI software are two different approaches to data processing and problem solving. Classical algorithms are static and follow precise instructions, while AI software is flexible, adaptable, and capable of autonomous learning.

Conclusions

Artificial intelligence is shaking the foundations of numerous industries, completely redefining our approach to problem solving, opening the door to innovative solutions and opportunities that once seemed the preserve of science fiction (see Asimov, Huxley). To fully grasp the unprecedented impact that artificial intelligence is having and will continue to have on our daily lives, it is essential to keep pace with the rapid evolution of technology. Only then can we fully embrace this revolution that will transform our interaction with technology, opening new horizons of progress and paving the way for what is, for now, seemingly limitless growth.

Simone Raponi


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