Mar 10, 2024
min read

Python vs Other Languages: The Dominance in AI Development

The rise of AI last year has proven the reign of Python. Read this material from the AI development team at Uni to learn about how this happened and why Python is among the top choices for AI projects.

Python’s recognition among developers is skyrocketing at break-neck speed. Although it’s commonly appreciated for data analysis and web development, the influence of Python for AI (artificial intelligence) development couldn’t be overestimated.

Uni stays at the forefront of AI-based approach in software development, so we couldn’t miss a chance to explain why you should choose Python for your AI project. Read the comprehensive overview from senior Uni developers. Contact us for more information about Python and other languages for your projects.

Is Python’s Popularity Well Deserved?

Foremost, let’s glance back at the Python’s origin. Since its development in 1991, it has been an interpreted and dynamically typed language. It means that coders don’t need to compile the code before running, introducing a drastic difference from how they used to work before. Moreover, Python’s code structure and syntax are straightforward, allowing developers to write less.

Python is widely used anywhere from Google to your startupping neighbor next door. That’s why, if you face a problem, you can address it to a vast community of Pythonists, willing to help. There is likely a ready-made solution for you out there.

For this purpose, we contemplate how Python was chosen as the prevailing language for AI development and if we can replace Python for AI programming with alternatives. Stay tuned, and let’s move on.

Advantages Of Python

Again, as another proof of Python’s worldwide dominance, it sat the first lines in the TIOBE index in 2023 as the most commonly used programming language. No wonder, since it is beneficial to developers, learners, and businesses. Let’s list the major examples relevant to Python AI programming.


We believe that Python’s comprehensiveness is the number one reason why it is widely adopted in almost every coding niche, including AI programming Python. The easy-to-learn and easy-to-apply syntax turns Python into a common tongue among coders. Also, it fosters AI development since non-programmers like data scientists could use Python for work despite having no solid knowledge of coding.

Moreover, Python’s code is undemanding in maintaining and sharing. Especially when compared to languages like Java, Python generates very legible, concise code


Python commands are written in an Integrated Development Environment (IDE) as text files with instructions for the interpreter. Also, there are plenty of built-in features, namely code browsers, debuggers, grammar checkers, text editors, etc.

Furthermore, the vast selection of third-party solutions, components, and modules simplifies the development process, unit testing, and AI programming with Python in particular. For example, NumPy, Pandas, SciPy, and more bolster Python’s potential for large-scale projects.

Fast Progress

Since Python forces coders to close tasks faster, overall development boosts, benefiting overall business and Python and AI time-to-market metrics.

Python is a dynamic scripting language, allowing coders to deal with the code like stacking Lego blocks rather than writing it from scratch. Besides, the interfaces between components are clear, and the components are reusable, amplifying the progress.

As a result, the development process is hastened as compared to other languages, granting Python one of competitive advantages.


Python works on various platforms. Besides, its code is easily convertible without any modifications for various platforms, in particular, Linux, Windows, MacOS, and UNIX. This is because Python is platform-independent due to its byte-code compilation and interpreted nature.

Moreover, Python offers portable Graphical User Interfaces (GUIs) for Python-based apps. GUIs help users interact with the apps visually while coding. It’s more accessible and convenient since you don’t have to use command lines anymore.

To further improve portability, Python has a virtual environment utility that makes dependency management simple, which is especially valuable for AI for Python.

Extended Community

Since Python is an open-source programming language, it has an active community, offering a plethora of ready-made components. Nearly 200,000 unique software applications have already been submitted by users to an online repository. Nice, eh?

It’s more than any other open-source community offers. Numerous open-source AI frameworks, tools, and platforms have already been created in Python and are accessible, all for free.


Python’s code flexibility is not among its top characteristics, however, it’s still better than average. Nevertheless, Python’s use cases are very extended, thanks to its ability to suit object-oriented and procedural programming modes, as well as introducing data types.

Numbers (amounts), Strings (names), Lists (order), Tuples (restrictions), Dictionaries (indexes) let us rearrange and organize data according to the needs of exploratory data analysis and overall Python AI programming. So much simpler!

Python and Other Programming Languages

Since we’ve described most of Python’s killer features, let’s compare it to other languages in a quick overview.


JavaScript is the same dynamically typed language as Python. However, JavaScript is designed mainly for front-end web programming, while Python’s use cases are much wider, including web development, AI programming with Python, and data analysis.

In view of simultaneous operations, Python utilizes multi-threading (although the Global Interpreter Lock (GIL) may restrict this). At the same time, JavaScript supports concurrent tasks due to its usage of asynchronous operations and callbacks. It equals them at this point.

Nonetheless, there is a point where Python beats JavaScript. It’s Python's data science and machine learning package. They are unmatched thanks to data visualization features and more.

And the last but not least reason why Python outperforms JavaScript is that Python is more secure, making it simpler to adopt best practices and prevent safety problems.


Unlike Python, C++ is a statically typed language. It’s renowned for its fast performance and system-level programming features. Python is not so fast unless optimized, but it has other perks as a Python AI language.

Foremost, C++ and Python are different in memory distribution. C++ supports manual memory management, which gives developers complete control over memory allocation. Python, on the other hand, implements automated memory management via garbage collection, automating the process.

Then, as in the case with JavaScript, Python guarantees more security due to its dynamic typing and vast standard library. Indeed, C++ is more powerful but prone to overcomplicated and erratic code.


Ruby is often described as “more of a work of art than a programming language” In some ways this is correct, but in this case the art doesn’t pay off. Python for AI is simply more common and less complicated.

Both languages have good syntax, but Python is far more predictable. When something goes wrong, you can say where and when the error occurs in most cases. Ruby pulls in the slack in that.

Next, if we compare the simplicity, both languages are good. Except that Ruby is less accepted beyond its devoted community, while there are rows of educational resources on Python.


Both Python and PHP are suitable for server-side scripting. Like Python, PHP also provides various web development frameworks, such as Lavarel and Symfony. However, Python's libraries are more cohesive and well-developed.

Generally, both languages are high-level, interpretable, and object-oriented. PHP's Object-Oriented Programming is more chaotic, although it strives to become more organized over time.

Why is Python used for AI more often than PHP? Another stumbling block in PHP is syntax. Python prioritizes simplicity, while PHP's syntax is comparable to C-type languages, making it more difficult and puzzling. As a result, the worse training experience of PHP makes it less appealing to newcomers.


Although Lisp has dynamic semantics similar to Python’s, its approach is opposite to Python’s one so much that comparing them becomes absurd. How to compare straightforward syntax with a lack of it?

However, Python has introspective features comparable to Lisp. Typically, Common Lisp is large (in every sense), while Python offers a single, free, small implementation, which makes AI programming with Python attractive.


Java is known as the most commonly used language for building web applications on Android. For this purpose, coders relish almost every package they need from a wide variety of libraries, yet Python can even score over Java in terms of support.

At the same time, Python is interpreted and Java is compiled, meaning that the potential errors occur at runtime and compile-time to the same extent. Due to its interpretability, Python is a more productive programming language than Java. So, Python requires fewer lines of code for the same task.

Finally, Python provides a more intuitive learning experience. Still, this does not scare away beginners who choose to learn Java with its extra coding anyway.


We hope we’ve managed to prove that the Python AI language is a great option for machine learning because of its extended library ecosystem, powerful visualization features, low entry barrier, active community, flexibility, readability, and platform independence.

However, the choice is yours whether to follow the path of world-class companies that picked Python or opt for more selective languages. Anyway, Python stands out in the coding landscape and, in many aspects, outperforms its rivals as a programming language.

Uni will keep a finger on the pulse of the trends in AI scripting, so we’ll keep you informed. Remember, you can rely on our expertise; we’re here for consulting and new fascinating projects.


Is Python used for AI programming?

Python's developer community and appealing learning curve favor choosing Python as the number one language for AI development. The truth is, Python has already won the race as a leader in AI systems since it’s more comprehensive for data scientists and other development team members.

Which is better for AI, Python or Java?

Python and Java are the two most popular languages for AI development. Although Python is simpler and more advanced in many aspects, the choice of programming language for your AI project will depend on how you want to use that AI.

For instance, Python would be your best option when it comes to data analysis. However, Java would be the ideal language for AI in mobile apps.

Is Python development more cost-effective than other languages?

Python is an open-source programming language, which means no licensing costs are necessary to use it. Furthermore, this language reuses dozens of open-source frameworks, libraries, and development tools from community repositories, allowing cost savings and faster delivery.

Igor Marga
Tech Lead
Never get behind of the latest uni news.
Subscribe to news
Latest blog posts
work with us:
Let's devise a plan and make a real impact. Let's make it big!
Back to top