As Artificial Intelligence becomes more popular, it’s essential to know the best programming languages AI uses.

If you’re trying to code an AI software solution and don’t know which programming language(s) to use, it can hinder – even hurt – your development process.

However, there are a lot of choices when it comes to programming languages you could use to develop an AI solution. So if you’re wondering what the best programming languages for AI are, you’re at the right place!

Origin of AI

Artificial intelligence (AI) has been around for a very long time. Therefore, it cannot be considered an innovation in 2022. We have seen, used, and become accustomed to this area of technology, which is continually improving.

However, AI development has become increasingly popular among individuals and businesses recently. AI development seems like the best option because it offers advantages like improved customer experience, intelligent decision-making, automation, fewer errors, and data analytics.

However, after you have made this decision, you must also make a difficult choice about a programming language for AI development. You should know which language works best for your project from the many options. We’ve compiled a list of programming languages for artificial intelligence to help you make an informed choice.

Top 12 the best artificial intelligence programming languages

1. Python

Python development is one of the most popular programming languages globally and a top choice for AI developers.

It’s easy to learn, runs on multiple platforms, and provides an interactive environment that allows you to quickly test ideas and make changes without waiting for a compile or deployment phase.

Python development is also one of the fastest-growing languages in popularity and employment opportunities. You can use Python development in various AI applications, including natural language processing (NLP), machine learning, deep learning, and robotics.

Python development has also been used in data science applications such as web scraping, web crawling, and scraping data from websites.


LISP stands for List Processing Language or LISt Processor. It is a functional programming language that makes it easy to create functions that can manipulate lists of data items. John McCarthy created this language at MIT in 1958.

It remains in use today because it is still an excellent vehicle for research in logic programming and because of its continued wide use in artificial intelligence applications such as natural language processing for semantic web applications.

LISP is also great for creating neural networks because it can easily manipulate the network’s weights, which is usually the most challenging part of building a neural network.

Lisp became the most popular programming language for artificial intelligence after being developed primarily as practical mathematical notation for computer programs. Lisp is responsible for developing higher-order functions, tree data structure, conditionals, dynamic typing, automatic storage management, self-hosting compiler, recursion, and read-eval-print loop, among other programming innovations. In addition, Lisp offers flexibility, garbage collection, information process capabilities, dynamic object creation, rapid prototyping, and other features.

3. R

R is a free software environment for statistical computing and graphics that runs on multiple platforms, including Windows, Unix, macOS X, and Linux operating systems. Ross Ihaka created R and Robert Gentleman at the University of Auckland, New Zealand, in 1993, originally under the name “S.”

R provides different analysis methods such as linear regression, generalized linear models, time series analysis, classification, and clustering.

The main advantage of using R is that it allows users to develop complex algorithms without having to write complicated code or spend time debugging the code.

R is your go-to programming language for analyzing and expressing data. DPLYR is a sophisticated package with a simple syntax used in data manipulation in R. It is a free program that can look at data, show changes and trends, and help with forecasting.

Through user-created packages, R’s capabilities can be expanded to include a variety of statistical techniques, import/export capabilities, tools, graphical devices, and so on. As a result, language is becoming increasingly popular among data scientists and analysts.

Its popularity has increased significantly over time due to its ease of use and flexibility from simple linear regressions to multi-level modeling approaches.

4. C++

It is one of the most popular and widely used programming languages for developing AI solutions. It is a general-purpose language used to create software applications, operating systems, and other programs.

BjarneStroustrup originally developed C++ to enhance C with object-oriented features. Its popularity has increased due to its ability to support multiple paradigms, including object-oriented programming (OOP), imperative and procedural programming techniques, generic programming, and others.

5. JavaScript

Netscape Communications Corporation developed JavaScript in 1995, but the standardization of JavaScript only began in 1997 when Ecma International adopted it as ECMAScript.

JavaScript is a programming language used by over 65% of developers to create interactive web pages. It is prevalent because you can run it on all modern browsers without installing plug-ins or additional software.

You can use JavaScript to create web pages and applications on web browsers and mobile devices like smartphones and tablets.

JavaScript also has an object-oriented structure, making it easy for programmers to build complex programs using multiple objects.

The interaction that is compatible with other source codes, like Html and CSS, is where JavaScript’s AI skills shine. It can handle front and backend tasks, including data storage, buttons, and video.

A few high-level Machine Learning libraries and tools are included. It provides developers with numerous additional options and runs directly in the browser. A web-based dashboard also lets users see the results of machine learning algorithms.

6. Java

Java is one of the most popular programming languages in the world. As a platform, it has excellent support for AI development. You can use Java for developing machine learning algorithms, deep learning frameworks, and other tools.

Many of the most popular libraries and frameworks are written in Java, including Hadoop and TensorFlow.

Java supports large projects essential in AI/ML, visualization, debugging, and user interaction. You can quickly get help because it has a large online community. Java debugging is simple. It is a favourite among software developers due to its ease of use and adaptability to various platforms.

Additionally, Java is a relatively safe and scalable programming language, making it an excellent choice for applications on a large scale. Regarding artificial intelligence, Java is one of the best programming languages available due to its advantages and simple code.

Java is also very popular with enterprises because it has excellent performance, scalability, and portability across different operating systems and hardware platforms.

7. Haskell

Haskell is an excellent choice for AI development because it allows for the use of a functional programming paradigm.

It means that it will enable you to write your code in a way that focuses on composing functions together instead of focusing on variables and data structures.

While this may not seem like a big deal, it makes it easier to reason about your code and make changes without introducing errors.

Haskell also has strong type inference capabilities, which allow you to focus on what your program does rather than how it does it. It also makes writing tests and ensuring that your code works as expected without manually testing every possible case.

8. Julia

Julia is a high-level, high-performance programming language that makes coding fast and efficient. It’s great for AI development because it’s flexible and easy to learn. Julia combines the speed of C with the usability of Python, making it ideal for numerical computing.

Julia is a multi-paradigm programming language that allows you to write code in numerous styles – from functional to imperative, object-oriented to metaprogramming – all within the same program.

You can hire an AI developer to take advantage of the best tools for each task instead of forcing everyone down a single path.

9. Prolog

One of the most popular programming languages for developing AI solutions is Prolog. It was developed in 1972 and used for decades as a powerful logic programming language.

Prolog uses an underlying theory called predicate logic based on facts, rules, and inference.

Prolog became popular due to its ability to represent knowledge in a form that can be queried and reasoned about. It makes it ideal for solving problems that require reasoning about the world.

Another reason Prolog is so famous for developing AI solutions is because it allows you to hire AI developers to combine logic programming with declarative programming through pattern matching and unification.

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10. Scala

Scala is a general-purpose programming language that runs on the Java virtual machine. It can be used in distributed and parallel systems, developing scalable software applications.

Scala is easy to learn because it integrates object-oriented languages with functional programming features.

It was developed by Martin Odersky in 2001 at École Polytechnique Fédérale de Lausanne in Switzerland as an academic research project. Many companies have used Scala to develop AI applications.

It has an advantage over other programming languages because it allows to hire AI developers to get the best of both worlds, i.e., object-oriented and functional programming paradigms.

Scala is statically typed and uses JVM for execution. You can use Scala for building web applications and big data applications.

11. RUST

The Rust programming language is one of the most popular languages for developing AI solutions. It was developed by Mozilla and was released in 2010.

The main goal of Rust is to provide a safe, fast, productive, and memory-safe language.

Performance is one of the main features of the rust programming language because it can work on a low level with C/C++ and other systems programming languages.

Rust is also suitable for machine learning because you can use it to write efficient code without sacrificing safety or performance.

12. Wolfram

Wolfram is a programming language and environment for technical computing, data science, and machine learning.

Students, teachers, researchers, and commercial developers worldwide develop applications that range from technical and scientific to financial analysis, music generation, and art creation.

Wolfram is a great place to start if you’re new to programming because it has a clean syntax that makes it easier to understand than other languages.

It’s also inherently visual – you can build your code by dragging blocks together on a canvas. So you don’t need to spend time learning how to write code from scratch before getting started.

Now that you know about the various languages, do you need clarification about what is the best programming language for AI? Programming languages for AI include Haskell, Java, Python, Julia, and Lisp. A good AI programming language should be simple to understand, use, and read. But which programming language is best for AI? For most developers, Python is the best programming language for artificial intelligence. Java, C++, and JavaScript are other top contenders, but Python is probably the best all-around option for AI development.

Other Programming Languages for Artificial Intelligence

In addition to the languages mentioned above, numerous others compete to develop AI. Matlab, Smalltalk and Go are the unmentioned heroes and the multiple libraries and frameworks that make Artificial Intelligence development possible. As the list goes on, developers, businesses, and companies all agree that Python is the most preferred language for Artificial Intelligence development.The reason why Python is the best choice includes the following:

  • Easy to lean
  • Well-integrated
  • Well-documented
  • Platform independent
  • Easy and simple to learn
  • Excellent visualization tools

Wrapping up

Whether you are choosing a language to help build the future of technology in AI or if you are looking for a new language to learn, you must consider the features of the programming language before jumping in.

Many factors affect the choice of languages, such as cost, scalability, and maintainability.

In this article, we try to analyze each language’s strengths and weaknesses, but it is crucial to understand what you want to achieve, how much you spend, and your time schedules for implementation.

We hope this article will help you decide which programming language suits your needs to hire an AI developer.