The Top Programming Languages for Artificial Intelligence (AI) in 2022

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Many organizations around the world reporting plans to expand their AI strategies across many industries. As an offshore outsourcing company, we know that this technology sector is well established and has much to offer.

Artificial intelligence is gaining popularity because it has the capacity to optimize operational processes, to create innovative business models, products and services

A growing demand for AI experts means that companies need to hire developers who are proficient in programming languages that are well-suited for key AI applications.

Discover the world’s best programming languages for AI in 2022 with Bocasay, Your offshore outsourcing company.

AI: which programming language to choose? ©Canva
AI: which programming language to choose? ©Canva

What is Artificial Intelligence (AI) ?

Artificial Intelligence [AI] uses computer systems to simulate human intelligence in order to perform a wide range of tasks which would otherwise be performed by people.

Digital devices employing AI are able to perceive their environments, interact and collect data, as well as to take actions which optimize desired goal achievement.

AI-powered computer systems can perform tasks like complex decision-making, language translations, financial transactions, visual perception and self correction.

The Best AI Programming Languages in 2022


In 2022, Python was awarded Tiobe’s programming language of the year for the second  consecutive year, and was identified as the language with the highest increase in ratings for the year of 2021. Easy for beginners because of its readability, Python is a free, open-source computer programming language that is popular with machine learning and deep learning applications. It is particularly well-suited to AI applications because it offers a wide range of pre-designed libraries that optimize the AI development process. 


Java is a general-purpose and object-oriented computer programming language, designed to function across a wide range of digital systems and devices. Java applications are almost everywhere: data centers, websites, laptops, gaming consoles, supercomputers, smartphones and tablets. 

Facilitating easy scaling of complex AI applications, Java has become the go-to language for projects that require speed. With support from a range of machine learning libraries, Java is ideal for machine learning algorithms, predictive modeling, data analysis, deep learning and natural language processing.  


This language is basically one of the building blocks of the World Wide Web, alongside HTML and CSS. 

JavaScript’s AI capabilities are centered on interactivity, or how smooth it works with other source coding languages like HTML and CSS. Widely supported by programmer communities around the world, this is a highly capable language, able to manage both front-end and back-end operations, anything from designing buttons to complex data storage. 

Fun fact: As of 2022, 98% of websites use JavaScript on the client side. 

ℕ𝕖𝕖𝕕 𝕒 𝕥𝕖𝕒𝕞 𝕠𝕗 𝕤𝕜𝕚𝕝𝕝𝕖𝕕 𝕕𝕖𝕧𝕖𝕝𝕠𝕡𝕖𝕣𝕤 𝕥𝕠 𝕔𝕣𝕖𝕒𝕥𝕖 𝕔𝕦𝕤𝕥𝕠𝕞 𝕤𝕠𝕗𝕥𝕨𝕒𝕣𝕖? 𝔸𝕟𝕕 𝕥𝕠 𝕚𝕟𝕥𝕖𝕘𝕣𝕒𝕥𝕖 𝔸𝕀? 𝕊𝕒𝕪 𝕟𝕠 𝕞𝕠𝕣𝕖, 𝔹𝕠𝕔𝕒𝕤𝕒𝕪 𝕚𝕤 𝕥𝕙𝕖 𝕤𝕠𝕝𝕦𝕥𝕚𝕠𝕟. 𝕆𝕦𝕣 𝕚𝕟𝕥𝕖𝕣𝕟𝕒𝕥𝕚𝕠𝕟𝕒𝕝 𝕖𝕩𝕡𝕖𝕣𝕥𝕤 𝕨𝕚𝕝𝕝 𝕞𝕖𝕖𝕥 𝕒𝕝𝕝 𝕪𝕠𝕦𝕣 𝕕𝕚𝕘𝕚𝕥𝕒𝕝 𝕔𝕙𝕒𝕝𝕝𝕖𝕟𝕘𝕖𝕤 𝕚𝕟 𝕣𝕖𝕔𝕠𝕣𝕕 𝕥𝕚𝕞𝕖!

ℍ𝕒𝕣𝕕 𝕥𝕠 𝕓𝕖𝕝𝕚𝕖𝕧𝕖? 𝕊𝕖𝕖 𝕗𝕠𝕣 𝕪𝕠𝕦𝕣𝕤𝕖𝕝𝕗, 𝕔𝕠𝕟𝕥𝕒𝕔𝕥 𝕦𝕤 𝕟𝕠𝕨!


Endorsed by tech giants like Uber, Google, Airbnb and Facebook – the R language is not only trusted by companies shaping the future of technology, but has been an important tool for academic and research communities for decades. 

R is an open-source, free computer programming language that is widely used for data analysis and statistics. This programming language is perfect for AI applications that require analyzing and representing large amounts of data. R can easily handle data processing, pattern reporting and data predictions.


First appearing in 1972, and originally intended for Natural Language Processing, Prolog is considered a logic programming language that enables developers to efficiently represent ‘knowledge’ in a way that an artificial intelligence algorithm can comprehend and act upon it. 

It is closely associated with artificial intelligence and computational linguistics. Capable of understanding and matching patterns, of backtracking a process to find a better path, as well as to find and structure data logically, Prolog is most often used for complex problem-solving applications


Julia is a general-purpose, open-source, high-level, high-performance and dynamic programming language that can be used for a wide range of programming applications. 

It is a language particularly well-suited for numerical analysis and computational science. When it comes to its AI capabilities, Julia is great for any scalable machine learning project, as it offers premade models, algorithm help and probability programming. 

With over 8,000 Julia packages for community use, you can benefit from helpful packages like MLJ.jl, Flux.jl, Turing.jl and Metalhead.

Think outsourcing for your IT with Bocasay ©Canva
Think outsourcing for your IT with Bocasay ©Canva


Originally developed for applied mathematical notation in computer software, Lisp is one of the earliest AI programming languages. 

Despite its old age, many critical components of a robot’s operating system are still coded in Lisp, and that is why it is also a leading language in the field of artificial intelligence. In fact, John McCarthy, the inventor of LISP, coined the very term ‘Artificial Intelligence’. 

Automatic data storage management, dynamic typing and elevated order functions are only a few of its benefits. 


Another attractive language for AI programmers, Haskell offers advantages like efficient memory management, a type system, and code reusability capacity. It is a functional programming language that places high importance on code correctness. 

With advanced features offering safety and speed in machine learning environments, Haskell supports embedded domain-specific languages that are vital to AI research. One of the safest AI programming languages out there, developers using Haskell can benefit from next-level flexibility and error-handling capacity. Above all, Haskell offers efficiency that lets you do more thinking than typing. 


C++ is a low-level language that works well with hardware and machines, and has been available for quite some time. Its capacity for low-level programming makes it ideal for handling AI models in production. This is a high-performing, object oriented language that offers a rapid processing speed, perfect for use in complex machine learning models. 

It is also worth noting that many machine learning and deep learning libraries, like SHARK and MLPACK, are written in C++. There is no better language to use for resource-intensive AI applications in need of quick execution. 

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