Whether you realize it or not, Artificial Intelligence is becoming more prevalent in everyday life. According to trusted sources, the market for AI software will be valued at $62 billion in 2022, a 21% increase over 2022. Marketing, e-commerce, education, travel, and even hospitality are all using Artificial Intelligence. AI is now used by 51% of e-commerce businesses and mobile app development companies to give their consumers an amazing user experience.

AI has helped firm app developers develop and realize their full potential throughout the years. By 2027, the worldwide Artificial Intelligence industry is predicted to be worth $267 billion. In 2019, the global Artificial Intelligence market was valued at USD 27.23 billion, and it is predicted to rise at a 33.2% CAGR to USD 266.92 billion by 2027.

Some AI programming languages excel at handling and analyzing massive volumes of data. The app developers can select the ideal language for their project by first knowing about them in detail and characteristics. So, let’s get started!

The Best AI Development Languages to Take Advantage of


Python is currently the best language for Machine Learning research and development due to significant app developers’ community support. According to Google Trends, Python language interest among app developers has grown over the preceding five years when compared to other programming languages such as Java, Scala, R, Prolog, Julia, and so on. What makes Python such an excellent language for Machine Learning applications? This language is easier to learn and needs less coding. Python has a pretty simple syntax. That is, if the developer already knows another programming language, learning Python will be much easier.

This ease of use greatly accelerates the entire coding and execution process. As a result, Python is the greatest alternative for every mobile app development company that wants to get started with offering AI development services. Furthermore, Python is a well-known programming language with a large number of free libraries that help to reduce the effort and time spent throughout the development cycle. Python’s popularity has grown by 18.5% in the last five years. It has become one of the most widely spoken languages on the planet. It’s used to construct desktop and mobile apps, internet applications, hardware programming, and other software. It is also trustworthy and efficient.


Isp was one of the earliest languages used to build Artificial Intelligence. List processing was one of the first Lisp applications, appearing in 1958. Because of the language’s advancements, John McCarthy, the language’s designer, was able to deal with Artificial Intelligence difficulties by 1962. Even though Lisp remains quite powerful today, developers seldom utilize it as their first choice because of its challenging syntax and complex libraries. However, knowledge of Lisp may be useful for a range of AI applications, including but not limited to,

  • Rapid prototyping
  • Dynamic object creation
  • Executing data structures as programs
  • Modifying programs as data
  • Mandatory garbage collection

Lisp is well-known for its extreme adaptability and ability to materialize ideas.


Java is the language of choice for all app developers for a wide range of applications, including client-server web apps, Android apps, AI and Machine Learning applications, search algorithms, multi-robot systems, server-side programming, and neural networks. Neuroph, Apache OpenNLP, Java Machine Learning Library, Deep Java Library, and MLlib are some well-known Java AI libraries and frameworks. Google, Netflix, Uber, Airbnb, Instagram, Spotify, Amazon, Slack, and Instagram are among the Fortune 500 companies that use Java.


JavaScript, like Java, is an excellent tool for AI development. It is, nevertheless, used to develop more dynamic and secure websites. JavaScript is suitable for developers who enjoy coding, but Python is suitable for those who do not. The AI features of JavaScript allow for smooth interaction and operation with other source codes like HTML and CSS. Like Java, JavaScript has a big developer community that aids in development. Frameworks such as jQuery, React.js, and Underscore.js make AI programming easier. JavaScript is capable of handling both frontend and backend tasks such as video, buttons, and data storage. JavaScript guarantees development security, performance, and speed.


Another good object-oriented programming language that may be utilized for AI applications is C++. Its fast processing speed allows it to draw complicated Machine Learning models, allowing them to work more efficiently. C++ offers some really helpful features. It generates concise code that allows for extremely efficient module execution. There are no runtime type errors because it is a statically typed language. C++ is a popular AI programming language because it supports dynamic load balancing, adaptive caching, memory management, and a variety of other features. Did you know that C++ is the quickest programming language? AI development needs a solid grasp of C++. Without a doubt, speed is an important advantage and that’s why every mobile app development company will definitely have a C++ team.


Julia may not have a large user base or community, but it does provide a variety of cutting-edge AI technologies. It is the market’s most sophisticated data analysis and statistics generating tool. Julia possesses all of the skills required to create a dynamic interface, eye-catching visuals, or data visualizations. Because of its debugging, memory management, and metaprogramming features, this language makes AI development easier. Julia is the best choice for AI jobs that need Machine Learning. Flux.JL, Turing.JL, MLJ.JL, and Metalhead.JL is among the packages available.


Haskell is a statically typed, fully functional programming language. As a result, Haskell seems to be expressive and versatile. Because of its abstraction, it lowers the requirement for time-consuming error debugging. The improved memory management, type system, and code reusability of Haskell only contribute to its attraction. One of Haskell’s most enticing features is that it is a lazy programming language. Haskell only evaluates code when it is needed. Depending on your point of view, this might be a good or bad thing. Haskell’s overall efficiency is what attracts AI app developers. Developers can type more quickly than they think.

Which AI Development Programming Language is the Best?

Python is the most popular programming language for AI, according to most developers. Java, C++, and JavaScript are other major contenders, with Python possibly being the greatest all-around alternative for AI development.

AspectsPythonJava JavaScriptC++
AI CodebasesManyFewFewFew

The finest language for AI is Python. It is simple to learn, has a sizable developer community, and a vast array of libraries, and codebases. Here are other major advantages of Python for AI development,

  • Simple to learn
  • Well-integrated
  • Well-documented
  • Crisp and straightforward to read
  • Platform-independent
  • Excellent tools for visualization

Wrapping Up

Artificial Intelligence should not be taken lightly. You use technology every day to make your life easier, from driving to booking appointments on your digital calendar. This technology is pushing the boundaries of data, technology, and programming languages. The aforementioned programming languages are appropriate for AI projects. Simply select the project that best meets your requirements. If your mobile app development company partner has a basic understanding of the language, choosing the best one for the same is straightforward.

Read more: What Is The Future Scope Of The Software Testing In India?

By Anil kondla

Anil is an enthusiastic, self-motivated, reliable person who is a Technology evangelist. He's always been fascinated at work from 7 years especially at innovation that causes benefit to the students, working professionals or the companies. Being unique and thinking Innovative is what he loves the most, supporting his thoughts he will be ahead for any change valuing social responsibility with a reprising innovation. His interest in various fields like Tech, entertainment, gadgets, travel and lifestyle that urge to explore, led him to find places to put himself to work and design things than just learning. Follow him on LinkedIn

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