Top programming languages for AI development



If you aspire to work in the field of AI, you may have difficulty in picking up the right programming language. Luckily you have come to right place. So I will help you in selecting the correct programming language you may need. But before that let’s know what is Artificial intelligence.

Artificial Intelligence (AI) is the study of computer science which focuses on developing software or machines that exhibit human intelligence. Developing computer systems that equal or exceed human intelligence is the crux of artificial intelligence. AI has had some success in limited domains.


The central goals of AI research are reasoning, knowledge, planning, learning, natural language processing, perception and the ability to move and manipulate objects. General intelligence is among the field’s long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI which includes various versions of search and mathematical optimization, logic, and methods based on probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience and artificial psychology.

Artificial Intelligence is a large field. It is really difficult to refer one single programming language. You can use different programming languages but not every programming language offers you the best value of your time and effort. And there is absolutely no authoritative answer as to which programming language you should use for AI project.

Types of artificial intelligence:



Weak AI – Weak Ai is a non-sentient computer intelligence, typically focused on a narrow task. The intelligence of weak AI is limited.

strong AI – Strong AI is hypothetical artificial intelligence at least as smart as a human. Such an AI would be recursive, in that it could improve itself. In successive intervals of increased intelligence, such an entity could theoretically achieve superintelligence in a relatively short period of time. One or more superintelligences could potentially change the world so profoundly and at such a high rate, that it may result in a technological singularity. Strong AI does not exist. The prospect of its creation inspires exceptions of both promise and peril and has become the subject of an intense ongoing ethical debate.

Superintelligence – Superintelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds.

Future of AI


Source: Forrester Research. Inc.

We are living in the era of Artificial Intelligence. The market for AI technologies is flourishing. Numerous startups and the Internet giants are racing to acquire them. There is a significant increase in investment and adoption by enterprises. A Narrative Science survey found last year that 38% of enterprises are already using AI, growing to 62% by 2018. Forrester Research predicted a greater than 300% increase in investment in artificial intelligence in 2017 compared with 2016. IDC estimated that the AI market will grow from $8 billion in 2016 to more than $47 billion in 2020.


Python is one of the best languages for working on AI projects. It is a popular choice for many when building AI prototypes. Clean easy code, freely typed and saves a lot of time from ridiculing yourself around handling compilation issues and rather focus on the real problem. The Python community has developed a lot of libraries and extensions to handle most common tasks used in AI projects like Plotting Graphs, Processing Data etc easily. There are also packages available for almost all AI components ranging for Bayesian Networks to Artificial Neural Networks. Mostly AI developers suggest Python for Artificial Intelligence development.


Java is a very good choice.  It is an object-oriented programming language that focuses on providing all the high-level features needed to work on AI projects. It is portable and it offers inbuilt garbage collection. AI is closely connected with search algorithms, genetic programming and the use of artificial neural networks. Java in artificial intelligence sphere may be more than useful. Programming AI in Java has many benefits as it is easy to use, easy to debug, facilitates visualization and has better user interaction. Another reason for programming AI in Java is the incorporation of Swing and SWT. These features make graphics and interfaces look appealing and sophisticated. Java is good but not as fast as C ++.



C++ is an object-oriented programming language and has influenced other languages, such as C#, Java and the latest version of C. C++ is mostly used when the program is simple, and execution speed is the most important. C++ is still much faster than Java. Statistical AI techniques such as neural networks are common examples of this. Its ability to talk at the hardware level enables developers to improve their program execution time. C++ is extremely useful for AI projects. Algorithms are written extensively in the C++  for speed execution. AI in games is mostly coded in C++ for faster execution and response time.


Selecting a programming language for AI project mainly on the sub-field. Before choosing a programming language it is important to check whether the programming language can be utilized extensively or not. Python is currently more popular among the above languages as it is viable to use for most of the AI subfields. Java and C++ are also very good languages for AI development.

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