AI has led toward automation of different types of work in various industries, homes, and other areas. To take advantage of the prowess of AI, proper applications developed using AI are required. Programming languages are the languages used in writing different types of applications and software to be used in various computing devices. For efficient building of AI system, an appropriate programming language is essential. If the programming language used for developing a particular type of application is not suitable for that type of development, then it will result in loss of time and effort and ultimately a poor-quality product. Thus, selection of a suitable programming language before developing is necessary. 

Let us look at a few AI programming languages you should know in 2024, if you want to learn AI. 

Python: Python is a programming language that lets you work more quickly and integrate your systems more effectively. You can learn to use Python and see almost immediate gains in productivity and lower maintenance costs. Python can be easy to pick up whether you're a first time programmer or you're experienced with other languages. Python is developed under an OSI-approved open source license, making it freely usable and distributable, even for commercial use. Python's license is administered by the Python Software Foundation. 

Java: Java is a programming language and a platform. Java is a high level, robust, object-oriented and secure programming language. Java was developed by Sun Microsystems (which is now the subsidiary of Oracle) in the year 1995. James Gosling is known as the father of Java. Before Java, its name was Oak. Since Oak was already a registered company, so James Gosling and his team changed the name from Oak to Java. 

Javascript: JavaScript is mostly used in creating highly interactive browser-based applications. It’s primarily a client-side scripting language that runs directly on users’ browsers. As a result, it can help perform various computation tasks and improve the performance of AI applications. It’s also valuable when implementing real-time AI applications like virtual assistants, chatbots, and recommendation engines. 

Prolog: Prolog is recognized for its strength in logic programming and symbolic reasoning, which facilitates the development of AI applications, particularly regarding knowledge representation and problem-solving. Its declarative nature allows developers to specify the logic of computations without worrying about the underlying control flow. Developers can represent rules, relationships, and facts in a straightforward manner, making it a suitable choice when creating knowledge bases in AI systems 

Lisp: Lisp is a high-level functional programming language suitable for AI development, specifically due to its adaptability and support for symbolic expression processing. Symbolic expressions can represent both code and data, which can be primitive types like strings and numbers, or complex data structures like lists and arrays. This unique feature helps Lisp applications perform complex computations and manipulations on large data sets, making it particularly suited for AI applications.