LISP is recognized as a suitable programming language for artificial intelligence (AI) due to its capabilities in symbolic manipulation, recursion, and meta-programming, which are essential for handling non-arithmetic problems and dynamic code evaluation. Early AI programs often focused on verbal inputs and outputs, making LISP's list processing features advantageous. Despite being considered outdated by some, LISP was specifically developed for certain applications, offering benefits over more popular languages like C, Java, or Python. Discussions highlight the language's complexity, particularly its extensive use of parentheses, which can complicate code readability and maintenance. While LISP has evolved into modern dialects like Clojure, its relevance in contemporary AI differs from earlier AI paradigms, which relied heavily on its unique strengths. The choice of programming languages in academic settings often reflects familiarity rather than optimal performance, influencing the adoption of languages like Perl and Python in bioinformatics over LISP.