Multiple areas of artificial intelligence, such as machine learning, deep neural networks, and large language models (LLMs), have greatly influenced human communication domains via natural language processing (NLP) technologies, including text generation, translation, text analysis, sentiment analysis, etc., across various languages including English, Arabic, and others. Arabic is particularly influential among these languages, with approximately 300 million speakers worldwide, leading to Arabic Natural Language Processing (ANLP). ANLP has emerged as a successful NLP area, particularly in dialect classification, generation, and translation, with the Saudi Dialect (SD) being a notable focus due to its value in the Middle East. Various researchers have effectively utilized different types of NLP architectures across different domains, ranging from everyday use to social and business platforms, to address the challenges and applications associated with SD. This survey aims to review and summarize five years of research in this field, from 2020 to 2024, showcasing the successes achieved and identifying research opportunities to enhance the understanding and utilization of NLP in diverse SD scenarios. Additionally, the survey will shed light on the challenges encountered in acquiring SD datasets for efficient analysis using different NLP methodologies.