The introduction of Artificial Intelligence (AI) in sociolinguistic analysis has helped to improve the analysis of code-switching (C-S) in multilingual conversations. This paper investigates the effectiveness of various AI programmes, such as Natural Language Processing (NLP) and Machine Learning (ML), in finding and analysing the linguistic phenomena of C-S. AI-powered models enable the automatic recognition and processing of many languages from a single utterance, improving the accuracy and efficiency of sociolinguistic research. AI in sociolinguistics allows for a more in-depth understanding of language dynamics, cultural exchanges, intricate dialects, and accent variations. Nonetheless, there are challenges when applying AI in sociolinguistic research, such as algorithm bias, the requirement for diverse linguistic data, and ethical considerations. Thus, this article looks at recent research on AI's role in sociolinguistic analysis to interpret the positive and negative effects of AI on C-S analysis. It aims to raise awareness about AI's revolutionary role in enhancing sociolinguistic efforts to understand and analyse C-S in multilingual situations, with a focus on C-S in Indian communities.