Article
Optimizing Regulatory Compliance and Mitigating Legal Risks in MSME Textile Clusters: A Secondary Evaluvation of AI Tool Efficacy in Coimbatore
The textile MSME clusters in Coimbatore play a significant role in India's manufacturing sector but face increasing challenges in complying with evolving regulatory requirements related to taxation, labor laws, environmental standards, and intellectual property protection. Limited financial resources, inadequate legal expertise, and manual compliance processes expose these enterprises to substantial legal and operational risks. This study evaluates the effectiveness of Artificial Intelligence (AI)-enabled compliance tools in optimizing regulatory compliance and mitigating legal risks using secondary data from government reports, policy documents, industry publications, and academic literature. The study adopts an explanatory research design supported by thematic content analysis to assess the role of AI applications, including Natural Language Processing (NLP), automated GST compliance systems, predictive analytics, and computer vision technologies. The findings indicate that AI tools can significantly improve compliance accuracy, reduce legal violations, and enhance operational efficiency. The study also identifies barriers to AI adoption and proposes practical and policy recommendations to facilitate sustainable digital compliance among MSME textile enterprises in Coimbatore.