Greenwashing and Consumer Trust: Unmasking Deceptive Sustainability Claims with AI-Driven Detection and Analysis A Study based in Navi Mumbai Area

ntroduction In recent years, sustainability has become a significant factor in consumer decision-making, with more companies claiming to be environmentally conscious. However, as the demand for sustainable practices grows, so does the prevalence of "greenwashing" – the practice of misleading consumers about the environmental benefits of a product or service (Delmas & Burbano, 2011). Greenwashing can undermine consumer trust and damage the credibility of genuine sustainability efforts, leading to confusion and skepticism among consumers. As a result, detecting and exposing deceptive sustainability claims has become a critical challenge in maintaining consumer confidence in green products. Artificial Intelligence (AI) offers a promising solution in addressing the complexities of greenwashing. AI-driven tools, such as machine learning algorithms and natural language processing, can be employed to analyze vast amounts of data, including marketing materials, product claims, and social media content, to detect inconsistencies or misleading statements (Lyon & Montgomery, 2015). By automating the detection process, AI can provide a more accurate and efficient means of uncovering greenwashing and identifying brands that are genuinely committed to sustainability. Moreover, AI-driven analysis can help regulators, consumers, and advocacy groups assess the authenticity of sustainability claims, thus ensuring transparency in the marketplace. This research aims to explore the role of AI in detecting greenwashing, highlighting its potential to safeguard consumer trust and promote more sustainable practices across industries. By employing AI to scrutinize sustainability claims, businesses may be encouraged to adopt more genuine environmental strategies, ultimately contributing to a greener and more sustainable future.