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Transformation of Corporate Social Responsibility Practices: Adapting Artificial Intelligence and Internet of Things

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2023)

Abstract

Data processing applied science techniques like artificial intelligence and the Internet of Things are grand inventions in tech history that are revolutionary themselves. This highly advanced and intelligent mechanism calls the attention of business concerns and enterprises to implement these applications to facilitate the productivity of the establishments gain better results from Corporate Social Responsibility (CSR) activities and achieve sustainable development goals. In this study, the author examines how innovative technologies like AI, IoT, and blockchain are executed by organisations to assist CSR operations and be effective instruments for economic resilience and security. The study focuses on how AI and IoT can transform CSR initiatives by automating tasks, improving efficiency, and enabling new and innovative ways to engage with stakeholders and address social and environmental challenges. For this purpose, the researcher comes to grips with various monitoring reports and examination papers to collect statistics regarding technologies and CSR and implement the same from a different perspective and also explore the challenges faced due incorporation of this automation are measured in this overview. Finally, the author concludes this study with suggestions that may be utilized in the forthcoming research and academic work.

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Correspondence to Samta Kathuria .

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Khare, S., Uniyal, V., Kathuria, S., Chauhan, A.S., Akram, S.V., Aluvala, S. (2024). Transformation of Corporate Social Responsibility Practices: Adapting Artificial Intelligence and Internet of Things. In: Santosh, K., et al. Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2023. Communications in Computer and Information Science, vol 2026. Springer, Cham. https://doi.org/10.1007/978-3-031-53082-1_14

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  • DOI: https://doi.org/10.1007/978-3-031-53082-1_14

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