See the potential!
The shift towards data-driven CSR management is promoted and accelerated by Artificial Intelligence. Methods to analyze and compare sustainability-related textual data will not only increase efficiency but also scalability. This is relevant, as it is time-consuming, error-prone and rather subjective to process large amounts of text manually, especially since these documents often contain rich and ambiguous natural language. A content analysis of texts about sustainability and CSR-related topics provides valuable insights, for instance regarding upcoming CSR trends. It also enables sectoral benchmarking or quality checks for sustainability reporting.
The DFGE Whitepaper “Automatic Analysis of Textual CSR Data” introduces methodologies and use cases for an automated analysis of CSR-related textual data.
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