The European Union plays an important role in promoting the Sustainable Development Goals (SDGs) of the 2030 Agenda through the advancement of sustainable finance. The aim of sustainable finance is to direct financial resources toward initiatives aligned with ESG (Environmental, Social, and Governance) principles. However, unlike financial ratings based on recognized accounting standards, a globally shared framework for assessing ESG activities and investments is still lacking.
To fill this gap, the EU has launched a process to develop common standards for identifying sustainable economic activities, not only from an environmental but also from a social perspective.
In this context, the proposal for a European Social Taxonomy has emerged, developed by the Platform on Sustainable Finance (PSF). Its goal is to classify projects, investments, and policies based on their social impact. The three main objectives identified, decent work, well-being and adequate living conditions, and inclusive societies, are supported by sub-goals to facilitate implementation and reporting.
Nonetheless, the analysis of social variables remains particularly complex due to their qualitative, multidimensional, and often subjective nature, which makes objective and standardized measurement challenging. In the absence of a global social reporting standard, practices remain heterogeneous and fragmented, undermining data comparability and the development of evidence-based policies.
In this scenario, Public Administrations (PAs) are called upon to adopt effective tools to make their social actions visible, measurable, and communicable. The Final social balance sheet serves as a key tool for accountability and transparency, useful for strengthening the relationship with citizens and evaluating the public value generated.
The integration of the Social Report, the Social Taxonomy, and Artificial Intelligence (AI) represents a strategic opportunity to improve the analysis, monitoring, and implementation of social policies in alignment with the 2030 Agenda. This study analyzes the approach adopted by local administrations in social reporting and the potential of AI to enhance these processes, promoting more effective and sustainable public governance.