Inteligência Artificial - contributo para os ESG

O caso da RAR Açúcar

Authors

  • Beatriz Germano Henriques Departamento de Economia, Gestão, Engenharia Industrial e Turismo, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
  • Beatriz Rodrigues Matos Departamento de Economia, Gestão, Engenharia Industrial e Turismo, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
  • Letícia Afonso Lourenço Departamento de Economia, Gestão, Engenharia Industrial e Turismo, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
  • Manuel Luís Au-Yong-Oliveira GOVCOPP, University of Aveiro

DOI:

https://doi.org/10.34624/iciemc.v0i6.40169

Keywords:

ESG, Artificial Intelligence, Optimization, Energy efficiency, RAR Açúcar

Abstract

Our study analyzes the integration of Artificial Intelligence (AI) as a contribution to ESG (Environmental, Social and Governance) practices. Through qualitative and exploratory research, based on interviews and field analysis, followed by data and content analysis, we focused on the case study of RAR Açúcar, a benchmark company in the portuguese agri-food sector. From the information gathered and analysed, we can conclude some problems and possible solutions, including: (1) Optimizing supply chain traceability using AI and blockchain; (2) Implementing an artificial intelligence system focused on two critical dimensions of supplier management, to guarantee social responsibility practices in the supply chain and optimize the procurement process; (3) Adapting and eventually implementing the SATO platform in RAR Açúcar's industrial environment, in order to improve the energy efficiency of industrial facilities. Although the company is still at an embryonic stage of technological transformation, it demonstrates an openness to innovation and a commitment to 2 sustainability. Our study aims to reveal the potential of AI to support more sustainable, efficient and ethical business practices. Future research in different sectors will be necessary to validate and deepen the conclusions.

References

Published

2025-06-22