Artificial Intelligence plays an increasingly critical role in enabling ESG-from resource usage optimisation and energy consumption to reduced environmental impacts, and advancing climate research.
Examples of AI applications in manufacturing and agriculture, among others, are already able to enable better sustainability of operations by optimising production lines and making more efficient use of inputs.
However, the environmental footprint of AI remains a concern. Computational power for AI systems could be a high contributor to energy consumption, especially for large-scale machine learning models. In addition, many companies, including Google and Microsoft, have begun to commit to renewable energy and increase the efficiency of data centres. This shows that AI innovation must go hand in hand with sustainable development.
AI is facilitating the social avenues of healthcare, education, and supply chain transparency. AI tools help businesses make sure working conditions everywhere in the world are fair. Still, some of the most problematic issues remain the rooting out of bias in AI models; algorithms have to be carefully designed to avoid reinforcing social inequalities.
Governance structures are also changing to keep pace with the rapid integration of AI into business practices. As AI becomes more embedded in decision-making, regulatory frameworks – such as the Artificial Intelligence Act of the European Union – are being developed to make the use of AI transparent, accountable, and ethical. These will help align AI development with the broader ESG goals and ensure public trust in the technology.
The author is a Bahrain-based management consultant
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