Navigating ESG Trends, Revolutionizing Supply Chains with AI

In a rapidly evolving world, sustainability has become a cornerstone for businesses. Alejandra Espinosa, ESG Product Manager, CIAL Dun & Bradstreet, emphasized the pivotal role of adopting technology and artificial intelligence (AI) in managing sustainability-related risks, especially in decision-making.

Technological tools and AI simplify data analysis and reporting based on ESG criteria, ensuring enhanced reliability and traceability. These innovations transform information capture, documentation, and dissemination, enhancing corporate transparency and providing insights into how companies address sustainability.

In 2024, emerging ESG trends are shaping corporate risk management. Global regulations are compelling companies to map ESG criteria throughout their supply chains, evident in initiatives like the European assessment of social and environmental criteria. International frameworks, such as the UN Global Compact, are propelling companies to comprehensively map and manage these risks.

According to Espinoza, the commitment to global sustainability initiatives, such as the Sustainable Development Goals, significantly influences how companies address ESG risks. Engaging in these initiatives involves reporting, developing specific strategies, and adhering to clear paths for adopted commitments, fostering corporate responsibility. 

Supply chain sustainability poses a pressing challenge for companies today due to worsening global conditions. As the climate crisis approaches a point of no return, it becomes essential for corporations to ensure their business practices are sustainable and protect the environment from further damage. According to a 2016 McKinsey report, 80% of a company's emissions occur in the supply chain. Companies recognize the crucial importance of sustainability within their supply chains and rank it among their most urgent concerns.

By integrating AI into the supply chain sustainability process, companies can play a pivotal role in fostering a more equitable and environmentally conscious global economy. The vast network of suppliers worldwide presents a significant challenge for companies in terms of tracking, collecting, and measuring environmental data, particularly related to sustainability performance. Additionally, the increasing number of government-implemented regulations adds complexity to supply chain data management. 

This is where AI has the potential to transform how companies interact with data. AI applications include sustainability data management, identifying patterns and trends to improve predictability, providing insights and suggestions for improvement. AI can monitor a company's current sustainability performance by continuously providing feedback on highly polluting actions executed daily, such as coal emissions, waste generation, water consumption, and energy usage. The use of AI can improve communication between supply chain networks as companies share real-time data.

It also provides quick feedback to decision-makers so that errors can be corrected, and improvements implemented. Moreover, AI can be programmed with technology that advises companies on areas to improve sustainability and points out departments that may be falling short. With predictive capabilities, AI can analyze inventory levels, sales patterns, and supply chain trends to help predict supply and demand.

This knowledge can help combat overproduction, reduce waste, and ensure products are delivered to customers safely through the analysis of transport routes. According to Avery Dennison, a material science company, overproduction and waste can represent approximately US$163 billion in lost inventory value.