Automation in the sustainability function can be effective because the work depends on fragmented data (operational, supplier, and financial) that has to be translated into credible metrics, disclosures, and action plans.
The best automations reduce the manual burden of data collection, emissions calculation, evidence gathering, and reporting while preserving methodological consistency, auditability, and enough transparency for regulators, investors, and customers to trust the numbers.
This strategic collaboration between Nestlé and IBM Research utilises advanced generative AI and chemical language models to rapidly discover sustainable, high-barrier packaging materials, effectively compressing years of traditional laboratory R&D into digital simulations.
Mondelez International utilises an AI-powered monitoring system within its Harmony Academy Digital Platform to drive sustainable wheat farming. By analysing real-time environmental data from supplier farms, the automation provides actionable insights that optimise agricultural inputs and ensure high-level ESG compliance across the global supply chain.