This week we are diving into AI use cases across decarbonisation, regulatory compliance and client data requests, human rights in the value chain, ESG performance and risk assessment, and sustainability reporting.
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Sustainability teams are expected to deliver credible emissions reductions across complex operations and value chains, often with fragmented information, limited capacity, and increasing expectations on transparency and decision quality. Start here: WBCSD and Accenture give you a high-level framework and structure for thinking about where AI can help. You will also discover how to move beyond AI pilots and keep human review where it matters, plus ten lessons for business leaders. Dig further for more slides and resources. [Read more]
Listen to this podcast episode, where IBM's CSO, Christina Shim, shares how her small team kept up with growing sustainability regulations. Inundated with questions from client account teams and regulators, the team built AskSustainability, an AI agent that brings 50 data sources into one place the whole company can access. Response times to clients in the sales cycle fell 60%, with $120 million of pipeline revenue supported in the first five months of the year. The important takeaway is their approach and the return it delivered, because you do not need to be IBM to do the same with a free tool like NotebookLM. [Listen here]
With hundreds of thousands of suppliers, Amazon is experimenting with AI around its supplier social audits. The point is not to make a human rights team obsolete, but to help it deliver more. Before audits, a model built on tens of thousands of past audits flags suppliers unlikely to meet Amazon's supplier code of conduct. In testing, it caught about 9 in 10 high-risk sites. After audits, an AI tool checks each report's risks against that code, rates their severity and suggests next steps. An early version of the tool helped Amazon process reports 65% faster, and experts review every recommendation. This is a high level piece, but there is enough in it to discover how to do the same with existing AI tools. [Read more]
ESG data points multiply faster than any team can work through by hand. At BNP Paribas, bankers assess clients' ESG performance and risks partly through an internal questionnaire that feeds credit decisions, can hold up to 80 questions and takes hours to fill in. To cut that time, the bank's sustainability team launched an AI assistant that suggests answers from client ESG documents, with source links. Answers are not pre-filled, and bankers select and double-check any suggestion they use, staying responsible for the final answer. 600 users adopted the assistant, used in around 35% of ESG assessments and rising. [Read more]
Manual processes and scattered data take teams away from the strategic work that drives progress. AI can help you win that time back, and this playbook's five-step framework, tested in Google's own environmental reporting, shows how to do it with tools already out there. Discover prompts to copy and examples of Google using AI to check draft green claims against internal guidelines before human review. Another example shows bringing public reports into one AI tool, so client-facing teams can give customers accurate, consistent answers with citations. [Read more]