ESG reporting & disclosure with targeted AI prompts

ESG reporting and disclosure are becoming increasingly complex and critical for organisations, driven by evolving regulations such as the CSRD, rising stakeholder expectations, and the need for transparent, reliable, and high-quality reporting. Collecting, managing, and interpreting ESG data, drafting disclosure narratives, and ensuring accuracy across multiple frameworks can be time-consuming and prone to error.

This cheat sheet provides sustainability teams with practical, AI-driven prompts to facilitate the ESG reporting cycle. By offering AI prompt examples and guidance on how to write AI prompts and how to structure AI prompts, it helps teams standardise and validate data, draft compliant narratives, and enhance report quality, while maintaining essential human oversight and professional judgement. The guide also highlights eco-friendly AI practices and the sustainable use of AI, considering the environmental impact of AI prompts in reporting workflows.

Building on foundational principles from Guide 1: Mastering ESG AI prompting fundamentals, this cheat sheet delivers actionable techniques for efficient workflows, consistent reporting, and credible disclosures across multiple standards. It integrates generative AI capabilities and demonstrates best prompts for AI in ESG contexts, ensuring outputs are both accurate and trustworthy.

By combining AI with human expertise, the guide enables faster ESG reporting, improved consistency, and clear communication of organisational ESG performance to stakeholders. It also addresses common challenges, ethical considerations, and practical approaches for AI prompting for sustainability and AI prompting for climate, helping teams produce reliable disclosures while maintaining professional judgement.

What you’ll find inside

Chapter 1: Data collection and management facilitation

• Challenges in gathering consistent ESG data from internal operations, suppliers, and external benchmarks

• Using good AI prompts to classify, flag, and summarise ESG data

• Checklists for identifying critical data streams, preparing templates, and version control

• Example AI prompt examples for anomaly detection, missing data, and summarising trends

• Practical exercises for drafting and testing prompts

Chapter 2: Drafting CSRD-compliant ESG disclosures

• Aligning disclosure content with regulatory requirements and materiality principles

• Using AI to generate first draft narratives from structured data

• Checklists for outlining sections, refining drafts, and integrating stakeholder feedback

• AI prompt examples for environmental, social, and governance disclosures

• Exercises for creating prompts and reviewing AI-generated drafts

Chapter 3: Quality assurance and narrative enhancement

• Ensuring reliability, consistency, and clarity in ESG reports

• AI prompts to check data alignment, flag unsubstantiated claims, and suggest narrative improvements

• Checklists for multidisciplinary review, iterative feedback, and audit preparation

• Exercises for testing prompts against draft disclosures

Chapter 4: Practical situations and AI prompt examples

• Real-world scenarios including incomplete supplier data, technical content simplification, report consistency checks, and audit readiness

• Example prompts and intended outcomes for each situation

• Summary checklist covering data management, disclosure drafting, and quality assurance

Download now to start using AI-driven prompts for faster, more accurate, and transparent ESG reporting.