Google: The AI Playbook to Streamline ESG Reporting

Organisations are facing increasing intricacy in sustainability reporting, a process often complicated by manual procedures, disparate data and rapidly changing standards.

In an effort to address these challenges, Google has introduced its AI Playbook for Sustainability Reporting.

This guide is built on Google’s own experience with environmental disclosure and nearly two years of directly testing AI within its reporting cycle.

The playbook presents AI as a tool to augment sustainability teams, helping them to navigate complexity and concentrate on strategic impact rather than replacing human roles.

By providing specific tools, prompts and real-world applications, Google is promoting a collaborative approach to sustainability reporting where sharing knowledge can benefit the entire industry.

The focus is on practical use, with AI leveraged to enhance efficiency, accuracy and the accessibility of information.

A framework for practical AI adoption

At the heart of the playbook is a five-step framework intended to help organisations integrate AI into their reporting workflows methodically.

The process starts with auditing manual and time-consuming tasks such as summarising policy updates or processing unstructured data from suppliers to find areas where AI could reduce operational friction.

It advises teams to differentiate between tasks suitable for simple automation and those that require machine learning.

Kate Brandt, Chief Sustainability Officer (CSO) at Google, writes on LinkedIn: “We’re releasing the AI Playbook for Sustainability reporting to hopefully make it a bit easier.

“At Google, we know that high-quality data is the foundation of high-impact climate action. But we also know the workload is immense.”

She adds: “This playbook shares actual step changes you can implement right now, like data validation, claims verification and accessibility. By sharing these tools, we hope you and your teams can spend less time wrangling data and more time acting on it.”

The framework’s subsequent steps include selecting the right AI tool for the job, building and testing a prototype against human-verified data and then documenting the solution so it can be scaled.

This final step helps ensure successful prompts and processes can be expanded from individual teams to become standard practice across an organisation.

Mapping high-value AI applications

The playbook outlines an opportunity landscape to show where AI can provide the most value. In data analytics, AI can be used to automate data management, find anomalies, pinpoint gaps in reporting and assist with peer benchmarking and supplier analysis.

For content generation, its uses include drafting narrative sections, standardising text to meet specific reporting framework requirements, summarising long documents and improving accessibility with features like automated alt text for images.

A third area, content interaction, involves using AI to change how stakeholders engage with sustainability information. This could enable users to ask interactive questions about a report, localise content for different regions or generate multimedia outputs.

As Google writes in the playbook: “You must remain the pilot rather than the passenger when it comes to AI.”

These applications show how AI can support both the technical demands of reporting and the communication tasks that sustainability teams manage.

Real-world reporting scenarios

Google shares several examples from its 2025 reporting cycle to show how its teams used AI tools in a live environment.

Google uses AI to help validate sustainability claims by checking draft statements against internal guidelines, which provides a consistent first review before human oversight.

It also employs persona-based prompting in its NotebookLM tool to test narratives.

This involves simulating how different parties, such as investigative journalists, investors or non-governmental organisations (NGOs) might scrutinise the text, which helps to identify potential weaknesses or areas that could be perceived as greenwashing.

Another practical use is supporting responses to customer sustainability queries. AI is used to generate answers grounded strictly in verified disclosure documents, which reduces the risk of providing inconsistent information.

These examples highlight a central theme of the playbook: that AI is most effective when used with clear boundaries and human supervision.

Google maintains that AI should be viewed as a collaborator that accelerates workflows, while humans maintain final responsibility for strategy and verification. By sharing its methods, Google suggests transparency and collaboration are key to the future of sustainability reporting.