AI
Decoding ESG Reporting: Navigating The Puzzle With AI Assistance
During a recent conversation with the CEO of a partner company, we talked about the thorny issue of environmental, social and governance reporting. I explained how AI can identify and collect relevant data from supply chain documents needed as input into ESG reporting tools and solutions.
All it takes is an AI assistant and effective human/AI communication.
It’s no secret that many companies are struggling to adopt the Corporate Sustainability Reporting Directive and other similar mandates, which are mired in complexity, causing uncertainty and requiring major changes in organizational processes.
Successful ESG reporting is like putting together a giant jigsaw puzzle. Companies may have different strategies on how to do it, but the pieces are similar.
One piece of the puzzle would be embedding sustainability in your business strategy and highlighting your company’s commitments to the U.N. Sustainable Development Goals. That creates the foundational piece.
Another piece would be setting targets and working steadily toward them to achieve lasting impact. Other pieces include choosing the right ESG framework and conducting a double materiality assessment to determine whether a sustainability target is material to the business from either an environmental perspective, a financial one or both.
But the crucial piece of the puzzle that all the others rely on is having the right data. Collecting data from multiple sources including company internal documents or public databases, such as smart utility meters in buildings, is a challenge.
Many details required to track and measure ESG targets are available in hundreds or thousands of documents such as invoices, bills of lading, supply chain documents, and scattered bills and reports. Your company may have a manufacturing facility in one city and a sales office in another. You must be able to collect all relevant data from utility bills in both locations, for example, to determine your carbon footprint for Scope 1 reporting.
But you must also collect data such as vehicle mileage or weight of transported goods from third-party suppliers and partners to report on Scope 3 emissions. This data is much harder to collect as it may be hidden in another company’s data lake.
Solutions with third-wave AI capability—or AI assistants as our company calls them-can collect the necessary data from various sources, so you have all the data in one place, ready for use and analysis in appropriate reporting dashboards and regulatory frameworks.
As a finance leader, there are several factors you should consider before adopting an AI assistant to enhance ESG reporting processes and drive sustainable business practices.
First, consider whether the AI assistant can accurately collect, process and analyze data related to ESG metrics. At the same time, you must evaluate the AI assistant’s capabilities to ensure compliance with relevant regulations such as GDPR, the EU’s data and privacy regulation. The tool’s security measures should be robust to protect sensitive ESG information from unauthorized access or breaches.
Other important factors to consider are whether it can be tailored to meet specific requirements, such as changing ESG standards, industry guidelines and internal policies, and whether it can be easily integrated with existing enterprise systems and platforms to ensure seamless data exchange.
Make sure you choose an AI assistant that provides transparent insights into the decision-making process. It’s imperative to understand how the AI models work and to interpret results effectively, so as not to jeopardize the credibility of your ESG reporting.
And three final points to consider: Is your AI assistant scalable to handle large volumes of data, especially during peak reporting periods? Does it facilitate stakeholder engagement and communications? Have you evaluated the total cost of ownership including licensing fees, ongoing support and potential savings from improved ESG reporting efficiency?
As a finance professional responsible for collecting relevant ESG information, you may be wondering how to go about the task. Of course, you could ask interns or data entry clerks to perform this complex yet tedious and time-consuming task, but humans may fail to find all the minute details hidden within your stacks of documents.
An AI assistant can do all that with speed and accuracy beyond human capability. It can look through all your business documents within a matter of minutes to identify and examine information relevant to your ESG reporting. It just needs exact instructions.
This is where effective human/AI communication plays a role. As I explained in my recent article about demystifying prompt engineering, you don’t need to be an engineer to give AI assistants instructions. You just need to use language in a very precise, logical way.
Next, you might ask yourself, “Who on earth will be able to tell the AI assistant which documents to search for which information?” Rest assured; you won’t need to hire anyone. The employees who are already managing documents manually know better than anyone else where to find relevant information.
By upskilling current employees with AI assistants and the necessary training to craft effective commands, your employees can learn how to guide your AI assistant’s behavior, so you will quickly be up to speed when it comes to collecting ESG data.
For example, to report on your Scope 3 emissions for transporting goods from your manufacturing plant to your distribution site, you might instruct your AI assistant to search all documents from your freight provider relevant for calculating transportation carbon emissions such as vehicle type, distance traveled and fuel efficiency. You would then input that data into your ESG reporting tool to perform calculations, complete necessary forms and ensure compliance.
Once you have collected the right information, you can then proceed with completing all the other pieces of your ESG reporting puzzle, confident in the knowledge that your report is based on relevant, high-quality data. This provides you with an accurate and detailed representation of your company’s ESG practices and impacts, allowing you and your stakeholders to make more informed decisions to benefit people, profits and the planet.
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