EnerSys: GenAI for accurate ESG data, efficiency, and sustainability
AI is reshaping almost every area of business. Our Future of Professionals Report 2024 found that 77% of professional services respondents predict AI to have a high or transformational impact on work throughout the next five years. Expanding environmental, social, and governance (ESG) regulations are dramatically increasing the amount of work necessary to stay compliant. This is good news for sustainability and ESG practitioners like EnerSys, a leader in battery manufacturing and energy storage.
That’s why Christina Sivulka, Global Sustainability Manager at EnerSys, has led a push to embed AI into the company’s sustainability data collection and reporting processes. This began with collecting Scope 1 and Scope 2 emissions and resource consumption data through ESG Flo. This data management platform uses machine learning to gather utility bill data across 180 global sites in an accurate, traceable, and efficient way. It also detects discrepancies to make sure nothing is missed in the audits.
The platform also uses AI-driven project management tools to ensure quick responses to new regulations and disclosure requirements to ensure compliance. For example, it populates answers to similar disclosure questions in other ESG frameworks to save time and effort.
EnerSys is pairing its use of ESG Flo with ChatGPT Enterprise, which helps them analyze sustainability metrics, including Scope 1 and 2 emissions for cross-referencing, and extra information like travel and waste data. Not only does this ensure reliable AI output, but it also lets Sivulka and her team fill in customer sustainability questionnaires 50% faster.
This is just the beginning. EnerSys plans to use AI to write certain aspects of its sustainability reports, support story creation for specific stakeholders, and potentially review its Carbon Disclosure Project (CDP) questionnaire responses for any improvements.
Addressing concerns about trust and accuracy
It’s well-documented that AI isn’t perfect. It requires a huge, reliable database to provide comprehensive, accurate outputs. Employees must know how to use it properly to maximize its value and avoid vague, ambiguous answers that could introduce risk.
Sivulka and her team pre-empted these issues in two ways. First, they brought IT, legal, auditing, and compliance teams together to evaluate risks beforehand and implement specific controls — including flagging and rejecting proprietary information requests.
Secondly, they trained employees in areas like prompting, cybersecurity, data privacy, and bias detection. Now, anyone using the data externally must ensure it’s been reviewed by a peer.
Getting started with AI
When it comes to streamlining data collection and compliance processes, the benefits of AI far exceed the drawbacks. Our Future of Professionals Report supports this idea, finding that 78% of professionals believe AI is a force for good.
Sivulka’s advice? Adopt AI cautiously but proactively to stay ahead of the competition and growing regulations. The three vital tips she identifies to support others’ AI journeys are:
- Partner across the enterprise. Cross-functional collaboration on AI is crucial for an effective approach to sustainability and ESG.
- Engage actively with software vendors. Don’t be afraid to talk with AI software vendors. Many tools are easy to use, and many partners tailor their offerings to your business.
- Make human review mandatory. Treat the output of AI tools like human work — subject to review for accuracy and bias.
Learn more about the AI-enabled success you can achieve regarding ESG data collection, reporting, and analysis.
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