Businesses are increasingly utilising artificial intelligence in order to get a broader picture of their performance metrics, and the area of sustainability is no exception.
In the sixth and final edition of its ESG series, communications and advisory firm Teneo has examined the role that AI will play in sustainability reporting in the future, and what firms can do to prepare.
It has proposed three important considerations for businesses:
1. AI is already being used
AI is currently being applied in evaluating companies’ sustainability disclosures by investors and related service providers, including ESG raters, proxy advisory firms, and analysts. According to Teneo, as these tools advance in efficiency, ESG ratings may shift towards a more responsive, ‘on demand’ system, providing real-time insights into a company’s ESG risk profile amid global events.
‘Just as investors already use AI to parse the nuances of a company’s quarterly earnings calls, investors are using AI to extract company ESG data, estimate company ESG data that is not disclosed, generate summaries to assess a company’s ESG goals and even identify red flags for greenwashing,’ Teneo said.
Early use cases involve frameworks proposed by institutions like the University of Zurich and the Oxford Sustainable Finance Group, which have proposed a framework to assess the integrity of net zero plans.
Read More: Upstream energy sector turning to AI to assist with decarbonisation: report
2. AI should be considered a ‘key stakeholder’
As AI gains importance in the ESG analysis process for investors and service providers, companies need to reconsider their approach to this technology. As Teneo notes, it’s important for companies to utilise these tools not only as efficiency aids but also as means to comprehend the perspectives of investors.
‘While AI is, and will be an efficiency tool, it can also be fraught with errors, omissions or worse – entirely fabricated content (or “hallucinations” in AI lingo). Knowing what AI is saying about a company’s ESG strategy can inform sustainability reports, proxy statements earnings call transcripts and other communications.’
To enhance AI compatibility, companies should ensure that graphics and charts are machine-readable, facilitating proper ingestion by ESG ratings firms and other data aggregators. Moreover, using succinct language is essential to facilitate easy comprehension by AI and prevent mixed signals that might lead to unfavourable interpretations of a company’s ESG communications.
3. Using AI can be energy-intensive
The adoption of AI comes with significant energy consumption, posing unexpected challenges to a company’s environmental goals. This could necessitate a reevaluation of GHG emissions targets established before AI implementation.
Efficiency gains from AI could also potentially lead to a reduced workforce, raising concerns about algorithmic bias affecting talent management processes, from hiring to promotions. This poses a dilemma for companies emphasising employee well-being, prompting shareholder proposals to align AI use with overall employee welfare.
At the same time, however, as Teneo notes, using AI also ‘creates opportunities’ for businesses. ‘In addition to enterprise models being offered by platforms like OpenAI’s ChatGPT, other third-party systems, as well as in-house models are being developed to synthesise company ESG data in a more efficient way than the traditional database/spreadsheet model of data storage. Boards of directors, who are typically responsible for the oversight of a company’s ESG strategy, may benefit from the use of AI for regular ESG reports.’
Read the full report, Teneo ’23 & ESG Series: AI’s Impact on Sustainability Reports, here.
