AI has recently marked its first anniversary, witnessing a remarkable surge in adoption across diverse industries, sectors, and niches. Notably, the ESG sector has not remained untouched, experiencing a notable transformation with the integration of AI tools.
On one hand, concerns have surfaced regarding the ethical implications of AI implementation. Issues like algorithm bias, job displacement, and data privacy are on the forefront of discussions. Moreover, the environmental impact of large-scale AI models cannot be disregarded due to CO2 emission of data centre.
On the other hand, AI resents a promising avenue for significantly improving the ESG scoring system and material information reporting for companies, especially given the introduction of IFRS S2 and the anticipated enforcement of IFRS S1 from 2025.
To briefly recap, IFRS S1 and IFRS S2 are regulatory frameworks aimed at governing the disclosure of sustainability-related financial information. Effective January 1st 2024, IFRS S2 mandates climate-related risk and opportunity disclosure, aiming to enhance the materiality of ESG reporting. Starting January 1st 2025, IFRS S1 will broaden the scope, requiring disclosure of general sustainability-related risks and opportunities. Both policies aim to aid investors in better evaluating a company’s sustainability position and understanding the impact on financial aspects.1
Aligned with these regulatory shifts, several actors find the current ESG scoring system inadequate. The World Economic Forum highlights AI as an essential tool to track and leverage relevant data, enhancing the reliability of ESG reporting2. AI emerges as a potential solution to bridge existing gaps in ESG reporting, presenting an opportunity for substantial improvement.
Several AI-powered tools have emerged for each ESG category3:
- In environmental management, tools like DeepMind aid in climate change modeling, real-time deforestation monitoring, and energy management for buildings and industries.
- Addressing social responsibility, AI combats discrimination by analyzing hiring and promotion data, with companies like Unilever developing tools for objective candidate screening.
- In governance, AI holds potential for automatically detecting regulatory breaches and enhancing public sector efficiency, such as Ayasdi’s goal to assist banks in detecting suspicious activities and reducing Anti-Money Laundering (AML) risks.
PwC’s recent report reinforces the profound impact of ESG data availability on essential company facets. A study within the automotive sector underscores a compelling correlation: increased material and available ESG data correlate with improved operational results, indicating tangible performance enhancements.4
In this context, the growing significance of Artificial Intelligence (AI) becomes evident. AI tools offer a transformative solution to enhance the quality and quantity of reported ESG data.
Better quality ESG data means easier way assessing the ESG impact on the company, the ESG score. With better readability on the ESG reporting, one could expect a better ESG score evaluation and therefore better assessment of the company valuation. EY mentioned that ESG disclosure improve pre-IPO performances and that good ESG Scores positively correlate to better financial performance.5
Amid the era of sustainability reporting, integrating AI into ESG processes is not just a necessity but a strategic move towards value creation. The logical evolution is clear – increased AI usage in reporting ESG data translates into improved communication, more comprehensive reporting, and ultimately, heightened company valuation. AI’s ability to analyze vast datasets, monitor real-time developments, and streamline reporting processes positions it as a catalyst for enhancing overall ESG performance, creating tangible and measurable value.
Written by François Mathieu, Associate
References:
1: IFRS, (2024). IFRS S1 General Requirements for Disclosure of Sustainability-related Financial Information. Retrieved from: https://www.ifrs.org/issued-standards/ifrs-sustainability-standards-navigator/ifrs-s1-general-requirements.html/content/dam/ifrs/publications/html-standards-issb/english/2023/issued/issbs1/#about
2: World Economic Forum, ( 2023). Without AI, we won’t meet ESG goals and address climate change. Retrieved from:
https://www.weforum.org/agenda/2023/01/ai-can-help-meet-esg-goals-and-climate-change/
3: Forbes,(2023). How AI can promote ESG. Retrieved from: https://www.forbes.com/sites/forbestechcouncil/2023/04/28/how-ai-can-promote-esg/?sh=41273f874716
4: PWC (2023). ESG Impact company Valuation. Retrieved from: https://www.pwc.com/gx/en/services/audit-assurance/corporate-reporting/esg-reporting/esg-impact-company-valuation.html
5: EY (2021). How ESG disclosure impact IPO valuation. Retrieved from: How ESG disclosures impact IPO valuation | EY – Global
