AI and ESG: the dynamic duo revolutionising sustainable reporting
The convergence of artificial intelligence (AI) technologies and environmental, social, and governance (ESG) considerations has emerged as a critical area of focus for enterprises in the 21st century.
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AI has the potential to enhance ESG reporting and drive sustainable practices across various industries
As organisations increasingly adopt AI solutions, including Large Language Models (LLMs), generative AI, diffusion models, and multi-modal AI, they must navigate the complex interplay between these technologies and their ESG commitments.
AI is therefore playing an increasingly central role in ESG strategies, offering new opportunities for data collection, analysis, and reporting.
These AI technologies can be a powerful tool to enhance the accuracy and efficiency of ESG data management, enabling entities to better understand and address their environmental and social impacts and performance. As a result, ESG and sustainability-focused AI technology and products have grown in number and complexity in recent years, which is a trend that is expected to continue in 2025.
As ESG and sustainability reporting increasingly becomes mandatory in 2025 and beyond, a growing number of entities, including smaller companies with key roles in corporate supply chains, will likely be drawn to AI tools to accurately and reliably collect data in a structured and efficient way.
However, the use of AI is not without challenges from an ESG perspective. In addition to the significant amount of energy required to power and develop AI systems, ethical and social considerations such as potential algorithmic bias, potential privacy issues, and ensuring that outputs are vetted so they are not misleading or controversial all need to be considered.
New legal regimes such as the EU AI Act, which entered into force on 1 August 2024, introduce additional regulatory requirements in relation to AI programmes, including prohibiting the use of AI in certain contexts. As stakeholder focus and regulatory requirements develop in 2025, companies must ensure responsible AI governance, addressing these challenges while leveraging AI’s potential to drive ESG performance. This includes developing clear policies and frameworks for AI use, as well as engaging with stakeholders to build trust and transparency.
Some important trends impacting the use of AI technology in ESG reporting are emerging and include:
Enhanced data collection and analysis: AI technologies, such as machine learning and natural language processing (NLP), are being increasingly used to automate the extraction and analysis of ESG data from diverse sources. This helps in managing large volumes of unstructured data, such as annual reports, news articles, and regulatory filings.
Improved accuracy and efficiency: AI-driven analytics have significantly improved the accuracy and efficiency of ESG reporting. Companies using AI for ESG data management have reported up to a 40% reduction in data processing time and a 30% increase in report accuracy. These savings are not insignificant given the potential size and demands of data analytics requirements in today’s modern organisations.
Real-time monitoring and updates: AI systems can continuously monitor data sources, ensuring that ESG information remains up-to-date and reflects the latest developments in real-time. This is crucial for maintaining the relevance and accuracy of ESG reports.
Regulatory compliance: With the introduction of new regulations like the EU AI Act and the Corporate Sustainability Reporting Directive (CSRD), companies are leveraging AI to streamline compliance processes. AI helps in standardising and validating data across multiple sources, providing a consistent and transparent view of ESG performance.
Addressing algorithmic bias and privacy concerns: As AI technology advances, there is a growing focus on addressing ethical and social considerations, such as potential algorithmic bias and privacy issues. Companies are developing clear policies and frameworks for AI use to ensure responsible AI governance.
Increased adoption by smaller companies: As ESG reporting becomes mandatory, smaller companies are also turning to AI tools to accurately and reliably collect data in a structured and efficient way. This trend is expected to continue as AI technology becomes more accessible and affordable.
Stakeholder engagement and transparency: Companies are using AI to engage with stakeholders and build trust through transparent reporting practices. Transparent AI practices have been shown to increase stakeholder trust and engagement by up to 20%.
These trends highlight the transformative potential of AI in enhancing ESG reporting and driving sustainable practices across various industries.
As we move through 2025, the ESG landscape is characterised by both challenges and opportunities. Companies must remain vigilant and adaptable, embracing integrated and strategic approaches to ESG and sustainability (including in relation to the terminology used) to ensure business resilience.
By staying informed and proactive, organisations can navigate the complexities of ESG and sustainability matters and position themselves for long-term success in an ever-evolving global environment.
The future of AI in ESG is promising, but it requires a balanced approach to fully harness its potential while mitigating associated risks and challenges.
About the author:
John Martin is the founder and CEO of Plutus Consulting Group.
John, with over 30 years’ global specialist banking and financial services experience, has a track record of strategic, technological, and operational leadership of large and small-scale corporate M&A, ESG, and business transformation programmes. All opinions are his own – feel free to debate and comment below!
Connect on LinkedIn: John Martin