AI Seen as Key to ESG Success, but Most Companies Have Yet to Put It to Work

Artificial intelligence is increasingly viewed as an essential tool for meeting growing environmental, social and governance (ESG) obligations, yet most organisations remain in the early stages of adoption, highlighting a significant gap between ambition and execution.

According to a new study published by KPMG, 82% of companies believe artificial intelligence will play a major role in helping them manage ESG requirements. However, only around one in four organisations currently use AI in their sustainability operations, while adoption is even lower in governance, risk and compliance (GRC), where just one in eight companies have integrated the technology into day-to-day processes.

The findings illustrate a broader challenge facing businesses as regulatory scrutiny intensifies and investors increasingly demand accurate, transparent and timely sustainability reporting.

Pressure from investors

For institutional investors, ESG data has become an increasingly important component of investment analysis. Asset managers are relying more heavily on corporate disclosures to assess climate risks, supply chain resilience and governance standards, while regulators continue to tighten reporting requirements across multiple jurisdictions.

Artificial intelligence offers the potential to automate data collection, identify reporting inconsistencies and improve the quality of ESG disclosures. Yet despite growing enthusiasm, many organisations remain hesitant to deploy AI at scale because of concerns surrounding data quality, governance and regulatory compliance. The KPMG survey suggests that while executives recognise AI’s strategic importance, implementation continues to lag behind expectations.

From compliance to competitive advantage

The slow pace of adoption may prove costly. As ESG reporting evolves from a compliance exercise into a strategic business function, companies that can generate reliable, real-time sustainability data may gain an advantage with investors, lenders and insurers.

Modern AI systems can rapidly process large volumes of environmental, operational and supply chain information, reducing manual reporting while improving consistency. The technology also has the potential to identify emerging climate risks, monitor supplier compliance and support more sophisticated scenario analysis.

However, these benefits depend on strong governance frameworks. AI-generated outputs remain only as reliable as the data used to train and operate them, raising concerns about transparency, bias and auditability.

Balancing opportunity with risk

The findings come as businesses worldwide are shifting from experimental AI projects towards practical deployment focused on measurable business outcomes. KPMG’s latest Global AI Pulse report found organisations are increasingly prioritising accountability and demonstrable returns on AI investment over experimentation alone, reflecting a maturing market.

That trend is particularly relevant for ESG, where inaccurate reporting can expose companies to allegations of greenwashing, regulatory sanctions and reputational damage. Rather than replacing sustainability professionals, AI is increasingly expected to augment decision-making by analysing complex datasets that would otherwise require significant manual effort.

Looking ahead

For investors, the report raises an important question: which companies will successfully integrate AI into their sustainability strategies, and which risk falling behind? As ESG disclosures become more data-intensive and regulatory expectations continue to evolve, AI is likely to become less of an optional innovation and more of an operational necessity.

The companies that combine robust governance with intelligent automation may ultimately be best positioned to deliver the transparency that both regulators and investors increasingly expect.