From reporting to reality: How CSRD 2.0 elevates the role of data and AI in ESG

The Corporate Sustainability Reporting Directive (CSRD) 2.0 and the amended European Sustainability Reporting Standards (ESRS) represent a decisive turning point: sustainability reporting must now be supported by the same discipline and auditability that is expected in financial reporting. While the reform reduces the volume of mandatory disclosures, it significantly raises expectations for how information is sourced, validated, and governed.

The evolution of the CSRD and ESRS signals a broader shift: sustainability reporting is no longer about ticking boxes but about building a system of record that captures how a business interacts with its environment and stakeholders. Firms that treat ESG data with the same rigor as financial data will move beyond compliance toward real-time insight - the ability to measure impact, forecast trends, and respond to investor questions with confidence.

The CSRD was designed to bring consistency and credibility to Environmental, Social, and Governance (ESG) disclosures across Europe. Its 2025 update, together with the amended ESRS, refines that ambition. The revisions reduce the number of mandatory data points but raise expectations for how every figure is sourced, validated, and reconciled with financial reporting. In practice, this means organizations will no longer be assessed on the length of their reports but on the reliability of their underlying data. The amendments promote a materiality-first mindset, align ESG and financial information under shared definitions, and reinforce the shift to a digital, machine-readable format (XBRL). Auditors will not only review what is reported but also trace how the data is consolidated.

Gaining a clear view of the data value chain - from source to report - can be complex, but documenting this flow has become fundamental to the integrity of sustainability reporting. Many organizations are responding by conducting double materiality assessments, carrying out gap analyses and scoping exercises, and mapping existing disclosures against ESRS requirements to establish a reliable baseline. Digital comparison tools are increasingly used to identify alignment gaps, prioritize remediation activities, and define realistic implementation timelines. These practices are emerging as core elements of a robust CSRD preparation process, helping organizations to strengthen their reporting foundations with greater confidence and efficiency.

For years, many sustainability teams operated in spreadsheet silos, reconciling dozens of KPIs manually at year-end. Under CSRD 2.0, that approach will no longer suffice. ESG data must now live inside the same governed environment as finance, risk, and operational data - with clear ownership, version control, and audit trails. This transition is not merely technical; it reshapes the culture of reporting. Rather than collecting indicators for disclosure, organizations must manage data as a strategic asset - one that equally supports regulatory assurance, investor confidence, and internal decision-making. The message is simple: less paperwork, more pipeline. Data lineage, metadata, and validation rules become as important as the emission numbers themselves, ensuring every statement can be traced and justified.

To support this shift, the KPMG Powered Sustainability approach provides a structured way for organizations to assess the readiness and quality of their ESG data, trace its lineage across systems, and design the metadata and orchestration frameworks required for effective governance. Within this model, sustainability metrics are integrated into existing enterprise platforms, such as Microsoft Fabric or Power BI, enabling ESG information to sit within the organization's broader reporting and analytics ecosystem rather than in isolated workflows. Powered Sustainability also provides a reference governance model that helps leadership teams clarify roles and responsibilities across sustainability domains and establish reporting frameworks aligned with EFRAG and CSRD requirements. By adopting these components, organizations can embed governance and accountability from the outset and build a reporting process that is scalable, consistent, and assurance-ready.

When this governance model is in place, assurance becomes far easier and the organization gains something more valuable than compliance: control. Companies that invest early in these foundations will find their ESG information can be reused seamlessly across investor reporting, regulatory submissions, and internal dashboards - without duplication, manual intervention, or uncertainty.

A stronger data backbone also enables the responsible and scalable adoption of artificial intelligence, but only for organizations that act now. AI is rapidly moving from experimentation to expectation, and sustainability reporting will be no exception. Recent KPMG research shows that nearly 97% of business leaders view AI as a net positive for achieving net-zero goals - yet fewer than one-in-three are prioritizing its energy efficiency. At the same time, AI’s share of data-center energy consumption is expected to rise from 8% today to 36% within three years, underscoring why responsible, well-governed data foundations are becoming essential for any credible use of automation.

Tools that can map ESRS datapoints to enterprise systems, flag anomalies before assurance, and even draft narrative sections of sustainability statements are already reshaping how ESG information is managed. Machine-learning models can identify outliers in energy or emissions data; generative models can pre-populate disclosures based on verified figures, freeing experts to focus on analysis and insight. Yet automation is no substitute for accountability. AI outputs are only as trustworthy as the data and controls beneath them, and organizations that delay building these foundations risk being left behind as reporting and assurance processes become increasingly data driven.

Translating CSRD requirements into operational capability increasingly relies on specialized tooling and structured methods. In practice, many organizations draw on the approaches embedded in KPMG’s sustainability and data frameworks, which include the use of climate-metrics extractors capable of scanning sustainability reports, identifying key figures and feeding them directly into ESG dashboards to reduce manual effort and improve accuracy. These frameworks also provide guidance on defining sector-relevant ESG KPIs and designing automated data pipelines that collect, validate, and publish these metrics on a recurring cycle. Capabilities of this kind help establish a more reliable reporting rhythm, improve consistency across business units and create a repeatable process that scales as CSRD expectations evolve.

By combining governance, data quality, and human oversight in a human-in-the-loop model, we ensure that AI remains explainable, auditable, and anchored in verified data, enabling organizations to embrace automation without compromising trust.

At KPMG, we help organizations make CSRD 2.0 workable in practice by:

• Running double materiality sessions with sustainability and finance teams to agree on which ESG topics genuinely matter for the business.
• Translating ESRS requirements into a focused set of sector-relevant KPIs and setting up automated data flows (e.g. in Microsoft Fabric or Power BI) so these metrics are regularly collected and checked.
• Clarifying who owns which ESG figures and capturing those responsibilities in clear, practical, RACI overviews that fit your existing organization.
• Using AI-supported tools in a controlled way to benchmark disclosures against peers, flag data issues early, and free up experts to focus on analysis rather than data chasing.

CSRD 2.0 rewards those who control their data, not just those who report it. By combining regulatory insight with deep expertise in data, technology, and assurance, KPMG professionals help organizations turn sustainability reporting into a competitive advantage, creating the trusted data foundations that make AI not only possible, but reliable.

If you want to understand how we can help you with this challenge, from ESG data governance and digital reporting to AI-enabled analytics, contact us through our services presented below.

Together, we can turn compliance into control, and data into lasting impact.

Authors: Jasper Demuynck, Junior Advisor & Marie Casier, Senior Advisor & Rani Torrekens, Manager Advisor & Mélissa Mariën, Senior Manager