Navigating carbon accounting complexity through collaboration

Isobel Gibson explains the importance of cross-functional collaboration for effective emissions reporting.

Carbon accounting has moved from the margins of sustainability reporting to the centre of regulatory scrutiny. With the arrival of Corporate Sustainability Reporting Standards (CSRD), International Sustainability Standards Board (ISSB) standards, Sustainability Disclosure Requirements (SDR) and the US Securities and Exchange Commission (SEC) climate related disclosure rules, firms are now expected to treat carbon data with the same importance as financial data. This shift has implications for compliance teams, who increasingly find themselves with a shared responsibility for ensuring that disclosures are accurate, complete, and defensible.

Despite this, many organisations still treat carbon accounting as a technical exercise owned solely by finance or sustainability teams. That model is no longer fit for purpose as carbon accounting evolves to be complex, multi sourced and often uncertain, particularly when it comes to Scope 3 emissions (those which indirectly occur through a firm’s operations). It is important to note that carbon accounting cannot simply be bolted onto existing reporting processes or blindly delegated to a single team. Without strong governance, controls, and cross functional collaboration, firms risk misreporting, misalignment, regulatory challenge, and even reputational damage.

Finance and compliance teams can play a critical role in carbon accounting, but they often lack the operational visibility needed to understand supply chain emissions, the specialist ESG knowledge required to interpret methodologies, or the governance frameworks needed to manage cross departmental data flows. This presents a risk to firms, as carbon disclosures are increasingly treated by consumers and other stakeholders like financial statements, in that there is an expectation that such data should be subject to assurance, audit, and regulatory enforcement.

Increased stakeholder scrutiny means that misreporting under either voluntary or mandatory disclosure platforms is not just a theoretical concern. It also highlights why compliance teams must be deeply involved in the process; their expertise in governance, controls, and assurance is essential to making carbon accounting reliable and defensible, in tandem with the specialist knowledge that ESG teams hold. With that in mind, this article presents a call to build a collaborative, cross functional model in which ESG, Compliance, and Finance work together on carbon accounting practices from the outset.

Firms are now expected to treat carbon data with the same importance as financial data.

Understanding the carbon accounting landscape

Carbon accounting is built around three categories of emissions. Scope 1 covers direct emissions from owned or controlled sources (for example, company facilities or vehicles). Scope 2 captures indirect emissions from purchased electricity, heat or steam. Scope 3 includes all other indirect emissions across the value chain, from purchased goods and services to business travel, waste, investments, and digital emissions.

For many firms, Scope 3 represents most of their carbon footprint. It is also the most difficult to measure because it relies on data from suppliers, customers, and third-party service providers. This is where collaboration between teams becomes essential to join the dots between specialist ESG knowledge on carbon accounting methodologies and standards, data sources, and implications to the budget sheet across firms of all sizes.

Moreover, there has been a shift across sectors by stakeholders towards an increased focus on emissions accountancy and disclosure. Carbon accounting of Scope 3 emissions in particular has previously been driven by organisations looking to stand out with strong corporate responsibility goals. However, an increased expectation is emerging for firms of all sizes to disclose greenhouse gas emissions across Scopes 1, 2 and 3 categories, explain their methodologies, describe governance arrangements, and, in many cases, obtain assurance over the data. These expectations elevate carbon accounting from a sustainability exercise to a more regulated and scrutinised activity that is pertinent to all teams.

For example, compliance teams often bring the required controls and documentation disciplines needed to meet these expectations, ESG teams bring the subject matter expertise, and finance brings the bolstered reporting infrastructure. When we consider Scope 3 emissions specifically, procurement functions are also likely to play a significant role. None of these functions can succeed alone.

The scale of the Scope 3 challenge

Scope 3 emissions are challenging because the data is fragmented, inconsistent and often incomplete. Suppliers may use different methodologies or sources when deciding on emission factors for specific resources or activities, and some may not report emissions at all. Where data is missing, firms must rely on estimates, proxies or industry averages, each of which requires careful documentation and justification.

The rise of digital emissions adds another layer of complexity. As firms increasingly rely on cloud computing and AI models, accounting for emissions from data centres they do not own or control is a real challenge. Estimating these emissions can require understanding the data centre’s location, energy mix, cooling systems, and the energy intensity of the AI model itself. This is a new frontier for many organisations, and one that demands a structured, cross functional approach.

Considering this, a successful carbon accounting framework depends on strong collaboration between compliance and ESG teams which brings together the ESG team’s aforementioned understanding of carbon methodologies, emission factors and supplier engagement, and the compliance team’s understanding of regulatory expectations, controls, documentation and assurance.

To work effectively together, teams need a joint operating model that clearly defines roles and responsibilities, establishes shared governance structures and embeds knowledge sharing mechanisms. Carbon data risks should be integrated into the enterprise risk framework, and both teams should use a common language to avoid misunderstandings. Without this foundation, even the best carbon accounting tools will fail.

Practical steps for creating a robust carbon disclosure framework

A defensible carbon accounting framework requires a structured approach. Firms can begin by focusing on the following practical steps.

• Map carbon data sources across procurement, travel, HR, cloud services, AI platforms and investment portfolios.
• Establish data lineage and documentation standards so that methodologies, assumptions and calculations are transparent and auditable.
• Design controls that validate data, manage exceptions, ensure approvals and maintain version control.
• Set up escalation routes for anomalies or inconsistencies in the data.
• Strengthen oversight of third party data providers, ensuring transparency, due diligence, and ongoing monitoring.
• Build a defensible audit trail that captures assumptions, evidence, meeting minutes and supplier correspondence. 

These steps help ensure that carbon data is accurate, consistent and ready for regulatory scrutiny. They also serve as a reminder that while firms may not get it 100% right the first time, documenting the approach and reasonable steps that have been taken to gain assurance on information accuracy provides a solid baseline for improvements in future disclosures.

Scope 3 and AI related emissions

AI related emissions are becoming a significant component of Scope 3 for many firms. This is only projected to increase, with the International Energy Agency forecasting that electricity demand from AI-optimised data centres will more than quadruple by 2030. As organisations adopt AI for customer service, risk modelling, compliance automation, and analytics, they should account for the emissions generated by these tools if they form a material part of operations. As a general rule, this means including AI and cloud service emissions in Scope 3 accountancy if they are core to operations, digital infrastructure costs are material, AI contributes to revenue, risk, or automation at scale, or key stakeholders such as investors, regulators, or customers are specifically requesting them. By contrast, these emissions could be reasonably de-prioritised if usage is immaterial, data is unavailable, and spend is negligible, or if cloud-use is incidental.

This approach provides some proportionality in consideration of the challenge that AI emissions are not directly visible and are complex to determine. For example, they depend on the data centre’s location, energy mix, cooling systems, the model’s computational intensity, and the number of hours of use. As practical guidance, acceptable approaches to AI emission accountancy for most firms could include the use of supplier provided emissions data, spend based emission factors (where supplier data is unavailable), or average cloud region intensity multiplied by usage volumes.

Estimating these emissions will likely require collaboration between teams including IT departments, cloud service providers, and AI vendors. Here, compliance plays a critical role in ensuring that assumptions are documented, methodologies are consistent, and uncertainties are disclosed transparently. Therefore, teams should be making sure that this is on their radar, especially as AI impact is a rapidly evolving area, and regulators will expect firms to demonstrate that they have taken reasonable steps to estimate emissions accurately.

This being said, AI is not only a source of emissions but also a powerful tool for improving carbon reporting. AI can automate data collection, identify anomalies, estimate missing data, and support scenario analysis where applicable. However, AI enabled reporting introduces risks. Models may use opaque methodologies, apply incorrect assumptions, or rely on generic emission factors that do not reflect the firm’s operations. As with the application of AI in other processes, human oversight will be a key requirement of this process to avoid the risk of errors which can stem from an over reliance on automation.

Here, compliance teams will be required to provide oversight, challenge, and governance in a way that is applied to other regulated disclosures, making sure AI enhances carbon reporting without undermining accuracy, transparency, or accountability.

As organisations adopt AI for customer service, risk modelling, compliance automation, and analytics, they should account for the emissions generated by these tools if they form a material part of operations.

Mapping the journey to robust carbon accounting

A maturity model can help firms take a pragmatic view of where they currently sit in their carbon accounting journey and where targeted improvements could add the most value. Rather than aspiring to an abstract ‘best practice’ state, firms should assess their position against business complexity, regulatory exposure, and stakeholder expectations. This includes considering the sustainability reporting regulations they fall under (or are likely to in the near future), as well as benchmarking against peers to understand emerging norms and external expectations from investors, clients, and regulators. Stages in that journey may be characterised as:

• Basic: Manual spreadsheets, limited documentation, ESG only ownership and minimal controls. Carbon accounting is largely ad hoc and focused on high‑level disclosures, with limited oversight or consistency between reporting periods.
• Developing: Defined roles, basic controls, partial documentation and some cross functional collaboration. Firms begin to formalise processes, introduce governance, and align more closely with recognised frameworks, though data quality and coverage may still be inconsistent.
• Advanced: Integrated compliance-ESG operating model, strong controls, AI enabled reporting and supplier engagement programmes. Carbon accounting is embedded into broader risk and reporting processes, with clearer accountability, improved data reliability, and enhanced analytical capability.
• Leading: Real time carbon data, full assurance readiness, advanced digital emissions tracking and an embedded culture of carbon accountability. Carbon data is decision‑useful, audit‑ready, and actively used to inform strategy, procurement, and operational decisions.

Most firms today sit between ‘Developing’ and ‘Advanced’, with significant room for growth. For many, the opportunity lies in identifying specific capability gaps such as controls, documentation, supplier data, or assurance readiness, as well as understanding impact materiality, rather undertaking a full process transformation. Here, making incremental enhancements can result in significant process improvements, regulatory confidence, and increased stakeholder trust.

A core component of corporate governance

Carbon accounting cannot just be considered as a sustainability side project or a technical reporting exercise. It is a core component of corporate governance, and one that is data heavy, operationally complex, and increasingly subject to regulatory enforcement. Treating it as the responsibility of a single team – whether ESG, finance, or compliance – is a structural weakness. Finance cannot ‘just add carbon to the balance sheet’, ESG cannot undertake data collection alone, and compliance cannot govern what it does not understand.

The future of carbon reporting depends on integration into firms at a cross-function level. Broadly speaking, ESG teams bring the scientific and methodological expertise, compliance teams bring controls and an assurance mindset, and finance teams bring reporting discipline and audit infrastructure. Each function therefore holds a piece of the puzzle. 

Firms that build cross functional operating models in which teams work together from the outset will be best placed to produce accurate, efficient, and defensible disclosures. They will also be better prepared for assurance, more resilient to regulatory scrutiny, and more credible in the eyes of investors and customers.