MartinAI
August 17, 2026·10 min read

Preparing utility data for an ESG audit

Assurance turns your energy and emissions numbers into claims an auditor can test. Here is how to make utility data assurance ready before the audit starts.

Sustainability reporting used to be a communications exercise. It is now an audited one. As disclosure rules take effect across major markets, the energy and emissions numbers a company publishes are increasingly subject to third-party assurance, which means an auditor will test them the way a financial auditor tests a balance sheet. The IFAC State of Play study found that 75 percent of the world's largest companies obtained assurance on their sustainability disclosures in 2024, up from 73 percent the prior year, a share that has climbed from about 51 percent five years earlier.

Most companies are not ready for that scrutiny. A KPMG survey found that only 29 percent of companies felt they had the policies, skills, and systems in place to be ready for independent assurance of their ESG data. The gap is almost always the data, and utility data sits at the center of it. This article covers what an ESG auditor actually checks and how to make your utility and energy data assurance ready before the audit begins.

What ESG assurance actually tests

Assurance comes in two grades. Limited assurance, the most common today, has the auditor perform enough work to state that nothing came to their attention suggesting the numbers are materially misstated. Reasonable assurance, the higher bar that regulators are moving toward, requires positive evidence that the numbers are right, closer to a financial audit. Either way, the auditor is testing the same thing: can each reported number be traced to source evidence, and was it calculated consistently and completely.

For energy and emissions, that evidence chain runs from the disclosed figure back through the calculation to the underlying activity data, which for most organizations is utility bills and meter reads. Under IFRS S2, the global baseline standard, companies must disclose Scope 1, 2, and 3 emissions measured in accordance with the GHG Protocol, and the GHG Protocol resolves every emissions figure to activity data multiplied by an emission factor. Weak activity data is a weak audit, no matter how good the model on top of it.

Why the data is usually the problem

Auditors and preparers agree on where the pain is. In Deloitte's Sustainability Action Report, 57 percent of executives named data quality and availability their single biggest ESG data challenge and 88 percent ranked it among their top three, while 81 percent flagged documentation and sign-off as a top-three challenge. Documentation is the auditability problem in one word: even a correct number fails assurance if you cannot show where it came from.

Utility data is prone to exactly the failures an auditor looks for. Bills arrive in dozens of formats and get keyed by hand. Estimated meter reads get treated as actuals. Units get mixed. Gaps in coverage get zeroed rather than flagged. Emission factors get applied for the wrong year or the wrong jurisdiction. None of these are exotic. They are the everyday state of a spreadsheet-based process, and each one is a finding waiting to happen.

The auditability test

For every energy and emissions number you disclose, ask one question: can you hand the auditor the source bill or meter read behind it, show the units and period, and reproduce the calculation? If any link in that chain lives only in someone's memory or a manual spreadsheet, it is a finding waiting to happen.

The regulatory picture, briefly

You do not need to track every rule to prepare well, but the direction of travel matters. In the European Union, the Corporate Sustainability Reporting Directive requires in-scope companies to obtain limited assurance on their sustainability reporting, with a planned move toward reasonable assurance over time. In California, SB 253 requires large companies doing business in the state to report Scope 1, 2, and 3 emissions, and SB 261 requires disclosure of climate-related financial risk. In Canada, the Canadian Sustainability Standards Board issued CSDS 1 and CSDS 2 in December 2024, aligned with the ISSB standards, currently on a voluntary basis.

One caution: at the United States federal level, the Securities and Exchange Commission climate-disclosure rule is not in force. It was stayed in 2024 and the Commission has since proposed to rescind it. The practical takeaway is that whether or not your specific rule is mandatory today, the assurance-ready standard for data is now set by the frameworks that are, and building to that standard is the safe move.

How to make utility data assurance ready

The GHG Protocol reporting principles, relevance, completeness, consistency, transparency, and accuracy, translate directly into a checklist for the data layer under your disclosure.

  • Completeness: every meter and account in scope is captured, and any gap is flagged, not silently zeroed
  • Traceability: every disclosed figure links back to the specific bill or meter read behind it, so an auditor can follow the number to its source
  • Consistency: usage is normalized to consistent units and billing periods, so comparisons across sites and years hold
  • Correct factors: emission factors are matched to the right jurisdiction and reporting year
  • Accuracy: bills are validated against expected ranges and prior periods to catch estimates, misreads, and keying errors before they enter the inventory
75%
of the largest companies got assurance on 2024 disclosures
29%
of companies feel ready for ESG assurance
57%
name data quality their top ESG data challenge
81%
flag documentation and sign-off a top-three challenge

How MartinAI helps you pass

MartinAI reads utility bills across every commodity and provider format, extracts the usage, period, meter, and account details that emissions accounting depends on, and validates each figure against expected ranges before it enters your inventory. Because every number stays linked to the document it came from, the evidence chain an auditor asks for is already assembled.

That turns assurance from a scramble into a review. Instead of reconstructing where a number came from under deadline, your team hands the auditor structured activity data with source bills attached, consistent units, flagged gaps, and factors matched to jurisdiction and year. MartinAI does not sell you a single tidy figure. It gives you the traceable, validated foundation that assurance is designed to test.

Frequently asked questions

What does an ESG auditor check in energy data?

An auditor tests whether each disclosed energy and emissions figure can be traced to source evidence, usually utility bills and meter reads, and whether it was calculated consistently and completely. Under IFRS S2, emissions must follow the GHG Protocol, which resolves every figure to activity data multiplied by an emission factor, so the activity data has to hold up.

What is the difference between limited and reasonable assurance?

Under limited assurance, the auditor does enough work to state that nothing came to their attention suggesting the numbers are materially misstated. Reasonable assurance requires positive evidence that the numbers are right, a higher bar closer to a financial audit. Regulations such as the EU CSRD start at limited assurance and move toward reasonable over time.

Why do companies fail ESG data audits?

Almost always because of the data, not the model. Surveys put data quality and documentation at the top of the challenge list. Common failures include estimated meter reads treated as actuals, mixed units, gaps that were zeroed instead of flagged, wrong-year or wrong-jurisdiction emission factors, and numbers that cannot be traced to a source document.

Is the SEC climate disclosure rule in effect?

No. The US Securities and Exchange Commission climate-disclosure rule was stayed in 2024 and the Commission has since proposed to rescind it, so it is not currently in force. Other frameworks, including IFRS S2, the EU CSRD, and California SB 253 and SB 261, continue to drive assurance-ready data expectations.