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Traditional carbon estimation models are missing the mark on Scope 3 emissions by up to 2,480%, according to new analysis by climate intelligence firm Carbon Responsible. The study compared widely aused Environmentally Extended Input Output (EEIO) estimates to Ada, an AI-powered emissions engine, benchmarking against verified 2023 emissions data across a sample of FTSE 100 companies.
While traditional EEIO methods showed divergences as high as 2,480% from verified data, Ada's technology reduced measurement inaccuracy to just 80% – making it 30 times more accurate, or a 97% improvement in precision.
"This represents a step-change in emissions measurement capability," said Matthew Paver, COO of Carbon Responsible. "When you're 97% more accurate than the industry standard, you're no longer in the realm of estimation – you're capturing investment-grade data."
The findings come as regulators worldwide tighten requirements for emissions reporting. Both the EU's Corporate Sustainability Reporting Directive (CSRD) and the US SEC climate rule now mandate traceable, up-to-date, and auditable emissions data – placing firms using outdated measurement methods at growing financial, regulatory, and reputational risk.
Scope 3 emissions – which include supply chain, investment, and product-use emissions – can account for more than 80% of a firm's carbon footprint yet have remained notoriously difficult to measure. EEIO, the globally accepted methodology for estimating carbon emissions using spend-based data, is endorsed by global frameworks including the GHG Protocol and the Partnership for Carbon Accounting Financials (PCAF).
“We’re seeing emissions disclosures based on proxies from six years ago – and regulators are starting to notice,” said Matthew Paver, COO of Carbon Responsible. “What’s being accepted in ESG reports today would never pass audit in a financial statement. Procurement, risk modelling, capital allocation – all now demand a firmer grasp of emissions data. Even if it feels like attention is shifting away right now, the CFO’s office can no longer afford to treat carbon as a compliance footnote.”
“There’s a widespread misconception that Scope 3 data is just a best guess, but if you’re setting net zero targets, allocating capital, or filing regulatory disclosures, guesswork isn’t good enough.”
Carbon Responsible this month launched its AI-powered carbon emissions measurement platform, Ada, to address the crisis of credibility in Scope 3 reporting. Built for investment-grade analysis, Ada delivers 90% accuracy across portfolios and supply chains, drawing on a proprietary dataset of more than 14,000 verified company records. The platform leverages machine learning to produce real-time, auditable insights – with no emissions data older than two years.
Carbon Responsible is already working with asset managers, private equity firms, and global corporates that are preparing for their first CSRD-aligned reports or submitting climate targets for SBTi validation. Many are seeking to replace “black box” ESG datasets with transparent and defensible carbon estimates.
From volume to verifiability
Carbon Responsible is the latest voice calling for a shift in ESG data standards – from volume to verifiability. The firm argues that while some providers boast carbon datasets covering hundreds of thousands of entities, those databases are often populated with coarse estimates that obscure rather than clarify climate risk.
“You wouldn’t invest based on a credit rating built from an industry average in 2017,” said Matthew Paver. “So why are firms making climate decisions based on the same approach?”
The Ada platform is built around the concept of evidence-based emissions reporting – using primary data where available and rigorous proxy logic where it’s not. Every data point comes with audit trails, source tagging, and methodological transparency.
In doing so, the platform aims to solve what Carbon Responsible calls the “missing middle” of carbon data: mid-tier suppliers, unlisted investments, and complex value chains where emissions are material but poorly understood.
“What we’re witnessing is the end of ESG’s ‘honour system’,” said Paver. "When your AI solution is 30 times more accurate than traditional methods, it transforms not just reporting, but the entire approach to climate risk management and decarbonization strategy."
