Scope 3 emissions from purchased goods account for 60–80% of corporate carbon footprints; Watershed’s new AI tool promises faster, more accurate measurement.
The system enables procurement teams to model supplier choices, bridging a long-standing data gap in sustainable sourcing.
Early enterprise users across manufacturing, automotive, and life sciences report improved emissions accounting and supplier engagement.
Technology Enters Procurement’s Carbon Blind Spot
Watershed has introduced a new AI-powered tool aimed at one of the most persistent challenges in corporate climate strategies: measuring and reducing Scope 3 emissions embedded in purchased goods and services.
The platform, called Product Footprints, breaks down each item a company buys into its component materials and production processes. By doing so, it replaces broad, spend-based estimates with detailed analysis that reflects actual procurement decisions. For businesses whose upstream supply chains account for the majority of their carbon impact, the technology is designed to close a critical gap in accuracy, speed, and decision-making.
Closing the Measurement Gap
Traditional life-cycle assessments (LCAs) can take up to a year and rely on suppliers to provide vast datasets, a process many companies find unworkable. Watershed says its AI system can generate detailed emissions profiles for purchased goods in minutes.
The tool not only accelerates the measurement process but also increases precision by mapping sub-materials, processes, and regional emissions factors. Companies can refine these outputs with primary supplier data and run procurement scenarios—enabling them to quantify the climate impact of different purchasing choices before contracts are signed.
“Procurement decisions have been made on incomplete or inaccurate emissions data because existing methods don’t scale,” said Christian Anderson, co-founder of Watershed. “By encoding climate intelligence into AI, we’re giving companies the ability to make informed, actionable choices.”
Built for Transparency
Watershed positions Product Footprints as part of a broader suite of sustainability AI tools, developed by its 21-person team of climate scientists and AI researchers. The system includes three processing layers:
Material enrichment, which adds context to company-provided data.
Supply chain intelligence, which models procurement processes.
Sustainability intelligence, which links materials and processes to region- and supplier-specific emissions factors.
Each calculation comes with a confidence score and documentation of data sources—an attempt to address transparency concerns that have slowed adoption of AI in corporate reporting.
RELATED ARTICLE: Watershed Launches New Software to Streamline Corporate Climate Reporting
Early Industry Tests
More than 20 large enterprises across manufacturing, automotive, chemicals, and life sciences have piloted the tool.
An automaker purchasing low-carbon steel saw the emissions benefit recognized for the first time, correcting the blind spots of traditional methods.
A global life sciences company, with over 50,000 suppliers, consolidated data from more than 70 internal databases. The exercise helped it prioritize supplier engagement and accelerate a program that had been bogged down by manual processes.
“Watershed Product Footprints is helping us uncover the nuances across our supplier base in ways we simply couldn’t before,” said Natalie Watson, Group Director of Sustainability at The Vita Group, a UK-based flexible foam manufacturer. “The speed and clarity of insight are game-changing. Where we once focused on a handful of suppliers, we can now spot patterns and opportunities across thousands.”
Implications for C-Suite and Investors
For executives, the development comes as regulators tighten reporting obligations on supply chain emissions. The EU’s Corporate Sustainability Reporting Directive (CSRD) and the U.S. Securities and Exchange Commission’s climate disclosure rule both increase the pressure to present verifiable Scope 3 data. Investors are likewise scrutinizing portfolio companies’ supply chain resilience and climate exposure.
By shortening measurement timelines and enhancing data granularity, Watershed’s tool could accelerate both compliance and operational decarbonization strategies. Procurement teams can now model supplier choices not only on cost and reliability but also on carbon impact—a shift with direct implications for risk management and brand value.
Global Stakes
The launch reflects a wider trend in sustainability software, where AI is being tailored to address specific corporate bottlenecks. While questions remain about scalability and supplier participation, early results suggest that purpose-built AI could reshape how companies approach climate risk in their value chains.
For companies facing scrutiny over Scope 3 emissions—often the largest and most opaque portion of their footprint—the arrival of tools that make emissions visible, auditable, and actionable may prove decisive.
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