Artificial Intelligence (AI)-Driven Supplier Emissions Benchmark Market Report 2025

The artificial intelligence (AI)-driven supplier emissions benchmark market size has grown exponentially in recent years. It will grow from $1.28 billion in 2024 to $1.56 billion in 2025 at a compound annual growth rate (CAGR) of 22%. The growth in the historic period can be attributed to the rising adoption of carbon accounting solutions, greater awareness of supplier emissions impact, stronger regulatory pressures on supply chain sustainability, wider integration of environmental reporting practices, and the increasing emphasis on energy efficiency in procurement.

The artificial intelligence (AI)-driven supplier emissions benchmark market size is expected to see exponential growth in the next few years. It will grow to $3.41 billion in 2029 at a compound annual growth rate (CAGR) of 21.6%. The growth expected in the forecast period can be attributed to the expansion of sustainable supply chain initiatives, increasing demand for transparent supplier emissions data, stronger corporate commitments to net-zero targets, the need for predictive emissions management, and the focus on risk mitigation across global supply chains. Key trends anticipated during this period include advancements in AI algorithms for emissions benchmarking, innovations in real-time data analytics platforms, progress in digital twin technology for supply chain monitoring, research and development in predictive environmental modeling, and the integration of IoT sensors with emissions tracking systems.

The rapid digitization of business operations is expected to drive the growth of the artificial intelligence (AI)-driven supplier emissions benchmark market in the coming years. Digitization involves the adoption of digital technologies across all aspects of a business to improve efficiency, enhance customer experiences, and remain competitive in evolving markets. As businesses increasingly digitize, they generate large and complex datasets, particularly within their supply chains. This makes AI-driven emissions benchmarking critical, as it enables the automation of data processing, accurate analysis of large datasets, and the delivery of actionable insights that would be difficult to achieve manually. For example, in July 2024, the Office for National Statistics, a UK-based government agency, reported that spending on digital infrastructure reached $12.36 billion (£9.2 billion) in 2022, reflecting a 22.9% increase from the prior year. As a result, rapid digitization is fueling the expansion of the AI-driven supplier emissions benchmark market.

Companies operating in this market are introducing advanced technologies such as natural language processing (NLP)-powered emission factor matching to simplify and automate the calculation of Scope 3.1 emissions from unstructured supply chain data. This approach uses AI-driven language models to interpret supplier or procurement data and align it with the most relevant emission factors for sustainability reporting. For example, in May 2025, Climatiq Technologies GmbH, a Germany-based technology firm, launched Climatiq Autopilot, an AI-powered feature designed to automate Scope 3.1 emission calculations. The tool leverages NLP to map unstructured text data to the appropriate emission factors and integrates with enterprise systems via API, providing real-time, audit-ready carbon insights. It also ensures compliance with global standards such as the GHG Protocol and ISO 14067, helping businesses make data-driven decisions to reduce carbon emissions throughout their supply chains.

In July 2025, Green Project Technologies Inc., a US-based carbon accounting software provider, acquired Emitwise for an undisclosed amount. The acquisition is intended to merge Emitwise’s capabilities in automated supply chain emissions tracking and product carbon footprint measurement with Green Project Technologies’ audit-grade accounting platform and ACT Group’s global decarbonization tools. This combination positions the company as a comprehensive provider of enterprise climate management solutions across supply chains. Emitwise Ltd., based in the UK, is known for its expertise in AI-driven supplier emissions benchmarking.

Major players in the artificial intelligence (AI)-driven supplier emissions benchmark market are Microsoft Corporation, Siemens AG, International Business Machines Corporation (IBM), Schneider Electric SE, EcoVadis SAS, Persefoni AI Inc., Pulsora Ltd., Unravel Carbon Pvt. Ltd., CarbonChain Ltd., Mavarick AI Ltd., SINAI Technologies Ltd., GLYNT AI Ltd., CO2 AI Ltd., CarbonAnalytics Ltd., DitchCarbon Ltd., Muir AI Ltd., Vaayu Technologies Pvt. Ltd., Climatiq Ltd., Net0 Ltd., and Footprint Intelligence Ltd.

North America was the largest region in the artificial intelligence (AI)-driven supplier emissions benchmark market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in artificial intelligence (AI)-driven supplier emissions benchmark report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the artificial intelligence (AI)-driven supplier emissions benchmark market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the professional services sector, particularly in legal, consulting, architectural, and engineering domains. Higher costs for imported technology, software licenses, office equipment, and digital infrastructure have raised operational expenses for firms reliant on global tools and platforms. International consulting projects are facing delays or cost overruns due to increased travel expenses and restricted access to foreign-sourced data and tools. Additionally, clients in manufacturing, construction, and logistics, heavily affected by tariffs are cutting back on outsourced services, squeezing demand for professional expertise. As a result, service providers are reevaluating pricing structures, expanding domestic supplier relationships, and investing in AI-driven solutions to sustain profitability and client engagement amid economic uncertainty.

Artificial intelligence (AI)-driven supplier emissions benchmarking refers to a technology solution that leverages AI to track, analyze, and assess the carbon and greenhouse gas emissions of suppliers within a supply chain. Its primary goal is to enable organizations to identify high-emission suppliers, enhance sustainability performance, and make informed, data-driven decisions to reduce their overall environmental footprint.

The core components of AI-driven supplier emissions benchmarking are software and services. Software consists of programs, instructions, and data that allow a computer or device to carry out specific tasks and functions. Deployment options include both cloud-based and on-premises models. The solution caters to organizations of different sizes, including large enterprises as well as small and medium-sized businesses. Applications span carbon footprint analysis, supply chain optimization, compliance management, reporting and analytics, and more. These solutions are adopted across industries such as manufacturing, retail, automotive, energy and utilities, healthcare, food and beverage, and others.

The artificial intelligence (AI)-driven supplier emissions benchmark market research report is one of a series of new reports that provides artificial intelligence (AI)-driven supplier emissions benchmark market statistics, including the artificial intelligence (AI)-driven supplier emissions benchmark industry global market size, regional shares, competitors with the artificial intelligence (AI)-driven supplier emissions benchmark market share, detailed artificial intelligence (AI)-driven supplier emissions benchmark market segments, market trends, and opportunities, and any further data you may need to thrive in the artificial intelligence (AI)-driven supplier emissions benchmark industry. This artificial intelligence (AI)-driven supplier emissions benchmark market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The artificial intelligence (AI)-driven supplier emissions benchmark market consists of revenues earned by entities by providing services such as risk assessment, supplier performance evaluation, sustainability strategy development, predictive emissions modelling, and continuous monitoring. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI)-driven supplier emissions benchmark market also includes sales of IoT emission monitoring sensors, carbon footprint tracking devices, industrial process sensors, and smart energy meters. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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