Use AI to Measure Emissions—Exhaustively, Accurately, and Frequently

New BCG GAMMA Survey Reveals That Only 9% of Organizations Are Able to Measure Their Total Greenhouse Gas Emissions Comprehensively

  • Ability to Measure Exhaustively, Accurately, and Frequently Is Critical to Achieving Reduction Goals
  • New AI-Supported Tools Can Help Take Companies to the Next Level of Measurement and Tracking—and, Ultimately, to Significant Emissions Reduction

PARIS—Eighty-five percent of organizations are concerned about reducing their greenhouse gas emissions. Measurement is the most significant roadblock, as only 9% of companies are able to quantify their total emissions comprehensively. These are among the findings of a new survey being released today from Boston Consulting Group (BCG) and BCG GAMMA titled “Use AI to Measure Emissions—Exhaustively, Accurately, and Frequently.”

To assess companies’ ability to measure and reduce their emissions, BCG collected and analyzed responses from executives at 1,290 organizations—across nine major industries worldwide—who have full or partial decision-making responsibility in this regard.

The survey found that companies are failing to measure their emissions:

  • Exhaustively. 81% of respondents omit some of their internal emissions (those related to the company’s own activities) in their reporting, and 66% of respondents do not report any of their external emissions (those related to the company’s value chain)
  • Accurately. Respondents estimate an average error rate of 30% to 40% in their emissions measurements
  • Frequently. 53% of respondents say they have difficulty in making and tracking decisions due to infrequent measurements
  • Automatically. 86% of respondents still record and report their emissions manually using spreadsheets, and only 22% of respondents have automated processes

“When companies aren’t able to understand their baseline emissions levels, how can they expect to track their emissions and set the right targets?” asked Sylvain Duranton, the global leader of BCG GAMMA and a coauthor of the survey. “For instance, if they are not collecting and analyzing granular data and emissions factors, they can’t expect their measurements to be accurate. We worked with a spirits company that was not breaking down and measuring emissions related to their glass bottles by input, such as supplier, color, materials, or country of origin; when they did, they found emissions were 45% higher than initially measured.”

Eighty-seven percent of the survey respondents want to increase the scope of their reporting, while 66% hope to update their emissions reporting yearly—or even more often. To do so effectively, however, they will require new AI-based tools. Organizations can use these tools in a range of ways, including to automatically ingest and report data, calculate a carbon footprint, run simulations, set targets, manage a global portfolio of abatement initiatives, and more.

“New AI-supported tools can play a crucial role in taking companies to the next level of measurement and reporting and, ultimately, to significant reductions. In fact, our experience shows us that AI can directly enable the reduction of companies’ emissions by as much as 40% through identifying the best initiatives, tracking results, and optimizing company operations,” said Charlotte Degot, a managing director and partner at BCG and a coauthor of the survey.

Explore some of the detailed survey findings in a slideshow here.

View a TED Talk by Charlotte Degot in which she explains how AI makes it possible for corporations to set meaningful climate targets, more accurately track their progress, and reduce pollution over time here.

To arrange an interview with one of the authors, please contact Eric Gregoire at +1 617 850 3783 or


BCG GAMMA is BCG’s global team dedicated to applying artificial intelligence and advanced analytics to critical business problems at leading companies and organizations. The team includes more than 1500 data scientists and engineers who utilize AI and advanced analytics (including machine learning, deep learning, optimization, simulation, natural language, and image analytics) to build solutions that transform business performance. BCG GAMMA’s approach builds value and competitive advantage at the intersection of data science, technology, people, business processes, and ways of working.

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