Market Insight: Nine Ways AI Will Drive Decarbonization

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Executive Summary

Net zero and sustainability executives face multiple obstacles when implementing a decarbonization strategy, from creating a large repository of carbon data sourced across the organization to facing uncertainties around their net zero targets. As software vendors and consultancies incorporate AI into their products and offerings to provide solutions to common decarbonization challenges, they should carefully consider their positioning in the market, as well as unexplored opportunities for the application of AI to decarbonization use cases. Potential – and existing – applications span carbon data anomalies detection, carbon calculations facilitation, emissions forecasting, supply chain emissions hotspot identification, and methane leaks detection and prevention. 
Applications of artificial intelligence will have a large net impact on decarbonization
AI lends itself to large emissions data sets and forward-looking analysis
Applying AI to decarbonization strategy development and implementation
Figure 1. AI helps overcome challenges to manage carbon data and implement decarbonization plans
Figure 2. Net zero target-setting, pathways and forecasting is a high priority for over half of respondents

About the Authors

Alessandra Leggieri

Alessandra Leggieri

Industry Analyst

Alessandra Leggieri is an Industry Analyst in the Verdantix Net Zero & Climate Risk practice. Her current research agenda focuses on solutions for GHG emissions and net ze…

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Ryan Skinner

Ryan Skinner

Research Director, Net Zero & Climate Risk

Ryan is the Research Director for the Verdantix Net Zero & Climate Risk practice. He guides the research team to develop compelling research at the intersection of net zer…

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