AI in ESG and Sustainability Market Trends 2025

The Global AI in ESG and Sustainability Market is expected to grow rapidly from USD 1.24 billion in 2024 to approximately USD 14.87 billion by 2034, registering a strong CAGR of 28.20% during the forecast period from 2025 to 2034. This surge reflects the increasing demand for data-driven decision-making in corporate sustainability strategies, regulatory compliance, and transparent ESG reporting. Artificial intelligence is being adopted to streamline emissions tracking, automate ESG disclosures, and optimize resource use across industries.

In 2024, the Generative AI segment led the market, holding over 41.8% of the total share. This dominance is driven by its ability to create predictive models, generate sustainability reports, and simulate impact scenarios, thereby enhancing ESG insights for enterprises. Additionally, the Data Collection and Analysis segment captured more than 37.3% of the market share, supported by the critical role of AI in aggregating and analyzing vast, fragmented ESG data from multiple sources for actionable intelligence.

Among industry verticals, Building & Construction emerged as the leading segment in 2024, accounting for more than 31.7% of the market. The sector is increasingly integrating AI to support green building standards, track carbon intensity, and align infrastructure planning with climate goals. Regionally, North America dominated the global market, commanding over 43.8% share and generating around USD 0.54 billion in revenue. The U.S. alone accounted for USD 0.48 billion, with a projected CAGR of 26.7%, underpinned by strong regulatory momentum, corporate ESG mandates, and growing investment in AI-led sustainability tools across sectors.

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1. AI in ESG and Sustainability Market The Global AI in ESG and Sustainability Market is projected to reach USD 14.87 Billion by 2034, growing from USD 1.24 Billion in 2024 at a CAGR of 28.20%. This presentation explores how AI is transforming environmental, social, and governance practices across industries and regions.
2. Market Overview & Growth Trajectory AI in ESG and sustainability leverages artificial intelligence to help organizations improve their environmental, social, and governance practices. By analyzing large volumes of data from reports, climate models, and supply chains, AI generates insights for transparent reporting, risk management, sustainable investments, and compliance. Key drivers accelerating AI adoption include regulatory frameworks like the EU SFDR and U.S. SEC climate mandates, which enhance ESG data transparency and compliance. Growing investor pressure, especially from institutional funds focused on ESG performance, is also driving demand for AI-driven sustainability solutions.
3. Key Market Segments Technology Deep Learning Natural Language Processing (NLP) Generative AI (41.8% market share) Others Function Data Collection and Analysis (37.3% market share) Identification of Patterns and Trends Enabling Predictive Analytics Others Industry Vertical Building & Construction (31.7% market share) Agriculture Food & Beverage Oil & Gas, Mining, Chemicals Others
4. Regional Market Analysis North America Europ e Asia Pacific Latin America Middle East & Africa North America Leadership North America held a dominant market position in 2024, with more than 43.8% of the market share and generating approximately USD 0.54 billion in revenue. The U.S. market alone was valued at USD 0.48 billion in 2024 and is expected to grow at a CAGR of 26.7%, signaling significant expansion in the coming years. This leadership stems from North America's early adoption of advanced technologies, a strong regulatory push for ESG compliance, and a robust digital infrastructure.
5. Technology Analysis: Generative AI Dominance 41.8% Market Share Generative AI held the largest share of the AI in ESG and Sustainability market in 2024 35% Efficiency Gain Average improvement in ESG reporting efficiency through generative AI solutions 3X Faster Analysis Speed increase in processing unstructured sustainability data compared to traditional methods Generative AI's leadership can be primarily attributed to its ability to generate comprehensive ESG reports, simulate future sustainability scenarios, and create synthetic data for ESG model training. Companies facing pressure to produce high- quality disclosures often lack the expertise for manual reporting. Generative AI converts structured metrics and unstructured data into cohesive, investor-ready ESG reports, saving time and ensuring consistency.
6. AI Impact on ESG Practices Enhanced ESG Reporting AI facilitates the collection, processing, and analysis of vast ESG- related data, leading to more accurate and timely reporting. By automating data validation and identifying inconsistencies, AI improves the reliability of sustainability disclosures. Risk Management AI enables corporations to assess climate risks, predict sustainability challenges, and improve efficiency. This leads to cost savings, stronger brand value, and faster industry adoption of sustainable practices. Climate Solutions Despite its environmental costs, AI can help tackle climate challenges by optimizing energy use, enhancing renewable integration, and improving climate modeling. Through better resource management and predictive analytics, AI can reduce emissions.
7. Market Drivers and Challenges Key Drivers Regulatory frameworks like EU SFDR and SEC climate mandates Growing investor pressure for ESG performance Increasing volume of ESG data exceeding manual analysis capabilities Cost savings and efficiency gains from AI implementation Enhanced brand value through transparent sustainability reporting Key Challenges Risk of data bias and inaccuracy affecting AI analysis Environmental footprint of AI technologies (energy and water consumption) Governance and accountability concerns with automated decisions Need for clear ethical guidelines for responsible AI use Ensuring data integrity to maintain trustworthy AI insights
8. Key Market Players Workiva Leading in ESG reporting with its cloud-based platform that helps companies collect, manage, and report ESG data with accuracy and compliance. Supports integrated financial and non-financial reporting for organizations of all sizes. Briink Stands out for using AI to simplify ESG data analysis, especially for EU regulations like the Taxonomy and CSRD. Uses natural language processing to transform regulatory documents and company data into actionable ESG insights. Sweep Offers a platform focused on carbon management, allowing companies to track, reduce, and report emissions across value chains. AI tools help identify emission hotspots and model reduction scenarios while supporting collaboration. Other key players include Clarity AI, GaiaLens, GLYNT.AI, Persefoni, Kanini, Dcycle, Watershed, Sunairio, Exowatt, and FactSet.
9. Future Opportunities and Outlook Enhancing ESG Reporting Accuracy and Efficiency AI technologies are streamlining the ESG reporting process by automating data collection and analysis, reducing processing time and improving report accuracy for better compliance and resource allocation. Optimizing Supply Chain Sustainability AI-driven analytics provide deeper insights into supply chain operations, allowing companies to identify and mitigate environmental and social risks, monitor supplier compliance, and enhance overall resilience. Advancing Climate Risk Assessment AI plays a crucial role in assessing climate-related risks by analyzing complex environmental data, supporting businesses in understanding potential climate impacts and developing mitigation strategies. As the market continues its robust growth trajectory, we expect to see increased integration of AI across all aspects of ESG practices, with particular emphasis on regulatory compliance, investment decision-making, and operational efficiency. The projected CAGR of 28.20% through 2034 indicates substantial opportunities for both established players and innovative startups in this rapidly evolving space.