2025 Sustainable Investing Trends
Fourth Quarter
Key Takeaways
Artificial Intelligence (AI) can enhance efficiency and reduce carbon emissions, but its rapid growth raises significant energy and water consumption concerns.
Investors must navigate the benefits of AI-driven advancements while managing environmental and social governance challenges.
AI: A Double-Edged Sword for Productivity, Power and People
AI is reshaping the global economy and the sustainable investing landscape. AI has great potential for reducing carbon emissions and boosting efficiency gains. However, its rapid adoption has led to soaring demand for power and water, raising social license challenges (e.g., gaining societal trust, addressing privacy concerns) and governance risks.
This creates a pressing need for investors to capture the upside potential of AI-driven innovation while managing environmental and social externalities.
AI Is Power-Hungry and Extremely Thirsty
AI-driven innovation and related structural build-outs are causing a significant surge in electricity use worldwide. Data-center power demand is expected to double by 2030, largely due to growth in AI workloads.
In the U.S. alone, data centers could account for as much as 8.6% of total electricity usage by 2035, up from roughly 3.5% today.1
Keep in mind that from 2008 to 2021 (the year before ChatGPT was released), the annual increase in electricity demand in the U.S. was nearly flat.2
Along with concerns about energy use, AI guzzles water. The cooling systems that hyperscale data centers use to keep their servers from melting consume massive amounts of water. Some data centers use up to a billion gallons per year, enough to meet the water needs of 10,000 U.S. households annually.3
This situation intensifies concerns about water scarcity and makes it increasingly risky to plan new housing and business projects in regions where water supplies are already limited.
Separately, AI hardware relies on rare earth and other critical minerals, many of which are refined in China (some over 90%).4 This reliance exposes supply chains to geopolitical uncertainties and vulnerabilities around material environmental, societal and governance issues.
AI Is Improving Sustainability Across Sectors
Amid these challenges, we must recognize that AI can lead to transformative solutions to environmental problems. Advanced AI algorithms optimize energy grids, forecast renewable power generation, and balance supply and demand for electricity in real-time, enhancing grid reliability and reducing the carbon intensity of the utility sector.
AI-driven analytics help manufacturing companies detect inefficiencies, reduce waste and minimize emissions.
In agriculture, AI-powered sensors and other tools enable precision irrigation and crop management to conserve water and boost yields while lowering demand for fertilizer and other inputs.
AI also enhances environmental monitoring by processing vast amounts of data from sensors and satellites to help track pollution, deforestation and biodiversity loss. This facilitates more targeted interventions and improves resource allocation.
In addition, as data centers demand more power, hyperscalers seeking to decarbonize their operations and ensure long-term energy security are accelerating investments in nuclear and renewable energy sources.
By signing power purchase agreements for solar, wind, and modernized nuclear generation, these technology leaders are reducing their reliance on fossil fuels and supporting the integration of clean energy into the grid. This is helping drive a broader energy transition, reducing the environmental footprint of the digital infrastructure needed to support AI, and setting new benchmarks for responsible growth in the AI era.
As these technologies mature, AI promises to mitigate its own carbon footprint and accelerate the transition toward a more efficient, circular and resilient global economy.
AI’s Societal and Governance Downsides
As AI infrastructure expands, community pushback is growing. Due to concerns about grid strain, rising electricity costs, water usage and large tax incentives, local opposition has delayed or halted over $60 billion in projects since 2023.5 These challenges may lead to a halt in new construction projects and increased difficulties in obtaining permits.
From a workforce perspective, AI is predicted to reshape 44% of core job skills within the next five years.6 Organizations that fail to establish robust upskilling and reskilling programs may face reputational and operational risks.
Beyond job implications, AI poses many risks for individuals and society, including privacy breaches, algorithmic biases, and misinformation, such as “hallucinations,” faulty diagnoses and denied insurance claims.
These concerns are prompting increased scrutiny from investors. Effective AI governance is becoming an urgent issue, with AI-related shareholder proposals quadrupling in 2024 and S&P 500® companies enhancing their disclosures around AI oversight.
Investors now expect clearly defined accountability, comprehensive risk frameworks and concrete ethics policies covering AI usage. Transparency is also increasingly important: Stakeholders seek more detailed reporting and community benefit agreements.
These factors are becoming prerequisites to operating AI data centers.
AI’s Opportunities and Risks
For investors, the evolving AI landscape presents significant opportunities and notable risks.
On the opportunity side, we believe companies that provide clean energy and grid enablers — including utilities, energy storage and transmission — are poised to benefit. Additionally, businesses specializing in efficiency technologies, such as advanced cooling systems and high-performance chips, likely stand to gain.
Investments in water-smart infrastructure and closed-loop cooling systems are becoming more attractive as data center growth intensifies concerns about resource use.
On the other hand, risks are mounting for greenfield hyperscale projects in water-stressed regions and companies that lack credible AI governance frameworks or robust workforce transition plans. Heavy reliance on hardware supply chains that depend on rare-earth mineral processing also introduces vulnerabilities.
To navigate these issues, investors should prioritize engagement in several key areas. These include setting and tracking specific energy and water efficiency metrics, such as hourly renewable energy matching and reclaimed water use.
Meaningful engagement with local communities is essential; evidence of this could include Community Benefit Agreements, local hiring initiatives, and proactive mitigation of environmental impacts. Rigorous AI governance requires board-level accountability, regular AI bias audits and robust privacy safeguards.
Lastly, focusing on human capital through AI literacy programs, upskilling metrics, and thoughtful workforce transition planning will be vital for sustainable success in the age of AI.
How AI Is Shaping the Future of Sustainable Investing
We believe innovation and sustainability are not only compatible but can also reinforce each other. At this pivotal time in AI’s development and adoption, the convergence of these two imperatives requires investors to act with conviction and foresight.
Those who champion clean energy, advanced efficiency solutions and responsible water management will not only promote the digital future but also safeguard communities and resources.
By prioritizing robust governance, accountable supply chains and thoughtful workforce strategies, investors may be able to turn potential AI-related risks into sources of enduring value.
As we move into the age of AI, we believe the decisive advantage will belong to those who prioritize engagement, drive measurable impact and set new standards for leadership.
Head of Sustainable Investing
¹ EPRI, “Powering Intelligence: Analyzing Artificial Intelligence and Data Center Energy Consumption,” May 28, 2024; Andreas Franke, “Global Data Center Power Demand to Double by 2030 on AI Surge: IEA,” S&P Global, April 10, 2025; Helen Kou and Nathalie Limandibhratha, “Power for AI: Easier Said Than Built,” Bloomberg NEF, April 15, 2025.
² U.S. Energy Information Administration, “After More Than a Decade of Little Change, U.S. Electricity Consumption Is Rising Again,” May 13, 2025.
³ Miguel Yañez-Barnuevo, “Data Centers and Water Consumption,” Environmental and Energy Study Institute, June 25, 2025.
⁴ Gabriel Gavin, “Precious Rare Earth Metals Belong to the State, China Declares,” Politico, June 30, 2024.
⁵ IndexBox, “U.S. Communities Halt $64B in Data Centers Over Environmental Fears,” August 24, 2025.
⁶ TCW Global, “The Workforce Disruption Is Already Here,” July 24, 2025.
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