Report on the Environmental and Sustainable Development Impacts of AI Data Center Expansion

Executive Summary

A proposed strategy to accelerate the development of Artificial Intelligence (AI) in the United States, primarily through the deregulation of land use for data center construction, poses significant challenges to the nation’s commitment to the Sustainable Development Goals (SDGs). The plan’s emphasis on rapid technological dominance risks undermining progress on climate action, clean energy, sustainable communities, and responsible production. The high energy and land requirements for AI infrastructure are already leading to increased fossil fuel reliance and the conversion of agricultural land, directly conflicting with established sustainability targets.

Analysis of AI Expansion and its Impact on Sustainable Development Goals (SDGs)

SDG 13: Climate Action & SDG 7: Affordable and Clean Energy

The expansion of AI data centers presents a direct threat to climate and clean energy goals. The immense energy required to power these facilities is leading to a renewed dependence on fossil fuels.

• Increased Fossil Fuel Reliance: To meet the high energy demands of new AI infrastructure, fossil fuel plants are reportedly being reopened. Ben Murray, a senior researcher with Food and Water Watch, stated, “anything that prolongs our reliance on fossil fuel is going to increase the problems that we’re seeing from the climate crisis.”
• Undermining Climate Commitments: The push for more data centers is reportedly causing major technology companies to backtrack on their climate goals. A 2024 report found that emissions from data centers owned by Apple, Google, Meta, and Microsoft were over seven times higher than what the companies had officially reported. Murray noted, “the emissions are amping up faster than ever for these companies,” despite appearances of meeting net-zero targets.
• Energy Consumption Inefficiency: AI-powered servers require substantially more energy than traditional ones. A single ChatGPT query, for instance, can consume up to ten times more electricity than a standard Google search, challenging the principles of affordable and clean energy under SDG 7.
• Renewable Energy Potential: While powering AI services with renewable energy sources is feasible, it requires significant political will to implement, a factor currently secondary to the goal of rapid AI development.

SDG 9: Industry, Innovation, and Infrastructure & SDG 11: Sustainable Cities and Communities

The strategy to remove prohibitive land use and permitting regulations is designed to fast-track the construction of AI infrastructure. However, this approach overlooks the core tenets of building resilient and sustainable infrastructure as outlined in SDG 9 and creates adverse effects for local communities, conflicting with SDG 11.

1. Regulatory Rollbacks: The administration’s position is that environmental and permitting regulations slow America’s progress in achieving dominance in the AI field.
2. Community Impact: Local support for these projects is low due to concerns over negative externalities, including increased traffic, noise pollution, and the potential for higher household energy prices as the grid is strained.
3. Land Use Transformation: The development of these centers involves significant changes in land use, often with consequences for the local environment and community character.

SDG 2: Zero Hunger & SDG 12: Responsible Consumption and Production

The physical footprint of data centers and the consumption patterns they support have direct implications for food security and responsible resource management.

• Loss of Agricultural Land: A significant case involves a 1,200-acre corn and soybean field near New Carlisle, which as of June 2025, has been converted to host eight Amazon-led AI energy centers, with plans for a total of 30. This conversion of arable land directly impacts SDG 2 by reducing land available for food production.
• Unsustainable Production Patterns: The massive and underreported energy consumption required for AI operations represents a move toward more unsustainable production and consumption patterns, directly opposing the objectives of SDG 12.

Case Studies in AI Infrastructure Development

Microsoft in Laporte, Indiana

An investment of $1 billion was announced by Microsoft to construct a new AI data center. This facility is intended to generate cloud computing infrastructure, exemplifying the scale of investment driving the AI expansion.

Amazon in New Carlisle, Indiana

Amazon is converting a 1,200-acre agricultural site into a massive AI energy hub. The project, which began with eight centers, is planned to expand to a total of 30 facilities, highlighting the extensive land-use changes associated with the industry’s growth.

Analysis of SDGs, Targets, and Indicators

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 7: Affordable and Clean Energy
  
  The article focuses on the massive energy demands of AI data centers, which are being met by reopening fossil fuel plants, directly conflicting with the goal of promoting clean energy.
• SDG 9: Industry, Innovation and Infrastructure
  
  The core issue is the development of new infrastructure (AI data centers) for a major innovation (AI), but this development is described as environmentally unsustainable due to its high energy consumption and reliance on fossil fuels.
• SDG 11: Sustainable Cities and Communities
  
  The construction of data centers impacts local communities through the removal of land use rules, conversion of agricultural land, and resident concerns over increased traffic and noise.
• SDG 12: Responsible Consumption and Production
  
  The article highlights irresponsible production patterns by tech companies, noting their actual emissions are far higher than reported and that they are backtracking on climate commitments to fuel AI growth.
• SDG 13: Climate Action
  
  A central theme is the negative impact on the climate. The article explicitly states that prolonging reliance on fossil fuels for AI “is going to increase the problems that we’re seeing from the climate crisis.”
• SDG 15: Life on Land
  
  The article mentions the direct impact on land use, specifically the conversion of a “1,200-acre corn and soybean field” into a site for numerous data centers, representing a loss of agricultural land.

2. What specific targets under those SDGs can be identified based on the article’s content?

• SDG 7: Affordable and Clean Energy
  • Target 7.2: By 2030, increase substantially the share of renewable energy in the global energy mix. The article indicates a move away from this target, as “fossil fuel plants are already being reopened to help meet high energy demands” for AI, despite the possibility of using renewable sources.
• SDG 9: Industry, Innovation and Infrastructure
  • Target 9.4: By 2030, upgrade infrastructure and retrofit industries to make them sustainable… The article shows a conflict with this target, as the new AI infrastructure is increasing reliance on fossil fuels and causing emissions to “amp up faster than ever,” making it less sustainable.
• SDG 11: Sustainable Cities and Communities
  • Target 11.3: By 2030, enhance inclusive and sustainable urbanization and capacity for participatory, integrated and sustainable human settlement planning… The article points to a failure in this area by mentioning the “removal of land use rules” and that “Residents’ support is low due to concerns,” suggesting a lack of participatory and sustainable planning.
• SDG 12: Responsible Consumption and Production
  • Target 12.6: Encourage companies, especially large and transnational companies, to adopt sustainable practices and to integrate sustainability information into their reporting cycle. The article directly challenges this by stating that emissions from major tech companies were “more than seven times higher than officially reported” and that they are “backtracking on their climate goals.”
• SDG 13: Climate Action
  • Target 13.2: Integrate climate change measures into national policies, strategies and planning. The article describes a government plan that prioritizes AI dominance by removing “environmental and permitting regulations,” suggesting climate measures are being de-prioritized rather than integrated.
• SDG 15: Life on Land
  • Target 15.3: By 2030, combat desertification, restore degraded land and soil… and strive to achieve a land degradation-neutral world. The conversion of a “1,200-acre corn and soybean field” into an industrial site for data centers represents a direct loss of productive agricultural land, working against this target.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

• Energy Consumption Levels: The article implies this as a key indicator by comparing the energy use of a ChatGPT query to a Google search (“up to 10 times more electricity”), highlighting the immense power needs of AI.
• Greenhouse Gas Emissions Data: A direct indicator is mentioned when the article cites a report finding that “emissions from data centers owned by Apple, Google, Meta and Microsoft were more than seven times higher than officially reported.” This discrepancy is a measure of transparency and actual environmental impact.
• Share of Fossil Fuels in Energy Mix: The article implies this indicator by stating that “fossil fuel plants are already being reopened to help meet high energy demands.” The number of reopened plants serves as a negative indicator for the clean energy transition.
• Land Use Change: A specific, quantifiable indicator is provided: “a 1,200-acre corn and soybean field just outside of New Carlisle has turned into eight Amazon-led AI energy centers.” This measures the conversion of agricultural land to industrial use.
• Corporate Climate Commitments: The article implies a qualitative indicator by noting that the push for data centers is “leading Big Tech companies to backtrack on their climate goals.” Tracking these public commitments versus actual practice serves as an indicator of corporate responsibility.
• Community Opposition/Support: An implied social indicator is that “Residents’ support is low due to concerns about increased traffic and noise near the centers,” which can be used to measure the social sustainability and acceptance of such projects.

4. Table of SDGs, Targets, and Indicators

Source: publicnewsservice.org