The Impact of Artificial Intelligence Expansion on Sustainable Development Goals

The rapid proliferation of Artificial Intelligence (AI) and its associated data center infrastructure is creating significant challenges to the achievement of several United Nations Sustainable Development Goals (SDGs). The immense electricity demand from these facilities is straining power grids, increasing consumer costs, and undermining efforts to transition to sustainable energy systems. This report analyzes the conflict between current AI development trajectories and key sustainability targets.

Challenges to SDG 7: Affordable and Clean Energy

The expansion of AI directly threatens the core tenets of SDG 7, which aims to ensure access to affordable, reliable, sustainable, and modern energy for all. The industry’s consumption patterns are driving up costs and increasing reliance on non-renewable energy sources.

Escalating Energy Costs and Affordability

The surge in electricity demand from data centers is being passed on to consumers, jeopardizing energy affordability.

• Energy prices saw an average increase of 6.5% between May 2024 and May 2025, directly linked to data center consumption.
• Certain regions experienced far greater price hikes, with increases of 18.4% in Connecticut and 36.3% in Maine.
• Projections indicate that without grid reform, electricity prices in areas with high data center concentration, such as parts of Virginia, could climb by as much as 25% by 2030.

Regression from Clean Energy Targets

To meet the crushing demand from AI, utilities are reverting to less sustainable energy sources, which directly contravenes the “clean energy” aspect of SDG 7 and undermines SDG 13 (Climate Action).

• Utility providers are increasingly relying on aging fossil fuel plants to generate sufficient electricity.
• This reliance on carbon-intensive sources moves energy production away from renewable targets and exacerbates climate change.

Strain on SDG 9: Industry, Innovation, and Infrastructure

While AI represents a significant technological innovation, its current implementation is placing unsustainable pressure on national infrastructure, challenging the goal of building resilient and sustainable systems as outlined in SDG 9.

Power Grid Instability and Lack of Resilience

The U.S. electric grid is ill-prepared to handle the sudden and massive increase in electricity demand, revealing a critical lack of resilient infrastructure.

1. A 2024 report from Lawrence Berkeley National Laboratory highlights an accelerated compound annual growth rate in data center electricity use, rising to 18% between 2018 and 2023.
2. Projections estimate this growth rate will be between 13% and 27% from 2023 to 2028.
3. By 2028, the AI industry’s power usage could represent between 6.7% and 12.0% of total U.S. electricity consumption.

Risks from Ancillary Infrastructure

The backup power systems for data centers introduce further risks to grid stability. Reports cite several “near-misses” where data centers activating their own generators nearly caused an oversupply of electricity, threatening to trigger cascading power outages across entire regions. This complicates the task of balancing national electricity supply and demand, a key component of resilient infrastructure.

Implications for SDG 11: Sustainable Cities and Communities

The concentration of power-hungry data centers has direct negative consequences for local populations, working against the objective of SDG 11 to make cities and human settlements inclusive, safe, resilient, and sustainable.

Degradation of Local Living Conditions

Residents in proximity to data centers face numerous challenges that degrade their quality of life and safety.

• Decreased Power Quality: The immense energy draw can reduce the quality and stability of power for nearby homes.
• Damage to Property: Reduced power quality shortens the lifespan of electrical appliances and can lead to malfunctions, overheating, and electrical fires.
• Pollution: These facilities contribute to local air, noise, and light pollution, impacting community health and well-being.

Contradictions with SDG 12: Responsible Consumption and Production

The operational model of the AI industry is fundamentally at odds with the principles of SDG 12, which promotes sustainable consumption and production patterns.

Unsustainable Production and Consumption Cycles

The AI development process is built on a model of continuous and massive resource consumption.

• AI tools rely on the constant ingestion of vast amounts of information, a process that requires incessant data crawling and retrieval, consuming significant energy.
• Historically, improvements in software efficiency have not led to reduced consumption but have instead been used to incorporate more features, perpetuating the cycle of high demand.
• This model represents an unsustainable pattern of production that prioritizes technological expansion without regard for its environmental and resource footprint.

Sustainable Development Goals (SDGs) Addressed in the Article

The article highlights issues that are directly and indirectly connected to several Sustainable Development Goals. The core problem of increased electricity demand from AI data centers has cascading effects on energy affordability, infrastructure stability, environmental quality, and climate change efforts.

• SDG 7: Affordable and Clean Energy

  This goal is central to the article, which focuses on the rising cost and decreasing reliability of energy due to the massive electricity consumption of data centers. The text explicitly states that “consumer electricity prices across the country are already rising” and that utilities are relying on “aging fossil fuel plants,” which moves away from the “clean energy” aspect of this goal.

• SDG 9: Industry, Innovation, and Infrastructure

  The article directly addresses the strain on infrastructure, stating the “power grid that’s ill-prepared for the sudden spike in demand.” It discusses the need for “grid upgrade costs” and the risks posed to the stability of the electrical infrastructure, which is a key component of this SDG. The innovation (AI) is creating a challenge for existing infrastructure.

• SDG 11: Sustainable Cities and Communities

  This goal is relevant because the impacts are felt at the community level. The article mentions rising electricity bills for consumers, the risk of “cascading power outages” affecting regions, and direct negative impacts on residents living near data centers, such as “air, noise, and light pollution” and reduced lifespan of home appliances.

• SDG 12: Responsible Consumption and Production

  The article describes an unsustainable pattern of consumption. The “massive amounts of electricity used” for AI operations and the “incessant retrieval of the sum of digitally accessible human knowledge” represent a production and consumption model with high energy and resource intensity, which is contrary to the principles of this goal.

• SDG 13: Climate Action

  This goal is implicated by the article’s statement that to meet the increased energy demand, “utilities are increasingly relying on aging fossil fuel plants.” This reliance on fossil fuels directly contributes to greenhouse gas emissions, undermining efforts to combat climate change.

Specific SDG Targets Identified

Based on the article’s content, several specific targets under the identified SDGs can be pinpointed.

1. Target 7.1: Ensure universal access to affordable, reliable and modern energy services.

   The article directly challenges this target by highlighting that energy is becoming less affordable, citing a “6.5% increase in energy prices” on average and projections of prices climbing “as much as 25 percent by 2030” in some areas. It also points to a lack of reliability with mentions of “near-misses” that “narrowly avoided wide-scale blackouts.”

2. Target 7.2: Increase substantially the share of renewable energy in the global energy mix.

   The article suggests a negative trend concerning this target. The statement that utilities are “increasingly relying on aging fossil fuel plants to generate enough electricity” indicates a move away from clean energy to meet the new demand from data centers.

3. Target 9.1: Develop quality, reliable, sustainable and resilient infrastructure.

   The article explicitly states that the U.S. electric grid is “ill-prepared” and not resilient enough to handle the demand. The risk of “cascading power outages” further underscores the lack of reliability and resilience in the current infrastructure.

4. Target 9.4: Upgrade infrastructure and retrofit industries to make them sustainable, with increased resource-use efficiency.

   The issues described run counter to this target. Instead of upgrading to more efficient and clean technologies, the energy sector is reverting to “aging fossil fuel plants.” Furthermore, the article notes that the AI industry itself is not prioritizing efficiency, as “software developers historically see improved efficiency as providing additional space to cram features into rather than a benefit unto itself.”

5. Target 11.6: Reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality.

   This target is directly relevant due to the article’s mention of the “air, noise, and light pollution generated by these facilities,” which are adverse environmental impacts affecting communities where data centers are located.

Indicators for Measuring Progress

The article mentions or implies several quantitative and qualitative indicators that can be used to measure progress (or lack thereof) toward the identified targets.

• Indicator for Target 7.1 (Affordability and Reliability):

  The article provides specific data points that can serve as indicators of declining affordability: the “6.5% increase in energy prices between May 2024 and May 2025,” with regional increases of “18.4% and 36.3%,” and a projected “25 percent” climb by 2030 in Virginia. For reliability, the mention of “near-misses” and the risk of “cascading power outages” serves as a qualitative indicator of decreasing grid stability.

• Indicator for Target 9.4 (Resource-Use Efficiency):

  The growth in electricity consumption by data centers is a clear indicator. The article cites a report showing a “compound annual growth rate of approximately 7% from 2014 to 2018, increasing to 18% between 2018 and 2023.” It also projects that data centers could account for “6.7% to 12.0% of total U.S. electricity consumption forecasted for 2028.” These figures measure the increasing resource intensity of the industry.

• Indicator for Target 13.2 (Climate Action Integration):

  An implied indicator is the share of fossil fuels in the energy mix used to power data centers. The statement about the increasing “relying on aging fossil fuel plants” suggests that this share is growing, which would be a negative indicator for progress on climate action.

• Indicator for Target 11.6 (Environmental Impact):

  The article provides qualitative indicators such as the presence of “air, noise, and light pollution” in communities near data centers. Another is the impact on local infrastructure and property, such as the “reduced life span of electrical appliances,” which can lead to “malfunctions, overheating, and electrical fires.”

Summary of SDGs, Targets, and Indicators

Source: tomshardware.com