Introduction
Many people, even when told that "AI will improve productivity," don't know exactly how to go about it. I, too, once struggled with the idea that "digitalization" and "AI utilization" were wonderful things, but I didn't know where to start.
In this article,Latest research reportBased on this, we will explain the core of the energy problems facing the US AI strategy. This is not merely a discussion of technology; we will answer questions such as "Why are energy sources important?" and "What are the specific risks?"
This article is especially recommended for those who want to learn about AI strategies, business executives interested in planning the future of their companies, and environmental professionals who are paying attention to SDGs and sustainability.
The Strategic Risks of Fossil Fuel Dependence to the US AI Strategy – Energy Issues are the Most Important Challenge
As of June 2026, the reality is that "the United States is in a competition to maintain its global dominance in artificial intelligence." However, a major problem lies behind this.
The core fact: The difference in energy sources determines the outcome.
The approaches to AI in the United States and China are fundamentally different.
Current situation in the United States
- The Trump administration withdrew support for renewable energy programs.
- Data centers are expected to account for nearly half of the increase in electricity demand from now until 2030.
- Even in the 2020s, fossil fuels, especially natural gas, will still supply more than half of the electricity needed for AI.
China's approach
- Shifting data center power to renewable energy
- Develop computing resources near renewable energy power plants located in coastal areas.
- From 2030 onward, both the amount and proportion of electricity generated from fossil fuels will decline.
This difference has a decisive impact on competitive advantage in the field of AI.
Why are energy sources important?
AI data centers consume vast amounts of electricity. Global data center power demand is projected to exceed 1,000 terawatt-hours (TWh) by 2030, double the current 460 TWh.
The impact of differences in energy sources:
- Cost: Average electricity prices in the US have already risen by 381 TP3T since 2020.
- Supply stability: Renewable energy is on a long-term downward trend.
- Environmental issues: Water shortages negatively impact food production.
Solving Energy Problems in AI Data Centers: 5 Key Points Regarding Specific Risks and Countermeasures
Point 1: Differences in electricity costs affect profitability.
Average electricity prices in the US have already risen by 381 TP3T since 2020. This is linked to increased demand from AI data centers. Meanwhile, renewable energy prices continue to fall at a faster pace than fossil fuel prices.
Result: In the long term, Chinese AI is likely to put US AI at an even greater disadvantage.
Point 2: Water shortages threaten food security.
One-third of the power supply for data centers in the United States is located in areas with severe water shortages. This increases the risk that AI poses to long-term food security.
Impact: There is a close relationship between energy, water, and food production. In the United States, increased energy demand from fossil fuels since 2020 will strain water supply and demand more than if renewable energy were used.
Point 3: Transition to renewable energy is essential.
China's approach is clear: it is working to develop computing resources near renewable power plants located along the coast. This will allow AI data centers to rely on renewable energy for their power supply.
Point 4: Differences in cost efficiency determine competitive advantage.
While fossil fuel prices are unstable, renewable energy prices are trending downwards. This is an important factor in investment decisions in the AI sector.
Point 5: A long-term perspective is necessary.
While the U.S. may be able to improve productivity in the short term, continued reliance on fossil fuels could ultimately lead to a strategic defeat.
Supplementary Information and Points to Note: The Multifaceted Impacts of Energy Issues
Data center power demand forecast
According to forecasts by the International Energy Agency (IEA), global electricity demand from data centers will increase as follows:
- 2024: 460 terawatt-hours (TWh)
- 2030: Expected to exceed 1,000 terawatt-hours.
- 2035: Expected to reach 1300 terawatt-hours.
This represents a scale that is roughly double the current level and will expand even further. In the United States in particular, it is estimated that data centers will account for "nearly half of the increase in electricity demand from now until 2030."
The relationship between energy and food
AI data centers consume vast amounts of water, impacting agricultural water resources. This could threaten long-term food security. According to an analysis by Bloomberg News, one-third of data centers built or planned since 2022 are located in areas with tight water supply and demand.
Impact on investment decisions
For companies, when making AI investments:
- Electricity costs: Renewable energy will be cheaper in the long run.
- Environmental regulations: Dependence on fossil fuels will be a risk factor in the future.
- Social evaluation: Prioritizing sustainability leads to increased shareholder value.
Summary: Energy strategy will determine the winner and loser in the AI competition.
Technological innovation alone is not the only important factor. The underlying energy strategy is the crucial factor that determines long-term competitive advantage.
The real battleground in the AI competition
The U.S. AI strategy may lead to increased productivity in the short term. However, if reliance on fossil fuels continues, the following risks exist:
- Long-term rise in electricity costs
- Water shortages leading to supply instability
- Negative impact on food security
In contrast, China's approach is sustainable and has the potential to secure a long-term competitive advantage.
Lessons for businesses
In the business world, it's crucial not to be fixated on short-term profits. This is because investments that ignore future risks will ultimately lead to significant losses. Considering sustainability in all businesses, not just AI strategies, is essential for long-term success.
The relationship between SDGs and energy issues
Environmental issues are becoming a management challenge. They are no longer merely CSR activities, but a crucial element that touches the very core of business operations. Improving energy efficiency is not only about cost reduction, but also about fulfilling social responsibility.
A perspective on the future
As competition in the AI field intensifies, the approach companies should take is clear:
- Investing in renewable energy leads to long-term cost savings.
- Development of water recycling technologies: Balancing environmental impact reduction and risk management.
- Rebuilding Supply Chains: Sustainability-Conscious Partnerships
Finally, the secret to true competitive advantage
The problems facing U.S. AI strategy are not simply energy issues; they are issues of sustainability. It is short-sighted to think that it is enough to simply make a profit in the short term, because investments that ignore future risks will ultimately lead to huge losses.
In the business world, "investing in the future" is what creates true competitive advantage. Considering "sustainability" in all business activities, not just AI utilization, is essential for long-term success.
Use this article as a guide to reconsider your company's AI strategy and energy procurement. Technological innovation alone is not enough. Harmonizing it with the underlying concept of a "sustainable society" is the key to creating true competitive advantage.
