The Hidden Cost of AI: Gotta Have More Energy
And the Stocks That Could Power Up!
Have you ever wondered what it takes to power all our new chatbots, productivity tools and self-driving cars? While many are talking about the latest AI chips, there's a growing concern that often goes unnoticed: energy use. As AI continues to expand, we must ask: where do we get the energy to fuel this revolution?
AI's Growing Appetite for Energy
Imagine if your neighbourhood suddenly needed as much electricity as a small city. That's similar to what's happening with AI. These systems are getting bigger and hungrier for power. Consider this:
Goldman Sachs Research predicts that by 2030, AI could increase yearly electricity demand by about 200 terawatt-hours. That's roughly equivalent to the electricity use of Australia!
ChatGPT alone, with its millions of users, is using up to 564 megawatt-hours of electricity every day. That's enough to power about 20,000 average U.S. homes.
The Push to Renewables
We're just beginning to see AI's potential, but we're already facing a big energy challenge. Various studies estimate that data centers could increase US electricity use up to 9% by 2030, driven by the growing demands of AI technologies. This is worrying because many data centers still rely partly on fossil fuels for power. If we can't meet AI's growing energy demands with clean energy sources, our increased reliance on fossil fuels could accelerate the rise in CO2 emissions, further driving climate change.
Recognizing this risk, big tech companies are taking action:
Microsoft has recently collaborated with Brookfield Asset Management to invest more than $10 billion to develop 10.5 gigawatts of renewable energy capacity between 2026 and 2030 in the U.S. and Europe.
Google is aiming to operate on 24/7 carbon-free energy across its entire global data centre network by 2030.
Amazon Web Services (AWS) aims to power its operations with 100% renewable energy by 2025.
Challenges persist: intermittent renewables, regulatory hurdles for nuclear, and outdated grid infrastructure struggle to meet AI's massive energy demands. Emerging technologies like energy storage, and smart grids may offer solutions, but significant infrastructure upgrades are needed.
To tackle this energy challenge, we need to work on two main areas:
Cleaner Energy Sources:
Natural Gas as a transitional fuel (cleaner than coal)
Improved Solar and wind power (but bigger and better)
Nuclear fusion (what powers the sun, providing limitless clean energy)
Hydrogen fuel cells (battery that never runs out as long as you have enough hydrogen, with water as the only byproduct.)
Smarter Energy Use
More efficient AI algorithms (doing more with less power)
AI-powered energy management (using AI to make AI use less energy)
AI to forecast energy supply and demand, to manage & improve grid (predicting and balancing supply and demand)
Upgrading power grids (Smart Grids) and deploying large-scale battery storage (making power network more responsive and efficient)
Companies Positioned to Benefit:
If we solve this energy puzzle, several industries could see significant growth:
Companies developing wind, solar, and other renewable energy sources.
Tech firms creating more energy-efficient AI chips and energy storage solutions.
Companies focusing on making data centers more sustainable and efficient.
Public Company Investment Ideas:
Clean Energy Providers:
NextEra Energy (NYSE: NEE): The big player in wind and solar
Brookfield Renewable Partners (NYSE: BEP): Diverse clean energy portfolio
Constellation Energy Corporation (NASDAQ: CEG): Focusing on nuclear and renewables
iShares Global Clean Energy ETF (NASDAQ: ICLN): Broader exposure to companies across the clean energy sector
AI Chip Makers:
NVIDIA (NASDAQ: NVDA): Making AI chips that use less power
AMD (NASDAQ: AMD): Competing with NVIDIA in energy-efficient AI chips
Qualcomm (NASDAQ: QCOM): Developing AI-optimized mobile processors for energy-efficient edge computing
Taiwan Semiconductor Manufacturing Company (NYSE: TSM): The world's biggest chip-making factory, building advanced AI chips for top tech companies
Google (Alphabet Inc., NASDAQ: GOOGL): Building special chips to power their AI systems more effectively
Data Center and Energy Management Specialists:
Vertiv (NYSE: VRT): Specializes in critical digital infrastructure
Digital Realty (NYSE: DLR): Major data center REIT with sustainability initiatives
General Electric (NYSE: GE): Leader in power systems and grid solutions, with a growing focus on AI-enabled smart grid technologies
Itron (NASDAQ: ITRI): Provides smart metering, data analytics, and smart city solutions for efficient energy management
Conclusion
The AI revolution's massive energy demands present both a critical challenge and a compelling investment opportunity. As global electricity consumption for AI surges, companies innovating in sustainable power solutions, energy-efficient hardware, and smart grid technologies are positioning themselves for potential growth. While risks exist in this fast-evolving market, the companies that successfully address AI's energy needs may define our technological future and offer significant opportunities for informed investors.
Those are my Thoughts From the DataFront
Max
Forward-Looking Statement and Disclaimer:
This blog post contains my personal opinions and is for informational purposes only. It is not financial advice. The companies and investment ideas mentioned are examples, not recommendations. Investing carries risks, and past performance doesn't guarantee future results. The AI and energy sectors can be particularly volatile.
Always do your own research and consult a qualified financial advisor before making investment decisions. I'm not a licensed financial advisor and don't guarantee the accuracy of this information. Forward-looking statements are subject to risks and uncertainties; actual results may differ materially.
By reading this, you acknowledge these risks and agree that I'm not responsible for your investment decisions. Invest responsibly and stay informed.
Great work, Max!!! Resource use is an important angle to consider. The drive to increase the power of our system is not without significant consequences for our planet or the future of humanity.
Such a great article Max. It's such an interesting question. A couple of additional thoughts:
* To your point about energy efficiency, I wonder how much AI moves on device - all the big foundational models are expensive to train (both chip wise, plus energy wise), and much of the compute today to answer queries is done in data centres. But once models get smaller, and computers/phones continue to increase in their ability to process on device, I wonder how much moves on device (and as part of the day to day, which doesn't impact much your need to charge your device daily). Interesting research question that could also form part of investment thesis. Could Apple just grab a huge chunk of this market if all the AI is running directly on iPhones?
* A lot of what Google has said about AI is that while its driving an increase in their emissions due to more data centre energy use, there is a lot of potential for AI to help in solving climate challenges, helping creating companies that are providing solutions, coming up with unique ideas, etc. A lot of doomers / degrowthers discard the possibility of immense productivity gains from AI that helps solve the climate crisis, even though to get their, it might exacerbate it a little.