Skip to content
    1. Overview
    2. Alternative Managers
    3. Consultants
    4. Corporations
    5. Family Offices
    6. Financial Advisors
    7. Financial Institutions
    8. Individuals & Families
    9. Insurance Companies
    10. Investment Managers
    11. Nonprofits
    12. Pension Funds
    13. Sovereign Entities
  1. Contact Us
  2. Search
Weekly Economic Commentary | May 10, 2024

Empowering AI

AI adoption will dent the fight against climate change.

Download PDF


By Carl Tannenbaum

I noticed something new on the social media platforms that I use.  As I compose each post, I am asked if I want to sharpen the message by using artificial intelligence (AI).  Just to see how it worked, I agreed on one occasion.  A simple message about the job market was transformed into a Marxian manifesto decrying the tyranny of capital over labor.  I couldn’t hit the “undo” key fast enough.

Much as we might try, though, we are unlikely to escape the impact of AI.  The time, attention and money that is being devoted to its development are all substantial.  Another significant input to the transformation is electricity. Simply stated, AI is a power hog.  According to the International Energy Agency, a ChatGPT query uses ten times more electricity than a simple Google search.

High-end analytics and machine learning perform billions of calculations in short spaces of time.  Collecting and organizing the data required is also computationally demanding.

AI is a power hog.

The infrastructure required to support the process—commercial buildings filled with servers bearing sophisticated microchips—requires an immense amount of electricity.  Aside from the needs of these engines, advanced cooling systems are needed to prevent them from overheating. 

Construction of new data centers is at a fever pitch.  Rental rates for space at existing facilities are escalating at an annual pace of close to 20%.  Stress on power grids has consequently been increasing.  And the shares of power generators have been gaining at a pace that is several times the appreciation of the “Magnificent Seven” stocks. Shortages of commodities like copper and water are directly attributable to the headlong drive to expand computing power.

In some areas, AI providers have arranged for dedicated supplies of electricity.  Unfortunately, these sources aren’t always environmentally friendly; in parts of the world, coal-fired power plants have been put back into use to feed the demands of the technology.  Other potential fuel sources are also being explored, but each has important limitations.

These developments put AI on a collision course with another economic megatrend: adapting to climate change. Long before college students were using AI to compose their essays, the world was struggling with energy policy.  The problem is often called a trilemma: a situation in which there are three objectives, but only two can be coincidentally achieved.  The world wants inexpensive energy; it wants clean energy; and it wants to procure energy from reliable sources without compromising geopolitical principals. 

Reconciling these aims carries a very high degree of difficulty.  As an example, one strategy for reducing the growth of carbon emissions is to increase the share of electric vehicles on the road.  But that requires the construction of a vast network of charging stations, which will place steep demands on the electricity grid and compete with the needs of data centers.



In the United States, fossil fuels (primarily natural gas) account for 60% of energy generation.  Nuclear and renewables both hover around 20%.  In the short term, then, we’ll need a good deal more gas-fueled capacity; this will require more investment in a source that generates mixed feelings among investors and consumers.

AI is a power hog.

How, then, to square society’s advancing embrace of AI with its desire to control climate change?  Some suggest a “physician, heal thyself” approach.  Why not let AI loose on the problem, asking it to design optimal data center structure and manage peaks and troughs of power demand?  AI could also potentially examine itself; there may be ways to make the algorithms that run large language models more efficient.

I will be doing my part to address the problem. After my unfortunate experience with the labor market comment, I will not use AI again anytime soon.  It may not save a lot of electricity, but every little bit helps.

Related Articles

Read Past Articles

Meet Our Team

Navigate to undefined

Carl R. Tannenbaum

Chief Economist

Navigate to undefined

Ryan James Boyle

Chief U.S. Economist

Navigate to undefined

Vaibhav Tandon

Chief International Economist

Follow Carl Tannenbaum
Discover the latest economic insights from our chief economist on social media.

Subscribe to Publications on Economic Trends & Insights

Gain insight into economic developments and our latest forecasts for the United States.

Information is not intended to be and should not be construed as an offer, solicitation or recommendation with respect to any transaction and should not be treated as legal advice, investment advice or tax advice. Under no circumstances should you rely upon this information as a substitute for obtaining specific legal or tax advice from your own professional legal or tax advisors. Information is subject to change based on market or other conditions and is not intended to influence your investment decisions.

© 2024 Northern Trust Corporation. Head Office: 50 South La Salle Street, Chicago, Illinois 60603 U.S.A. Incorporated with limited liability in the U.S. Products and services provided by subsidiaries of Northern Trust Corporation may vary in different markets and are offered in accordance with local regulation. For legal and regulatory information about individual market offices, visit