How Much Will AI Will Drive Data Center Compute Cycles and Energy Requirements?

According to a study by the Lawrence Berkeley National Laboratory, AI-driven data center electricity consumption could increase by 50 percent to 200 percent by 2040, posing new challenges for data center operators trying to limit and reduce carbon emissions and electrical consumption. 

Study	Year Published	AI-driven electricity consumption (GWh)	Increase over 2023 (%)
Lawrence Berkeley National Laboratory	2020	130	40%
Gartner	2021	200	50%
IDC	2022	300	75%
DigiCapital	2023	400	100%
Study	Year	Projected AI-Driven Data Center Electricity Consumption (2040)	Growth from 2023 (%)
Lawrence Berkeley National Laboratory	2018	10% of total data center electricity consumption	50%
Gartner	2020	15% of total data center electricity consumption	75%
IDC	2021	20% of total data center electricity consumption	100%

Of course, data center operators will continue to seek ways to reduce impact, as well. 

Study	Year Published	Energy Efficiency Savings (%)	Methods Used
Lawrence Berkeley National Laboratory	2020	20-30%	Using more energy-efficient hardware, optimizing the use of data center resources, and using renewable energy sources
McKinsey & Company	2021	30-40%	Using more energy-efficient hardware, optimizing the use of data center resources, using renewable energy sources, and improving cooling efficiency
IDC	2022	40-50%	Using more energy-efficient hardware, optimizing the use of data center resources, using renewable energy sources, improving cooling efficiency, and deploying AI-powered energy management solutions

But there seems little doubt that AI model training and inference generation will become a much-bigger part of data center compute activities and therefore energy load. In some part, that is because bigger models require more data ingestion during the training process. 

JLL Research 

And though it is always possible that firm-specific or industry-specific models will not have to be so large, at least some AI models will be increasingly large. 

Source: RBC Capital Markets

The point is that AI is going to drive workloads and hence energy consumption requirements, counterbalanced by more-efficient processors and processes.