An Empirical Analysis of the Relationship Between Artificial Intelligence Technology Growth and Energy Consumption in the United States Using Logistic and Time Series Modeling: Implications for Iran

Document Type : Original Article

Authors

Meysam Pashayi ¹

saleh Ghavidel Doostkouei ¹

Masoud Sofimajidpour ¹

Mahmood Mahmoodzadeh ²

¹ Department of Economics, Fi.C., Islamic Azad University, Firoozkooh, Iran.

² Department of Economics, Fi.C., Islamic Azad University, Firoozkooh, Iran

https://doi.org/10.22067/erd.2025.94492.1306

Abstract

This study aims to analyze the growth trajectory of artificial intelligence (AI) technology and assess its impact on energy consumption in the United States, with the intention of deriving implications for Iran. To measure the level of AI development, two proxy indicators were employed: the number of AI-related patents and the share of AI patents in total registered patents. A logistic growth function was used to model the technology growth, given its suitability for describing saturating growth patterns. The findings indicate that both indicators exhibit rapid growth, with the midpoint of growth estimated to occur in 2024 for both cases. The saturation level for the number of patents is projected around 2050, while the saturation for the share of AI patents is anticipated by 2060. Subsequently, using two forecasting scenarios, the impact of AI growth on energy consumption was examined. The results of energy demand modeling, using a structural time series model, reveal that AI-related variables have a positive and significant effect on energy consumption. These findings offer valuable insights for AI investment strategies in Iran and highlight that the expansion of data centers and related infrastructure—currently in its early stages in Iran—could substantially increase energy demand.

Keywords

Artificial Intelligence (AI) Growth

Energy Consumption

Logistic Growth Modeling

Structural Time Series Analysis

Subjects

• Energy Economy

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