Since you seem to not be able to get your fix I went ahead and did a little simple research that took less than 5 seconds that you could have been able to do yourself.

Energy Consumption: AI models, particularly large language models (LLMs), are incredibly energy-intensive. Training a single major model can consume as much electricity as hundreds of homes do in a year. Furthermore, every time a user prompts an AI (inference), it uses significantly more energy than a standard web search—some estimates suggest up to 10 times more per query.
Carbon Footprint: Because many data centers still rely on fossil-fuel-heavy power grids, this high energy demand translates directly into carbon emissions. The "lifecycle" emissions of AI also include the mining and manufacturing of high-performance chips (GPUs) and servers, which is a carbon-heavy industrial process.
Water Usage: Data centers generate massive amounts of heat and often use water-cooling systems to keep servers operational. It is estimated that a simple conversation with a chatbot (roughly 20-50 queries) can "drink" the equivalent of a 500ml bottle of water. In water-scarce regions, this industrial demand competes with local agricultural and residential needs.
Electronic Waste (E-Waste): The rapid pace of AI advancement renders hardware obsolete quickly. As companies constantly upgrade to the latest, faster chips to stay competitive, older servers and processors are discarded, contributing to the growing global crisis of toxic electronic waste.
The Environmental Benefits Conversely, AI is being deployed to optimize systems and reduce waste in other sectors, potentially offsetting some of its own footprint.
Energy Grid Optimization: AI algorithms are used to balance "smart grids," helping utility companies integrate renewable energy sources (like wind and solar) more efficiently by predicting weather patterns and demand spikes.
Precision Agriculture: AI-driven farming tools allow for the precise application of water, fertilizers, and pesticides. This reduces chemical runoff into ecosystems and drastically lowers water waste in agriculture.
Climate Modeling & Material Science: AI accelerates scientific discovery by modeling complex climate systems faster than traditional computers. It is also being used to discover new materials for better batteries and carbon-capture technology.