Recent studies are shining light on the energy consumption and carbon emissions of generative Artificial Intelligence (AI), uncovering that these modern AI models may be more carbon-intensive than we have realized. The hidden environmental cost of AI is becoming more tangible with comparisons suggesting that creating an image with such technologies could require as much energy as charging a mobile phone. This emphasizes the increasing concerns regarding the sustainability of AI applications and their burgeoning role in our daily digital activities. While the one-time energy input to train these large AI models is considerable, it pales in comparison to the emissions generated from their everyday use. Usage emissions can quickly surpass training emissions, with popular models like ChatGPT being used by millions daily. This frequent use is primarily due to the accessibility and integration of AI in consumer applications, such as Google's search engine, which has seen a spike in energy use after the inclusion of generative AI models. It raises the question of whether the convenience of AI is worth the increasing carbon footprint. The discussion extends beyond just numbers and into accountability and consumer awareness. Researchers like Gadepally and Dodge hope that bringing such data to the forefront will prompt consumers to inquire about the sustainability of the AI they use, potentially influencing market dynamics. There is a call for companies to be more transparent and responsible with their models' environmental impact, especially as AI becomes even more entrenched in both commercial and personal spheres. It hints at an emerging ethical dimension where the profitability of AI comes with an environmental responsibility.