Artificial Intelligence (AI) has revolutionized industries but poses significant environmental challenges due to its substantial energy consumption and carbon emissions associated with training large AI models and operating data centers. These centers, essential for AI operations, consume vast amounts of electricity and generate a carbon footprint that can surpass that of the airline industry, raising concerns about AI's sustainability. The energy-intensive nature of training models like GPT-3 results in high CO₂ emissions, which are exacerbated by the need for extensive computational power and cooling systems in data centers. This environmental impact is compounded by issues such as water consumption and electronic waste production linked to AI infrastructure. To mitigate these effects, the industry is encouraged to adopt sustainable practices, such as optimizing AI architectures, using energy-efficient hardware, and relying on renewable energy sources for data centers. Moreover, AI holds the potential to contribute to environmental sustainability by optimizing renewable energy systems, improving waste management, and aiding in climate change mitigation. Ethical AI development also requires transparency and accountability to ensure that AI systems are developed responsibly and do not exacerbate environmental or societal challenges. By prioritizing sustainability and ethical standards, the AI industry can align its innovations with global environmental goals and reduce its ecological footprint.