How AI leaders are reducing their ecological impact

The AI rollercoaster of expectations and concerns continues to twist at breakneck speeds as enterprises inch ever closer to understanding the rapidly changing technology and its possible functions within their business. Most recently, advanced artificial intelligence platforms such as generative AI and large language models (LLMs) have fallen under scrutiny for their voracious energy consumption and consequent ecological impact, with some researchers hypothesizing that LLMs consume hundreds of liters of freshwater and produce annual emissions equivalent to that of a small country.

With global warming exceeding 1.5 degrees across an entire year for the first time, global stakeholders are questioning where the bulk of responsibility should lie in preventing the climate crisis from worsening. Climate change remains an issue of critical importance for consumers and companies alike amidst these global efforts to reduce CO2 emissions, boding poorly for the public image of any company that uses consumptive AI tools without keeping their carbon footprint in check. More importantly, rampant unchecked AI use could have disastrous consequences for the environment – research from MIT suggests that training just , which has the potential to significantly counteract global progress in combatting climate change.