AI technologies are increasingly applied to environmental monitoring, agriculture, and geological exploration. According to the IEA, existing AI solutions could potentially reduce global CO2 emissions by 1.4 billion tons by 2035, while annual emissions from data centers are estimated at 180 million tons.
In agriculture, AI-driven systems like John Deere's See & Spray have optimized chemical usage, saving approximately 117 million liters of solution in the 2025 season. Meanwhile, startups like Carbon Robotics are deploying laser-based weeding robots, and specialized platforms like GRIT are assisting in humanitarian demining efforts by integrating environmental and geological data.
Geological exploration is benefiting from quantum sensors, such as gravimeters and diamond magnetometers, which detect subtle changes in magnetic and gravitational fields. Companies like Atomionics and Nomad Atomics are integrating these sensors with AI to improve mineral discovery and groundwater monitoring, with significant backing from major mining firms.
Research into biological processes, such as nitrogen fixation by the FeMoco enzyme, is being accelerated by advanced computing models. Additionally, new satellite projects like FireSat, supported by Google Research, utilize AI to monitor wildfires by analyzing real-time imagery against historical data.
