Mikkel

AI is being used to monitor and model our environment with incredible precision.

We're talking about satellite imagery, sensor data, ocean currents, deforestation maps, glacier tracking.

AI can analyze it all in real time.

Farmers are using AI-driven weather models and soil analysis to optimize crop yield and reduce water use.

Even NASA relies on AI to model climate features and track polar ice melt.

Let's talk about infrastructure.

AI is powering smart grids and smart cities.

These systems use real-time data to make energy distribution more efficient.

Google's DeepMind even reduced cooling costs in data centers by over 30% using AI optimization.

Imagine if every factory or office applied the same logic.

All of this can even lower emissions drastically, but again, it depends on implementation and political will.

Language models like GPT or image generators require massive computation.

That energy isn't always renewable.

So while AI might be helping industries go green, its own operations aren't even carbon neutral yet.

The good news?

There's also the rise of tiny AI.

Smaller, efficient modules that run on less energy but still solve real problems.

AI tools could help farmers in Africa predict droughts, or coastal cities in Asia adapt to rising seas, but only if they get access.

That's why international collaboration, open source models, and affordable AI access are critical.

Governments and NGOs use machine learning to simulate climate futures, test out policies, and plant disaster responses.