AI IQ—Can AI Save Nature?

By Isabella Aranda Garcia

The internet started off as a whisper, slowly gaining its voice. AI, on the other hand, started off singing opera. The AI revolution is advancing at rapid speed; companies are building massive data centers, new AI-related and AI-adjacent jobs are coming into existence, and AI is becoming a must-have tool to excel at any job. If you’re not already, it’s time to get comfortable with AI, and we’re here to help with this new series. You can thank us later.

AI risks to nature are no secret. Some large data centers can consume up to five million gallons of water daily, but the amount varies depending on facility size, location and cooling design. These centers can also place additional strain on the surrounding communities through pollution, rising utility costs and even land use. For the nature issue, that irony was not lost on us. So, we’re focusing on how AI can help conservation initiatives.

Problem:

Illegal logging and deforestation frequently occur in remote forests, where limited monitoring can make it difficult to intervene before significant damage occurs.

Solution:

AI-powered bioacoustic monitoring systems, like the Guardian 3 by the Rainforest Connection, listen for chainsaws, vehicles, gunshots and other threatening sounds. Once detected, it sends real-time alerts to rangers or local partners through its Companion app to stop illegal logging and animal poaching; plus, it can even detect forest fires. The Rainforest Connection works alongside tribes, villages and neighboring communities in the rainforests to help keep their lands safe, protect their crops and livelihoods, and preserve their cultural heritage. So far they have protected 750,000 hectares of rainforest and identified and monitored over 4,200+ species and 310 threatened species.

Problem:

Ocean plastic is difficult to track because debris moves with the currents, spreads out over huge areas, and is expensive to monitor manually.

Solution:

The Ocean Cleanup’s Automated Debris Imaging System (ADIS) can map GPS coordinates to where plastic is accumulating so cleanup teams can target high-density areas. These AI-powered cameras attach to vessels like ships and planes to detect and/or monitor plastic pollution at sea. This technology also identifies plastic pollution trends, and the goal is to make their data open source so everyone can access it.

Problem:

Climate change is real; heatwaves, heavy rainfalls, droughts and intense storms are becoming more frequent. Plus, climate patterns have become harder to predict in many regions.

Solution:

AI can analyze massive datasets to spot early warning signs humans or traditional models might miss. Models like Google’s WeatherNext 2 can produce 15-day global forecasts in under one minute. As a result, these models empower researchers to better predict downstream environmental crises from wildlife disease outbreaks to flash floods and agricultural droughts. If calibrated locally, AI forecasts could help farmers decide when and what to plant, according to The University of Chicago. For wildfires, Google, Earth Fire Alliance and two additional partners are developing FireSat, a constellation of satellites designed to detect fires as small as about five by five meters and update imagery every 20 minutes.

Problem:

One of conservation’s biggest obstacles is insufficient data.
It’s difficult to track species, monitor biodiversity and understand environmental change.

Solution:

With platforms like iNaturalist, users upload photos of plants, animals and fungi, and their Seek app uses AI to help identify the species. These observations contribute to a global database used by researchers and conservationists to track biodiversity. Users can start projects that encourage public participation, like a project launched on World Bee Day where users tracked pollinators across the world, contributing to 154,000+ observations and 10,735 species.

Addressing the Elephant in the room

Many data centers use large amounts of water and energy to run and cool their systems, raising environmental and public health concerns.

As AI infrastructure expands, systems that recycle cooling liquid could reduce data centers’ environmental impact. Two alternatives—often used together—are direct-to-chip and closed-loop cooling. Closed-loop systems circulate coolant through sealed pipes, where it absorbs heat and recirculates to eliminate internal water consumption. Direct-to-chip cooling sends coolant directly to high-heat components, like processors, rather than cooling the entire room. Several major operators say they are reducing cooling-related water use through these and other methods, including Microsoft and Oracle. Google, Meta, Equinix, Vantage Data Centers and Digital Realty have also announced initiatives. However, these changes do not eliminate data centers’ broader environmental impacts, including electricity use and construction.

This article was published in the July/August 2026 edition of Connect to Northern Westchester.