Skip to content
GCC AI Research

How AI is identifying millions of plant species in 'biodiversity revolution' to boost conservation - The National

The National · · Notable

Summary

AI technologies are being increasingly utilized to identify and classify millions of plant species globally, marking a significant advancement in biodiversity research. These systems leverage algorithms, often based on computer vision, to rapidly recognize and catalogue flora, a task traditionally requiring extensive human expertise and time. This accelerated identification process is crucial for providing comprehensive biodiversity assessments and supporting global conservation strategies. Why it matters: This application of AI offers powerful tools for environmental sustainability, a priority area for many nations, including those in the Middle East investing in technology-driven conservation efforts.

Get the weekly digest

Top AI stories from the GCC region, every week.

Related

AI in bloom: How MBZUAI graduate is helping preserve the world’s plants

MBZUAI ·

MBZUAI alumnus Kane Lindsay is using AI to digitize and analyze plant specimens at Kew Gardens, including handwritten notes and preserved plants dating back centuries. He developed an AI model to recognize handwriting (OCR) and extract phenotype data from plant images, and another to redact sensitive location data. This work began as an internship and evolved into a fully funded Ph.D. Why it matters: AI is accelerating the digitization and preservation of plant collections, making them more accessible to researchers and aiding in conservation efforts.

Fine-grained species recognition with MAviS: a new dataset, benchmark, and model

MBZUAI ·

MBZUAI researchers have developed MAviS, a new multimodal dataset, benchmark, and chatbot for fine-grained bird species recognition. MAviS includes images, audio, and text to help models identify subtle differences between species, especially rare and regional varieties. The related study was presented at EMNLP 2025 and selected as a "Senior Area Chair Highlight". Why it matters: This work addresses a key limitation in AI's ability to support biodiversity conservation and ecological monitoring in the region and globally.