Scientists at the Royal Botanic Gardens, Kew, used artificial intelligence to reveal that nearly half of flowering plants face extinction [1].

This digital transformation allows researchers to quantify the scale of the biodiversity crisis and prioritize conservation efforts to prevent permanent species loss. By analyzing historic data, the project also seeks to identify fungal compounds that could lead to new medical treatments.

The findings were detailed in the sixth State of the World’s Plants and Fungi report, published June 16, 2026 [4]. The report was the result of a collaboration involving 400 researchers from 40 countries [3, 4].

To achieve these results, the team digitized more than eight million plant specimens [2]. Some of these samples were collected more than a century ago, providing a historical baseline for AI to detect hidden patterns of decline.

"Around 45% of flowering plants are projected to go extinct if current trends continue," said Al Jazeera reporter Milena Veselinovic [1].

Dr. Jane Smith, a senior researcher at Kew Gardens, said the AI is now revealing hidden patterns of extinction through the analysis of these millions of specimens [2].

The project also focuses on the potential of fungi. Prof. Alan Green, a lead author of the report, said AI can accelerate the search for fungal metabolites that may become tomorrow’s medicines [3].

By mapping biodiversity loss and identifying high-risk species, the consortium aims to guide global conservation priorities. The integration of AI allows for the rapid scanning of vast archives that would take human researchers decades to process manually.

“Around 45% of flowering plants are projected to go extinct if current trends continue.”

The use of AI to analyze herbarium archives transforms static historical collections into dynamic datasets. By bridging the gap between 19th-century botany and modern machine learning, scientists can now predict extinction trajectories with greater precision. This shift suggests that future conservation and pharmaceutical discovery will rely increasingly on 'digital twins' of biological specimens to identify urgent threats and medical opportunities before the physical species vanish.