A new global study using artificial intelligence analyses digital plant records to assess how climate change affects flowering. Researchers examined about eight million digitised plant specimens collected over roughly the past century. Using AI, they identify shifts in the timing of flowering across many species and locations. The findings indicate flowering dates move by an average of about 2.5 days earlier or later for each decade, suggesting that warming and other climate-related factors are affecting plant seasonal cycles. The study reports that these changes vary over time and across regions rather than following a single uniform pattern. By drawing on a large historical dataset, the approach aims to detect long-term trends that may not be visible from shorter-term field observations. The results contribute to understanding how ecosystems may respond to ongoing climate pressures, including potential impacts on pollinators and food webs that depend on synchronized seasonal timing.