Traditional drug discovery is immensely time-consuming, taking 3-6 years for pre-clinical trials and costing millions of dollars. The industry is being reshaped in terms of speed and economy, with over 55% of US startups incorporating AI in the drug discovery process. Harnessing the power of AI has enabled scientists to analyze massive datasets of chemical compounds using high-throughput screening. AI is also used to identify drugs and their interactions with various biological pathways, reveal potential applications for treating different diseases, and tailor treatments for personalized medicine. The need for physical testing of candidate drug compounds has also reduced since then. 'High-fidelity molecular simulations', which use machine learning, can create complex simulations of biological processes and disease mechanisms, allowing for more accurate predictions of drug behavior and potential side effects. The United States leads in AI-led discovery with 55% of firms, followed by Europe and the United Kingdom with shares of 20% and 10%, respectively. Meanwhile, China and Australia fall below the 5% mark for drug development start-ups using AI. There has been a rise in AI investors in the USA, EU, and UK, making these regions leaders in AI-led drug discovery.