Conventional weed management relies on selective herbicides, biological control and allelopathy but faces limits from herbicide resistance, labour decline and climate change. Rapid advances in AI, UAVs, cameras and sensors drive Smart Weed Management (SWM) to map and target weed variability, cutting herbicide use and labour costs. SWM integrates organic bioherbicides, judicious organic or inorganic fertilizers and practices like alternate wetting and drying to reduce emissions and earn carbon credits. Computing, robotics and big data enhance precision control and decision making. Education of future weed scientists and farmer behaviour change are critical for adoption. Policy support, extension and research collaboration are needed to scale SWM. Together, conventional and smart methods offer resilient, low input weed control for diverse countries.