The purpose of this paper is to highlight the issues of landslide disaster risk reduction in India by presenting real case studies of landslide incidences happened in the past. It also focuses upon the resilience measures and policies required for reducing landslide risk. This study highlights and give insight on the few important case studies of past landslides/mass-movement incidences such as Phuktal landslide dammed reservoir, Kargil-Ladakh (2015), Idukki-Kerala (2018), landslide at Noney district-Manipur (2022), Rock-ice avalanche and debris flow, Chamoli (2021), land subsidence in Joshimath-Uttarakhand (2022), South Lhonak Glacial Lake Outburst Floods-Sikkim (2023) etc. These disaster events are influenced by the intrinsic factors (i.e., geo-tectonic, drainage/hydrology, land uses) and extrinsic factors (i.e., climate change, anthropogenic activities, climate variability, natural and socio-economic development). The landslide disaster events induced by geo-tectonics, heavy rainfall, Glacial Lake Outburst Floods (GLOFs), anthropogenic activities etc. have been causing severe losses and damages to lives and properties in different regions of India. The extreme weather events and climate change increases the frequency of disaster events in hilly regions of India. As a result, the necessity for stringent policies and strategies (e.g., landuse, construction practices, enact/revise regulations etc.) for reducing disaster risks was extremely felt. Simultaneously, the advancement of innovative technology and tools such as Deep Learning (DL), data mining, Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IOT) are required to generate reliable, field validated models of multi-hazards based early warning, risk assessment, mitigation, response etc., which may reduce impacts of future disasters and its occurrences.