From the perspective of synergistic adaptation between high-quality tourism development and ecological resilience, analyzing the interactive adaptation characteristics of these two systems is crucial for enhancing ecological governance efficiency and advancing regional sustainable development. This study selected 12 leagues and cities in Inner Mongolia Autonomous Region as the study area, integrated the concept of resilience, and constructed an evaluation index framework for assessing high-quality tourism development and ecological resilience. Using methods including the entropy weight method, an adaptability quantitative model, an obstacle degree model, and a grey correlation degree model, the study analyzed the spatio-temporal evolution characteristics of adaptation and its internal and external influencing factors from 2000 to 2023. The findings showed that: (1) Both the high-quality development level of the tourism industry and the level of ecological resilience improved continuously. From 2000 to 2018, the adaptation degree increased slowly with fluctuations. After 2019, it showed a trend of first decreasing and then increasing. The adaptation state shifted from marginal adaptation to primary adaptation. (2) In terms of overall spatial evolutionary trends, the adaptation degree showed an "east-high and west-low, north-high and south-low" pattern. From the local spatial evolution characteristics, Hulunbuir, Hohhot and Ordos showed the strongest adaptive development momentum. Baotou, Xilinguole, Chifeng, Tongliao, Ulanqab and Bayannur demonstrated moderate adaptation and development, while Wuhai, Alxa and Hinggan League lagged relatively behind. (3) Regarding internal driving factors, tourism product services, tourism innovation driven, innovation resilience, and recovery resilience were identified as key obstacles constraining adaptation. Among external environmental factors, temperature, precipitation, population urbanization rate, and government intervention showed relatively high correlation with adaptation. (4) The adaptation degree was jointly influenced by investment in eco-environmental governance, population urbanization rate, precipitation, the number of inbound tourists, and resource recycling capacity, with the effects of these factors displaying significant spatial heterogeneity.