<p>In the era of artificial intelligence (AI), numerous geographical issues require interdisciplinary approaches and theories. As the demand for cross-disciplinary problem-solving increases, human geography, which addresses challenges from a spatial perspective, faces methodological challenges in maintaining its distinctiveness. Scholars often approach urban, economic, and sociocultural issues within human geography through the lens of its subfields, resulting in a gradual decline in the recognition of human geography as an integrated discipline. This paper seeks to review the development and research methodologies of human geography systematically and, in response to the needs of interdisciplinary research, proposes the Space–Scene–Scenario (3S) research framework. This framework integrates dimensional and scalar thinking approaches within human geography, offering a comprehensive pathway—from identifying research starting points to uncovering research objectives—to analyze societal problems from a human geography perspective. Moreover, it is designed to adapt to the societal transformations and technological impacts brought about by AI. The flexibility and inclusiveness of the 3S framework not only enhance the distinctiveness of human geography as a discipline but also promote a holistic and integrative research approach that thereby transcends traditional subfield boundaries. Additionally, through the integration of theory and practice, this paper demonstrates how the 3S framework functions as a versatile tool for investigating spatial inequalities. Its ultimate aim is to guide human geographers in enriching the theoretical system of human geography while affirming their discipline’s value in the context of the AI era.</p>