The digital era has transformed political marketing through the collaboration of social media, big data, and artificial intelligence (AI), each of which offers complementary roles in shaping campaign strategies. This study investigates how these technologies are reconfiguring political communication by enabling data-driven, emotionally resonant, and personalised interactions between candidates and voters. The analysis is theoretically grounded in Political Market-Oriented Theory, which explains the strategic adaptation of political actors to voter demands; affective publics, which highlights how emotional expression and virality shape engagement in digital platforms; and surveillance capitalism, which frames the commodification of personal data and algorithmic control within political messaging practices. Using a qualitative analytical bibliometric approach, the study employs three main tools: VOSviewer for keyword co-occurrence analysis, R Studio for conceptual structure and thematic evolution mapping, and CiteSpace for co-citation clustering and timeline visualisation. The dataset consists of Scopus-indexed journal articles from 2015 to 2024 and is included in the open access. The study places a particular focus on non-Western democracies, with Indonesia as a case study, to highlight contextual challenges such as digital inequality and low digital literacy. The findings highlight strategic benefits such as targeted messaging, voter segmentation, and real-time feedback. However, they also raise ethical issues, including algorithmic bias, digital surveillance, and the threat of misinformation to democratic integrity. This study contributes to closing the literature gap on AI-based political marketing in emerging democracies and proposes normative guidelines for the ethical, inclusive, and transparent use of digital technologies in political campaigns.