This study develops an entrepreneurial marketing framework to facilitate the adoption of decentralized artificial intelligence (AI) and blockchain technologies in environmentally sustainable smart buildings. Employing Corbin and Strauss’s grounded theory approach, data were collected through semi-structured interviews with 18 experts from academia, industry, and digital technology sectors until theoretical saturation was reached. Data analysis, performed via open, axial, and selective coding, identified six core categories: causal conditions (e.g., transparency, sustainability demands, and green branding), contextual conditions (e.g., digital infrastructure and government support), intervening conditions (e.g., high costs and expertise shortages), strategies (e.g., personalized AI campaigns, blockchain smart contracts, stakeholder education, and interactive platforms), consequences (e.g., reduced carbon footprint, enhanced trust, and competitive advantage), and the central phenomenon (the entrepreneurial marketing framework itself). The proposed framework integrates AI-driven personalization with blockchain-enabled transparency to build stakeholder trust, improve operational efficiency, and accelerate technology adoption in sustainable construction. Findings offer practical recommendations for policymakers and industry practitioners aiming to promote green smart buildings. This research bridges the gap between technology innovation and marketing strategy in the built environment.