Governance and Coordination of AI in Urban Development Projects: Evidence from China and Kazakhstan

Governance and coordination arrangements critically shape whether artificial intelligence (AI) functions as an operational decision-support instrument or remains an analytical add-on in smart-green urban development projects. Drawing on a mixed methods study that combines an online survey and semi-structured expert interviews, this study examines urban project practices in China and Kazakhstan as contrasting contexts that pursue similar digitalisation and sustainability agendas, yet demonstrate divergent implementation trajectories. AI is conceptualised as a governance-dependent operational parameter embedded within project workflows rather than an autonomous technological driver. Findings indicate that although digital and AI-based tools are present in both countries, their capacity to influence planning, approval, and monitoring processes depends on governance conditions, particularly cross-stage coordination, formally assigned process ownership, and institutionalised feedback and learning mechanisms. In China, structured co-ordination systems and digital accountability frameworks support AI as a predictive and evaluative governance tool, whereas in Kazakhstan, fragmented responsibilities and weak procedural integration largely confine AI to advisory or representational roles. The Adaptive Filter is proposed as an analytical lens for interpreting governance-technology compatibility, while the Adaptive Pilot Governance Cell (APGC) is outlined as a conceptual implication derived from the empirical analysis. The findings suggest that governance maturity, rather than technological availability, determines whether AI becomes operational within project decision-making processes.