The challenging nature of urbanism requires us to think differently about how we plan and manage cities to address multiple aspects (infrastructure, environment, social, etc.). This chapter introduces a novel framework called the AI building blocks framework (ABBF), which aids the incremental, AI-driven development of smart cities and consists of modular building blocks. The framework consists of four interlocking layers: data infrastructure (IoT sensors and open standards), analytical intelligence (predictive algorithms and digital twins), applications (smart mobility and climate resilience), and governance (participatory platforms and equity audits). This allows cities to offer tailor-made solutions to citizens while maintaining systemic coherence. Examples of successful implementations in Barcelona and Singapore illustrate this potential and show how innovative management can reduce traffic congestion, optimize energy use, and enhance climate resilience. However, challenges such as data privacy, funding gaps, and algorithmic bias must be managed proactively. The framework recommends a phased implementation process of piloting, scaling, and institutionalizing to balance innovation with sustainability. Looking ahead, generative AI, the rise in blockchain, and the international alignment of global policy will continue to shape the conversation, but the barriers of a digital divide and institutional inertia challenge the rationale for success. The ABBF does not treat AI simply as a technology to be harnessed but rather views it as a driver of adaptive, inclusive, and sustainable urban ecosystems.