Urban economies face growing vulnerability to systemic crises including pandemics, climate shocks, and financial disruptions. Conventional recovery models—often reactive and siloed—have proven insufficient, creating a resilience deficit. Artificial intelligence (AI) and predictive analytics are increasingly positioned as tools to strengthen anticipatory governance and adaptive planning. This paper reviews the evolution of the smart city paradigm and introduces the concept of “urban predictive intelligence,” which integrates real-time data and machine learning to forecast risks and guide interventions. Comparative case studies of Singapore, Amsterdam, Pune, and Barcelona demonstrate that AI can accelerate recovery, improve transparency, and foster equitable growth, though risks of bias, privacy breaches, and technocratic dominance persist. The study argues that AI functions best as a strategic enabler within inclusive, collaborative governance frameworks for resilient urban economies.