Smart grids (SG) transform a traditional electricity energy grid by incorporating many emergingdisruptive technologies to produce clean, efficient, and dependable energy. This review focusesexclusively on one instance of AI application in SG - predictive analytics. We conducted asystematic literature review on AI applications in SG, which resulted in a review of 18 articlespublished after 2015. In the first part of the review, it is concluded that integrating AI into SGcould address many challenges in SGs and transform traditional grids. The second part focuseson the predictive analytic capability enabled through AI in SG. Predictive analytics can be appliedin many contexts to optimize decision-making, diagnose faults, and enhance grid stability. Thelast part presents two use cases for AI-enabled predictive analytics: energy outage prediction andsecurity enhancement. AI, especially the predictive analytic technique, is a future avenue for SGenhancement. The main conclusion from the review is that more research describing empiricalexamples of the adoption and deployment of AI predictive analytics in SG is needed.