The transportation sector is a significant contributor to global greenhouse gas (GHG) emissions. It is estimated that replacing fossil fuel-based vehicles with electric vehicles (EVs) powered by sustainable and renewable energy could contribute to approximately 21% of emission avoidance by 2050. To improve the efficiency of EV operation, various artificial intelligence (AI) technologies have been applied. Examples include charging system optimization, self-driving car technology, and traffic control technology. To understand the current readiness status of those technologies applications, a small database of AI use in EVs that is in practice globally is constructed. There are 23 locations of prototype projects identified. The projects are categorized by the AI type, developer type, size of operation, and readiness status. Readiness status is analysed with the Japan Technology Readiness Assessment (J-TRA) methodology. There are seven analysed parameters: 1) Market, 2) Technology development, 3) System Integration, 4) Sustainability Verification, 5) Safety, 6) Commercialization and 7) Cost and Risk. The results show that while there is a promising market, steady progress in technological development, and verified environmental benefits, more work is needed to ensure safety and integration with the current systems before the technology can reach higher readiness levels of commercialization, cost, and risk-coping mechanisms.