As electric vehicle (EV) adoption continues to accelerate – the US achieved a 5% all-electric sales share in Q2 2022 – utilities and planners are shifting their focus from understanding simply when and how many EVs will be adopted to also forecasting where they will be adopted. This presentation draws from forecasts developed for two utilities serving a total of 4.7 million electric customers. The results are based on the deployment of a powerful agent-based EV adoption forecast model that integrates consumer preference data with neighborhood-level demographic data to simulate probabilistic EV adoption behavior across residential populations. The forecast provides geographically granular EV adoption data to support load forecasting, system planning, targeted education and marketing, and strategic charging network buildout to serve underserved communities. The model utilizes two key inputs: survey-captured customer attitudes and preferences toward EVs, including stated EV purchase likelihoods, as well as a synthetic population of the consumers, vehicles, and households in a region derived from publicly available data. Model simulations incorporate the granular demographic and peer effects that drive EV adoption behavior and capture how customers evolve, act, and interact over time. The emergent EV adoption behavior of the system is driven by probabilistic decision-making, peer influence parameters, and local attitudes toward EVs, which vary across several demographic attributes. We will highlight how key differences in customer attitude/preference survey responses drive differences in forecasted adoption and discuss implications for utilities’ system planning and EV program efforts. We will also outline the survey instrument, synthetic population development process, and iterative forecast tuning process, highlighting how this approach supports a replicable adoption forecasting framework. This presentation – based on successful deployments of this innovative EV adoption model at major utilities – will be relevant to regulators, program managers, utility system planners, and EV charging system operators, among others.