A method comprising: generating, at a vehicle, an artificial intelligence, AI, model specific to a context of an operation of the vehicle, the context including a location or a type of the location where the vehicle travels, the generating based on training data collected from one or more sensors of the vehicle while the vehicle was present at the location or the type of the location; in response to a detection that the vehicle is within a proximity to a road side unit, RSU, associated with the location or the type of the location or that the vehicle is within a proximity to an additional vehicle that is at least anticipated to be present at the location or the type of the location, causing an AI model transmission to the RSU or the additional vehicle or causing an AI model reception from the RSU or from the additional vehicle; and based on causing the AI model reception, causing deployment of an additional AI model in the vehicle to optimize the vehicle for the location or the type of the location, wherein causing the AI model transmission or causing the AI model reception is based on a detection that a bandwidth available to the road-side unit, the vehicle, or the additional vehicle transgresses a minimum bandwidth threshold, wherein the deploying of the transmitted AI model includes aggregating the AI model with the additional AI model corresponding to the AI model reception; and installing an AI learning application (110A, 110B) on the vehicle based on a detection that the AI learning application was previously provisioned on the RSU or the additional vehicle, the AI learning application configured to learn information about driving profiles, driving policies, or a driving environment relevant to a particular location or type of location. generating, at a vehicle, an artificial intelligence, AI, model specific to a context of an operation of the vehicle, the context including a location or a type of the location where the vehicle travels, the generating based on training data collected from one or more sensors of the vehicle while the vehicle was present at the location or the type of the location; in response to a detection that the vehicle is within a proximity to a road side unit, RSU, associated with the location or the type of the location or that the vehicle is within a proximity to an additional vehicle that is at least anticipated to be present at the location or the type of the location, causing an AI model transmission to the RSU or the additional vehicle or causing an AI model reception from the RSU or from the additional vehicle; and based on causing the AI model reception, causing deployment of an additional AI model in the vehicle to optimize the vehicle for the location or the type of the location, wherein causing the AI model transmission or causing the AI model reception is based on a detection that a bandwidth available to the road-side unit, the vehicle, or the additional vehicle transgresses a minimum bandwidth threshold, wherein the deploying of the transmitted AI model includes aggregating the AI model with the additional AI model corresponding to the AI model reception; and installing an AI learning application (110A, 110B) on the vehicle based on a detection that the AI learning application was previously provisioned on the RSU or the additional vehicle, the AI learning application configured to learn information about driving profiles, driving policies, or a driving environment relevant to a particular location or type of location.