Government agencies across the globe are leaning on new technologies to face the challenges of a growing demand for information and the expectation of real-time response and issue resolution from the public. With so many devices and applications accessing government websites, it is important to have a communication and interaction strategy to field requests coming from a multitude of internet-connected devices with the requirement to provide an accessible and multi-lingual experience.
Interactive chatbots offer a modern and accessible communication platform for cities and states to interact with the public. Using speech, vision, and text-based technologies, chatbots driven by cognitive services bridge the gap between human and machine interaction in a 24/7 online customer service environment while also gaining valuable insights. With customization and a user-centric approach, chatbots offer a variety of additional online communication channels such as Facebook Messenger, SMS, iMessage, and many social networks, all in an accessible and multi-lingual format.
Online chatbots for government can process service requests in large numbers, operate continuously, and help public agencies conduct business while reducing effort and lowering costs. The value of this innovation includes instant access to public information and documents without human intervention. Details on laws, regulations and public services are simplified through an interactive format and presented in a quick-access menu within a chat window to display correctly on screens of all sizes.
Issue resolution is the primary focus for Tallan’s chatbot development. The most effective chatbots used for government can answer common and relevant questions quickly and enable citizens to access digital records and file routine forms and information requests right from their phone, tablet, or PC. Additionally, chatbots can be used internally to handle common IT requests such as password changes along with accessing policies and procedures (see California). Chatbots can recognize user preferences based on recorded history and categorize subject matter to be adaptive to each user based on interactions by leveraging Artificial Intelligence (AI) and Machine Learning (ML) from previously untapped user interactions.