  Chatbots are more and more prevalent in commercial and science contexts. They
help customers complain about a product or service or support them to find the
best travel deals. Other bots provide mental health support or help book
medical appointments. This paper argues that insights into users' language
ideologies and their rapport expectations can be used to inform the audience
design of the bot's language and interaction patterns and ensure equitable
access to the services provided by bots. The argument is underpinned by three
kinds of data: simulated user interactions with a chatbot facilitating health
appointment bookings, users' introspective comments on their interactions and
users' qualitative survey comments post engagement with the booking bot. In
closing, I will define audience design for conversational AI and discuss how
user-centred analyses of chatbot interactions and sociolinguistically informed
theoretical approaches, such as rapport management, can be used to support
audience design.
