Conversational artificial intelligence (AI) has advanced rapidly in recent years, with large language models now able to generate fluent and contextually appropriate text across a wide range of domains. Despite this progress, such systems continue to lack the ability to understand and produce the subtle, socially embedded meanings that shape human interaction, resulting in interactions that may appear insensitive or socially inappropriate.
This presentation argues that human-AI fit is essential for ensuring effective and empathetic interactions between users and AI systems. Building on the definition by Sun, Sheng & Zheng (2023), human-AI fit refers to “whether AI can experience the emotions of humans and provide emotional support in an empathy [sic] way” (p.1). Such alignment is particularly important in emotionally sensitive domains such as healthcare, debt or customer service. It is also crucial for interaction with vulnerable users, such as individuals with neurodiverse conditions. For these contexts, conversational systems must address users’ emotional needs – a principle conceptualised by Shores et al (2025) as ‘emotional access to digital systems’.
To ensure conversational systems meet the diverse needs of users and align more closely with human social expectations and emotional needs, we propose a set of design principles grounded in the concept of sociopragmatic competence. As defined by Kasper and Rose (2002), sociopragmatic competence is the ability to perform and interpret social actions appropriately by considering contextual factors. We also include in our approach insights from interactional sociolinguistics (Gumperz 1982), including key concepts such as politeness and accommodation, which illuminate how users’ interpretative frames shape their interpretation of meaning. Whilst other branches of pragmatics, for example conversation analysis, sociopragmatics offers a complementary perspective that emphasises the social and contextual dimensions of meaning-making.

References
Gumperz, J. (1982). Discourse Strategies. Cambridge: Cambridge University Press.
Kasper, G., & Rose, K. (2001). Pragmatics in language teaching. Cambridge: Cambridge University Press.
Sun, Y., Shen, X, & Zhang, K. (2023). Human-AI interaction. Data and Information Management 7(3). https://doi.org/10.1016/j.dim.2023.100048.
Shores, T., Robertson Nogues, A., Haque, L., Fernyhough, C., Gilroy, S., & Tennent, D., (2025). The right to emotional access in digital systems.
https://doi.org/10.17863/CAM.121111