ONGOING RESEARCH
Human–AI Companionship in Later Life
Connection, care and muluality in relationships with AI
Explores how older adults experience companionship and mutuality with AI, and how AI design and commercial practices shape caring, reciprocal relationships and well-being.
Research lead:
Xinni Zhang
Research Lead:
Key takeaway
AI systems are increasingly capable of interactions that can feel personal, caring and relational.
Features such as memory, personalisation, responsiveness and empathetic communication can contribute to feelings of being known, heard and cared for.
The research examines how relationships with AI can feel mutual despite being structurally different from human relationships, and what this may mean for well-being, autonomy and commercial influence.
Impact in practice
The findings could inform how AI companionship technologies are designed, marketed and governed, helping developers, service providers and policymakers support meaningful connection while protecting older adults’ autonomy, well-being and interests.
About the research
AI systems can now remember personal information, personalise conversations and respond in ways that feel caring and relational, creating new possibilities for companionship with AI.
Human–AI Companionship in Later Life examines how older adults experience and interpret these relationships, with particular attention to mutuality, how a relationship can feel reciprocal even though human and AI partners participate in fundamentally different ways.
Bringing together marketing, consumer research and human–computer interaction (HCI), the project also explores how AI design and commercial platforms shape these relational experiences and what they may mean for well-being and autonomy.
Why it matters
AI companions may create new opportunities for connection, engagement and support in later life. Features such as memory, personalisation, availability and empathetic responses can help people feel heard, understood and emotionally connected to AI.
However, human–AI relationships are structurally different from human relationships. AI can appear caring and reciprocal without having human needs, vulnerability or obligations of its own.
Understanding how older adults interpret this difference is important for assessing what AI companionship may mean for well-being, autonomy and meaningful connection. These relationships also take place within commercial platforms, raising further questions about how relational experiences may be shaped by engagement, subscriptions, personal data and other forms of monetisation.
Research focus
The project explores AI companionship through three interconnected areas:
Mutuality and companionship: How older adults experience and interpret mutuality in structurally asymmetric relationships with AI, including how they make sense of care, reciprocity, emotional connection and companionship.
Interaction and design: How features such as memory, personalisation, responsiveness, availability, conversational style and empathetic communication contribute to a sense that an AI knows, understands or cares about the user.
Commercial and well-being implications: How business models, marketing practices and firm interests shape these relational experiences, and what perceived mutuality may mean for well-being, autonomy, trust, disclosure, engagement and commercial influence.
Together, these areas examine AI companionship not simply as interaction with technology, but as an emerging form of relationship whose meaning, structure and commercial conditions may differ from those of human companionship.
How the research is being conducted
The project is developing a multi-study research design combining qualitative and potentially quantitative approaches.
The initial stage is expected to use in-depth qualitative research to understand how older adults experience and interpret relationships with AI: what makes interactions feel caring, reciprocal or companion-like, how these meanings develop through repeated interactions, and how users make sense of the differences between AI and human relationships.
The research will pay particular attention to the interaction and design features shaping perceived mutuality, including how AI communicates, remembers, personalises responses, initiates interaction and responds to users over time.
These findings will help identify important relational, interaction-design and commercial mechanisms for investigation in subsequent studies.
Meet the Researcher
Xinni Zhang
Xinni Zhang is a PhD candidate in the School of Economics, Finance and Marketing at RMIT University. Her research focuses on the intersection of marketing, human–computer interaction (HCI) and digital health, particularly technology adoption, digital inclusion and healthy ageing. She completed a Master's degree specialising in healthy ageing and digital health before joining RMIT.
Who the research is for
The research focuses on older adults who interact with AI platforms and recognises the diversity of later-life experiences, relationships and expectations of technology.
The findings will also be relevant to families, community and aged-care organisations, AI developers, HCI and interaction designers, technology companies, marketers, consumer advocates and policymakers.
Potential impact
Human–AI Companionship in Later Life aims to inform how AI companionship technologies are designed, marketed and governed.
The research may help AI developers and HCI designers understand how design choices shape perceptions of care, reciprocity and mutuality; support community and aged-care organisations in understanding the opportunities and challenges of AI companionship; and inform marketers, consumer advocates and policymakers about implications for autonomy, privacy, dependency and commercial influence.
More broadly, the project asks: what happens when AI can create a sense of mutuality without the reciprocal structure of human relationships, and how should such relationships be designed, marketed and governed?