From anxiety to reassurance: How AI is quietly supporting pregnancy wellbeing

New research suggests artificial intelligence (AI) is playing an major role in how pregnant women cope with anxiety, uncertainty, and emotional strain. Unlike traditional digital health tools, this use is informal, self-directed, and largely invisible to clinicians and policymakers.

That emerging pattern is examined in AI as Emotional Support in Pregnancy: A Review and Synthesis for Emerging Research Directions, a study published in Social Sciences, which reviews existing literature and finds that AI is increasingly used as an emotional companion rather than a medical aid during pregnancy.

Beyond medical monitoring: How AI is filling emotional gaps in pregnancy

Pregnancy has long been recognized as a period of increased emotional intensity, shaped by physical changes, shifting identities, social expectations, and uncertainty about health outcomes. While medical care during pregnancy has expanded significantly, emotional support remains unevenly distributed, particularly for those facing social isolation, limited healthcare access, or systemic barriers.

The study finds that most existing AI research in maternal health focuses narrowly on clinical objectives such as risk prediction, symptom monitoring, and mental health screening. These applications are typically designed for healthcare providers or embedded within structured clinical workflows. By contrast, everyday emotional experiences during pregnancy, such as anxiety, fear, ambivalence, loneliness, and the need for reassurance, have received far less attention.

According to the authors, this gap is increasingly being filled by general-purpose AI tools. Rather than relying solely on family members, clinicians, or peer groups, pregnant people are turning to AI systems that offer constant availability, anonymity, and non-judgmental interaction. These systems are not replacing medical care but are being used to process emotions, validate concerns, and make sense of bodily and psychological changes as they occur.

The review highlights that emotional support during pregnancy is not limited to clinical mental health conditions. Many pregnant people experience distress that does not meet diagnostic thresholds but still affects wellbeing and daily functioning. The study suggests that AI is particularly attractive in these moments, when individuals may hesitate to seek professional help or feel their concerns are too minor, confusing, or repetitive to share with others.

Importantly, the authors note that AI use in this context is often self-directed. People engage with AI outside institutional oversight, shaping interactions based on personal needs rather than predefined program goals. This organic use distinguishes AI-supported emotional care from traditional digital health interventions and complicates existing frameworks for evaluation and regulation.

Generative AI and the shift toward everyday emotional support

The study focuses on generative AI, particularly conversational systems capable of sustained interaction. While earlier maternal health technologies emphasized information delivery and monitoring, generative AI enables dynamic dialogue, emotional framing, and personalized responses. This shift allows users to explore feelings, ask open-ended questions, and receive immediate feedback without fear of stigma.

The authors identify a clear research gap around how pregnant people use these systems in practice. Existing studies largely examine purpose-built chatbots designed for education or screening, often tested in controlled environments with specific outcomes in mind. By contrast, little is known about how people use widely available AI platforms in their daily lives to cope with emotional strain.

The review suggests that AI is not simply being used as an information source but as a co-constructive emotional tool. Users engage in back-and-forth exchanges that help them reframe experiences, articulate fears, and regulate emotions. In this sense, AI becomes part of an informal emotional ecosystem, complementing but not replacing human relationships.

The study also emphasizes that pregnancy-related emotional needs are fluid and context-dependent. Feelings may shift rapidly in response to bodily sensations, medical appointments, social interactions, or life events. AI’s immediacy allows users to seek support at the moment distress arises, rather than waiting for scheduled appointments or availability of others.

However, the authors warn that the apparent neutrality and responsiveness of AI can create a sense of emotional safety that masks important limitations. AI systems do not possess lived experience, accountability, or the ability to provide material support. Without careful understanding, there is a risk that AI-supported emotional care could be misunderstood as equivalent to human support or professional guidance.

Equity, ethics, and the risk of invisible dependence

The authors note that emotional support during pregnancy is unevenly distributed across social groups. Immigrants, women of color, low-income individuals, and those living in rural or underserved areas often face barriers to consistent emotional care, including limited access to healthcare providers, language barriers, and social isolation.

The review suggests that these groups may be more likely to rely on AI for emotional support, given its accessibility and low cost. Yet they are also underrepresented in existing research on AI use in pregnancy. This imbalance raises concerns about whose experiences are shaping the development and evaluation of AI tools in maternal contexts.

The authors warn that without equity-focused research, AI-supported emotional care risks reinforcing existing disparities. If AI systems are trained on narrow datasets or designed without attention to cultural and social diversity, they may fail to address the needs of those most reliant on them. Worse, they could unintentionally reproduce biases or offer guidance that is misaligned with users’ lived realities.

The study also raises ethical questions about emotional reliance on AI. While AI can provide immediate reassurance, it lacks the capacity to recognize when a user’s distress signals deeper risk or requires human intervention. The authors stress that AI-supported emotional care should not become a substitute for structural investment in maternal health services or social support networks.

Another ethical concern involves the privatization of emotional care. As people turn to commercial AI platforms for support, intimate emotional experiences become entangled with data collection and corporate interests. The study highlights the need for transparency, safeguards, and clear boundaries around how emotional interactions are handled, stored, and potentially monetized.

AI-supported emotional care is already happening, often quietly and without formal recognition. The challenge, they suggest, is to understand it rigorously and shape it responsibly.

Rethinking maternal health in the age of AI

The study calls for a broader rethinking of how maternal health is conceptualized in AI research and policy. Rather than treating emotional support as a secondary or optional concern, the authors argue that it should be recognized as a central component of wellbeing during pregnancy.

They call for future research that centers the lived experiences of pregnant people, particularly those from marginalized communities, and that examines how AI is used across different cultural, social, and healthcare contexts. Longitudinal studies, qualitative methods, and participatory research approaches are identified as key tools for capturing the complexity of AI-supported emotional care.

Interdisciplinary collaboration is equally important. Understanding AI’s role in pregnancy requires insights from social science, ethics, public health, and human-computer interaction, not just technical development. Without this broader perspective, AI tools risk being designed for idealized users rather than real-world conditions.