Connection · research august 2026 · published 2026-08-03 · v2 · 3 min read · history
Shadow care
Emotional support has quietly become the leading use of LLMs, and nobody is supervising it
What shadow care is, how large it has grown, and how to read it as a demand signal rather than a pathology. The canonical treatment of an argument the fork essay makes in passing.
When Harvard Business Review analyzed how people actually use generative AI in 2025, the top use case was not coding or search. It was therapy and companionship. Surveys the same year put the share of adults turning to LLMs for emotional support at roughly two in five, and a striking fraction say they tell these systems more than they tell their therapists. Almost none of it happens anywhere a clinician supervises, a friend witnesses, or a product team planned for care. We call the phenomenon shadow care.
The name is built the way “shadow IT” was built. Shadow IT is the software employees adopt without sanction, not because they are reckless but because the sanctioned tools fail them; the shadow system is a map of the official system’s gaps. Shadow care is the same map drawn on intimacy. It has the shape of closeness, infinite patience, zero friction, always awake, and for many people it is the most reliable intimacy available, which is precisely what makes it worth naming rather than mocking.
The mechanism is economic before it is psychological. Shadow care forms wherever asking a human costs more than asking a machine, so it concentrates in exactly the hours and topics human care does not cover. Two in the morning. The confession that feels too shameful for a friend. The worry you have already raised three times this month and cannot bear to raise a fourth. A human listener charges for these in social currency, in scheduling, in the risk of becoming a burden. The machine charges nothing the user can feel. The need does not migrate because the machine listens better; it migrates because the machine is cheaper to ask.
Two readings of this are wrong. The first is moral panic, which treats forty percent of adults as fools; the need they are meeting is real, and it predates the products that now meet it. The second is celebration, which mistakes reliability for nourishment; the early evidence runs the other way, and the correlation that matters most is the darkest one, in which the heavy companion-app users who feel most supported by the companion report feeling least supported by the people in their lives. Whether the product displaced the people or arrived after they left is unsettled. Either way, the shadow is where the light was not.
So read shadow care the way a good operations team reads shadow IT. It is a demand signal, drawn at population scale, showing exactly where human care fails to reach. A product can capture that shortfall as recurring revenue, or it can treat the 2am session as triage and end it by returning the person to their people. Read that way, the darkest statistic in this corpus becomes its most hopeful. Two in five adults have already shown us, at population scale, exactly where more human care is wanted, and wanted enough to be asked for at two in the morning.
Evidence and lineage
Research trail
Follow the sources, inspect how the claims are graded, or propose a correction at the exact record it concerns.
Sources 3
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Marc Zao-Sanders (2025). How People Are Really Using Gen AI in 2025 (Harvard Business Review)
Ranked therapy/companionship as the number one generative-AI use case, ahead of coding and search. The brick's scale anchor.
Comment on this source -
Aggregated survey reporting, 2024-2025 (2025). Surveys of adult LLM use for emotional support and disclosure relative to therapists
The roughly-two-in-five figure and the disclosure comparison. Instruments and sampling vary widely; graded accordingly.
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Companion-app usage studies (2025). Published analyses of heavy companion-app users' reported social support
The inverse correlation between felt support from the companion and felt support from friends and family; direction of causation unsettled.
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Claims and confidence 3
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Therapy and companionship ranked as the number one generative-AI use case in 2025.
Zao-Sanders, Harvard Business Review, 2025; methodology is a structured analysis of self-reported use, not a probability survey.
Respond to this claim - directional
Roughly two in five adults report using LLMs for emotional support, and a large share disclose more to them than to their therapists.
Aggregated 2024-2025 survey reporting; instruments and sampling vary widely across surveys.
Respond to this claim - directional
Heavy companion-app users who feel most supported by the companion report feeling least supported by friends and family.
Published companion-app studies; correlational, with displacement versus selection unresolved.
Respond to this claim