A family might spend weeks researching senior living communities, comparing care options, checking costs, and reading reviews. But when it comes time to choose where a parent will actually live, the decision often comes down to something that happens during a visit.
How does the staff interact with residents? Does the community feel like somewhere their parent would be comfortable? Can the people running it actually provide the care their family needs?
Increasingly, AI is helping families figure out which communities deserve that visit in the first place.
A new study from U.S. News & World Report offers one of the more interesting looks I've seen at how this process is changing. And the findings suggest that AI may have an enormous influence on senior living decisions, even when families have no intention of letting it make the final choice.
AI is already influencing which communities families consider
On November 4, U.S. News & World Report published a survey of more than 500 Americans actively researching senior living communities or recently involved in a move.
The findings are worth paying attention to:
- 70% reported using generative AI during their search.
- 82% of AI users said they would trust an AI recommendation enough to book a tour.
- 75% of respondents said they wouldn't make a final decision without checking an independent source.
- 40% identified personal interactions with residents and staff as the most influential part of the decision.
- 43% said a positive feeling during an in-person tour gave them the confidence to sign a residency agreement.
These are self-reported findings from a group already involved in senior living decisions. The 70% figure isn't representative of AI adoption among all Americans, and willingness to book a tour isn't the same as an actual AI-generated booking.
Still, the findings reveal an interesting division of responsibility.
Families appear increasingly comfortable using AI to investigate their options and identify communities worth visiting. But they still want independent confirmation and personal experience before making a decision with such significant consequences.
For senior living operators, that creates two distinct challenges: providing enough reliable information to be considered in the first place, and demonstrating during the visit that the community is actually right for the resident.
The shortlist may be the most important decision AI makes
Consider a family looking for memory care in the Cleveland area. They might be evaluating 20 or 30 communities across a reasonable geographic radius, each with different care levels, amenities, pricing arrangements, and approaches to supporting residents.
Visiting every community isn't realistic.
A capable AI assistant could help narrow the options based on the family's circumstances. Perhaps the parent requires a secure memory care environment, the family wants to remain within 30 minutes of home, and the budget needs to accommodate increasing levels of assistance over time.
The assistant might compare available services, research licensing and inspection information, identify communities with relevant care capabilities, and produce a manageable shortlist.
The family may eventually tour only three or four.
Whether or not AI makes the final decision, it has already influenced which communities have the opportunity to earn the family's trust.
This is an important distinction in the broader conversation about AI agents. We spend a lot of time discussing when AI will autonomously book services or complete transactions. But for consequential decisions like senior living, the more immediate influence may be determining which providers ever get serious consideration.
A community doesn't need an AI agent to sign a residency agreement for AI discovery to materially affect its ability to attract residents.
It needs to be among the communities the agent identifies as appropriate for the family's particular requirements.
The problem is that some of the most important information is difficult to find
The survey also exposes a weakness in AI-assisted senior living research.
Among respondents who felt able to evaluate the accuracy of AI-generated information, 51% reported encountering inaccuracies. The most frequently reported problems included misstated care levels and amenities, incorrect availability or wait times, and outdated pricing.
These were respondent-reported discrepancies, rather than errors independently verified by researchers. Nevertheless, the categories are important because they concern the information families need to decide whether a community is even worth visiting.
A community that offers assisted living but not memory care may be entirely unsuitable for a particular resident. A quoted monthly rate might exclude significant care-related charges. Availability information that's several months old may no longer reflect reality.
And a community operating multiple campuses may offer different services at each location.
These aren't minor details. They can determine whether a family should consider the community at all.
The problem is that much of this information is either missing from public websites, difficult to compare, or subject to frequent changes. Business descriptions often emphasize attractive amenities, compassionate staff, and quality of life, while providing less detail about the operational characteristics that distinguish one community from another.
Those descriptions can be useful, but they don't necessarily answer the family's more specific questions.
We've been working with Judson Senior Living to make more of this information accessible to AI systems. Judson's TrustRecord brings together detailed information about its communities, care offerings, operating history, and regulatory information, while distinguishing independently verified facts from information attested to by Judson itself.
In our early checks, we've seen ChatGPT, Google AI, and other systems retrieve and reference information from Judson's TrustRecord. That's encouraging, although observing a record being used doesn't establish that it caused a recommendation or improved the accuracy of every answer. The broader opportunity is to make the facts that determine whether a community is suitable easier for AI to find, interpret, and substantiate.
And in senior living, knowing when a community isn't the right fit can be just as important as knowing when it is.
What families learn during a tour is different from what AI can research beforehand
The other side of the U.S. News findings is equally interesting.
Despite the growing use of AI, personal interactions with residents and staff remained the most influential factor for 40% of respondents. And 43% cited a positive feeling during an on-site tour as the factor that gave them confidence to sign.
I don't think this is simply about people preferring a human connection, although that's certainly part of it.
A visit can produce entirely new information.
Families observe how staff interact with residents, how the community operates, and whether the environment seems appropriate for their parent's needs and personality. They can ask questions based on what they see, meet the people who would actually provide care, and hear how staff would approach their family's particular circumstances.
A care assessment may reveal requirements that weren't obvious from the initial search. A conversation might clarify what happens if the resident's needs change, how additional services are arranged, or whether a particular community can reasonably accommodate someone with complex needs.
Much of that information didn't exist when the family began researching.
This is a broader distinction I've been thinking about as personal AI agents become more capable. AI can increasingly investigate a provider's existing qualifications, experience, capabilities, and operating history. But some of the information that determines whether to hire that provider only emerges when the professional encounters the customer's actual situation.
Senior living is a particularly clear example because the decision combines objective requirements with personal preferences and professional assessment.
Of course, a good impression during a tour doesn't necessarily establish good care. Families should still examine licensing, inspection records, costs, and other relevant evidence. A polished presentation can be persuasive without telling the whole story.
The most informed decision combines what can be established beforehand with what the family learns firsthand.
What senior living communities should be doing differently
For operators, the implications go beyond trying to appear more frequently in ChatGPT recommendations.
The more useful question is whether an AI assistant has enough accurate information to determine when a community is appropriate for a particular family.
That means making care levels, location-specific capabilities, regulatory information, pricing structures, and important service limitations easier to understand. It also means distinguishing relatively stable information from facts that need confirmation, such as current availability or individualized care costs.
A family shouldn't have to schedule a tour simply to discover that a community doesn't offer the level of care their parent requires.
There is also an opportunity to make the eventual tour more productive. If families arrive already understanding the community's capabilities, services, and general pricing arrangements, they can spend more time discussing their parent's specific circumstances and evaluating the quality of the experience.
The U.S. News survey found that 52% of respondents considered clear pricing and fee structures a must-have on a community's website. That reinforces the importance of providing useful information before a family makes contact.
But operators should resist the temptation to publish overly precise figures that don't reflect how care is actually priced. If the final cost depends on an individual assessment, explaining that process clearly may be more useful than advertising a starting price that creates unrealistic expectations.
The same principle applies to capabilities and operating history. Information should be specific enough to help families compare options, with clear distinctions between documented facts, business-provided information, and details that require direct confirmation.
And none of this replaces the work that happens when a family walks through the doors. A detailed public record may help a community earn consideration, but the experience of residents, families, and staff ultimately has to support the expectations it creates.
AI doesn't need to make the final decision to change who gets chosen
I think the U.S. News study offers an important early look at how AI may influence high-stakes service decisions.
Families are willing to use AI to research communities, compare options, and identify places worth visiting. But they still want to verify important information and form their own judgments before making a commitment.
That combination makes sense.
Choosing a senior living community isn't merely a matter of matching a list of services to a set of requirements. It involves a person's health, independence, daily experience, and relationship with the people responsible for their care.
AI can help organize the research and potentially make the process considerably more informed. The family still has good reasons to want the final decision to remain personal.
For senior living operators, though, the commercial implications are already significant.
If a family considers 25 communities but tours only four, being among those four matters enormously. The family may ultimately choose based on the staff they meet, the care plan they discuss, and how comfortable they feel during the visit.
But the other 21 communities may never get that opportunity.
AI doesn't have to choose where someone's parent will live to have an enormous influence on which communities get the chance to welcome them.