LeadingAge 2025: How Senior Care Organizations Are Evolving With AI

A Growing Understanding of AI in Senior Care

In one session, Scott Code, vice president of the Center for Aging Services Technologies at LeadingAge, shared some learnings from a CTO Hotline survey released earlier this year.

At the enterprise level, no organizations cited extensive AI competency, with most respondents sharing that they either have very limited AI knowledge or have certain team members with AI competency. (Only 49% of respondents felt somewhat confident to deploy some targeted AI.)

There is strong adoption of large language models, with Microsoft Copilot emerging as the leading industry solution: 63% of respondents use Copilot, while 36% use ChatGPT, 3% use Google Gemini and 1% use Claude. (For respondents who were currently not using an LLM, 53% are planning to implement one in the next 12 months.)

Joe Velderman, chief strategy officer at K4Connect and a board member of the Parker Health Group, shared that his interest in generative AI began around the time that ChatGPT launched to the public in late 2022. As he started his research, he grew to understand the importance of data to such solutions.

“Data is the fuel for these LLMs, and so, I started thinking about how necessary it was going to be for organizations to use and leverage data in order to effectively and contextually take advantage of these tools,” he said.

From left: Joe Velderman, Chief Strategy Officer at K4Connect, speaks during a session with Robin Visser, Director of Marketing and Digital Strategies at Christian Living Communities; Srini Alagarsamy, CTO of Lifespace Communities; and Scott Code, Vice President of the Center for Aging Services Technologies at LeadingAge. Photo by Teta Alim

A Discussion With ChatGPT

In an earlier session, human panelists included ChatGPT in their presentation and Q&A time with the audience. Travis Gleinig, vice president of innovation and CIO at United Methodist Communities, said the chatbot had been prompted to do a 15-minute research session into leading industry reports, data and other resources to give context to the panel.

As AI becomes more entrenched in the industry, Gleinig said, his organization is focused on culture change to get people to understand AI better.

“There’s a big difference between literacy and fluency,” he said, adding that he would like team members to become AI fluent so they could easily adopt and understand whatever solution the market lands on.

As part of new employee onboarding, Gleinig has explored using Google NotebookLM to create a sort of podcast on the organization’s history and culture, which he found to be much more engaging than traditional approaches.

At Presbyterian Living, Vice President of IT Raymond Benegas said that AI is used in clinical, sales and marketing workflows. Employees have also been testing the use of Microsoft Copilot, and cybersecurity platforms include AI features that have improved visibility and response for the organization, such as quickly noticing unusual login activity.

“We would not have caught that as quickly without these types of AI solutions really looking at the data all of the time and just giving us the information that we need to act,” Benegas said.

From left: Raymond Benegas, Vice President of IT at Presbyterian Living; Travis Gleinig, Vice President of Innovation and CIO at United Methodist Communities; and Steven VanderVelde, Director of Senior Living Partnerships at ProviNET Solutions, share the stage with a fourth panelist: ChatGPT. Photo by Teta Alim

When asked about the negative aspects of AI adoption and what organizations can do to protect themselves, the answer that ChatGPT generated focused on human oversight and bias concerns: “One example of the dark side is if AI is used to automate decisions that really need human empathy. For instance, relying too heavily on AI for resident care plans without enough human oversight could lead to decisions that miss the nuances of personal care. Another risk is data privacy: If AI tools aren’t well protected, there’s a chance of exposing sensitive resident information. And lastly, there could be bias in AI if it’s trained on data that doesn’t represent the resident population well. The best protection is always to keep a human in the loop, ensure strong data safeguards, and regularly review AI outputs for fairness and accuracy.”

The human panelists also emphasized the importance of data governance and ongoing training and education as AI-assisted phishing attempts become a growing threat across industries.

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