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Home health and personal care leaders say AI tools can help with staffing, scheduling and documentation, but their benefits depend on employee adoption. A Home Health Care News survey found gaps in formal training and staff buy-in, while executives described time pressures, trust and concerns about work identity as obstacles.
Home-based care executives say AI projects can fall short when staff do not adopt the tools, prompting providers to focus on training, employee input and empathetic change management. A Home Health Care News report, drawing on a survey of 20 providers and interviews with industry leaders, describes time constraints, limited trust and concerns about professional identity as barriers to implementation.
The report says AI-based tools may help address staffing shortages, administrative work and scheduling difficulties in home-based care. But executives stressed that technical performance alone does not guarantee results: employees must incorporate the tools into their work. “The adoption of the solution didn’t actually happen,” said Greg Meyers, chief operating officer at TheKey, describing why some technology projects fail. He said strong change management is needed for projects to succeed.
In a recent HHCN pulse survey cited in the report, 73.3% of providers said they were exploring AI use cases, piloting tools or integrating them in select departments. The survey received responses from 20 providers. Forty percent said their organizations had no formal employee training for AI tools; 20% reported vendor-provided training and another 20% an internal training program. Respondents worked for organizations with one to 20 locations, and the survey included providers offering skilled home health and personal care.
Some providers are bringing frontline or departmental representatives into implementation early. Tribute Home Care defined “AI key users” from each department to help shape internally developed tools, according to Galip Gencer, the organization’s director of strategic planning and project management. Gencer said Tribute began by asking department leaders about their goals, then built tools to support those strategies rather than allowing technology to dictate the work. Survey respondents also identified phased rollouts and visible leadership support as common adoption approaches.
Staff Adoption Shapes AI Results
The findings matter to providers investing in AI because staff adoption can determine whether a tool changes day-to-day operations. A system intended to ease scheduling or documentation may add work at first, especially if employees have little time to learn it or the new process differs from familiar routines. The report does not establish that AI will resolve the sector’s staffing challenges; it shows that leaders view implementation and workforce support as conditions for realizing potential benefits.
For workers, adoption can also touch questions of trust, workload and professional identity. CommonSpirit Health at Home president and CEO Trisha Crissman said some staff were hesitant about ambient scribing and more accustomed to documenting on tablets than using conversational assessment dialogue. Her account suggests that changing a workflow may require more than a software rollout: employees need time, clear explanations and a chance to adapt.
The survey’s training figures point to a practical gap, though the small respondent pool limits how widely they can be applied. Providers that do not plan for training or an initial slowdown may face resistance when employees are already responsible for meeting workload targets. Leaders interviewed by HHCN described empathy and upskilling as ways to address those pressures, framing new tools as skills to learn rather than replacements for staff expertise.
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How Providers Are Introducing AI
Home-based care companies are considering AI for work such as staffing, scheduling and documentation. The HHCN pulse survey grouped together providers exploring possible uses, running pilots and integrating tools in selected departments; the 73.3% figure therefore does not mean that this share had fully deployed AI across their organizations.
The report’s examples show different stages and types of adoption. Tribute Home Care, which provides personal care and related services in four states, involved departmental users in the design and adoption of internal tools. CommonSpirit Health at Home, which operates home health, hospice, palliative care and infusion services across 15 states, encountered slower-than-expected uptake of ambient scribing. TheKey provides in-home care and skilled nursing services across 32 states and more than 110 locations.
Leaders also described an early productivity dip when employees learn a new system. TheKey chief people officer Emily Kraeter called this a “J” curve: productivity can decline after a tool is introduced, then rise above earlier levels as users become more familiar with it. She said leaders need to guide teams through that initial period. The report does not provide measured productivity results for the tools discussed.
“The adoption of the solution didn’t actually happen.”
— Greg Meyers, chief operating officer at TheKey
Adoption Outcomes Remain Unclear
The report does not quantify whether the AI tools described improved productivity, reduced administrative time or eased staffing pressures. Nor does it report how many employees ultimately adopted the tools, how long adoption took, or whether results differed across roles and organizations. The survey covered 20 providers, all with one to 20 locations, so its findings should not be treated as a complete picture of the home-based care industry.
The source also does not provide a breakdown of the survey’s results by tool type or explain how providers defined successful adoption. It reports that many respondents saw lack of staff trust or buy-in as a major gap, but does not establish the causes or prevalence of that concern across the wider sector. Whether training and phased implementation lead to sustained improvements remains to be measured.
Providers Face the Adoption Test
The report identifies no single next milestone or industry-wide deadline. For individual providers, the next steps described by executives are to involve staff in tool design, provide training, roll out changes in stages and make leaders available as teams learn new workflows. Those measures are intended to help employees move through the initial learning period, though their results are not yet established by the survey.
As providers continue to explore and pilot AI, evidence to watch for includes staff uptake, time required to learn tools and changes in productivity over a defined period. Providers would also need to explain how tools affect specific tasks and what support employees receive. The report leaves open whether those efforts will translate into measurable operational gains or broader confidence in AI across home-based care.
Key Questions
What is the main finding of the report?
Industry leaders told Home Health Care News that AI tools depend on employee adoption. They pointed to training, staff involvement and empathetic change management as ways to support that adoption.
How many providers said they were exploring or using AI?
73.3% of providers in a recent HHCN pulse survey said they were exploring potential AI use cases, piloting tools or integrating them in select departments. That figure does not indicate full deployment across those organizations.
What did providers report about employee training?
In the survey of 20 providers, 40% reported no formal employee training. Twenty percent said they used vendor-provided training, and another 20% reported an internal training program.
Why might employees be slow to adopt AI tools?
Executives cited limited time, familiar existing routines, difficult-to-use tools and concerns about trust or work identity. Learning a new process can also reduce productivity at first, according to the leaders interviewed.
Does the report show that AI has improved home-care productivity?
No. The report describes expected uses and leaders’ experiences with implementation, but provides no measured productivity results for the tools discussed.
Source: rss
