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Home Health Care News reports that home-based care leaders see staff adoption—not just the technology—as a major challenge in AI deployments. A survey of 20 providers found gaps in formal employee training and trust or buy-in, while executives described using department-specific planning, phased rollouts and staff champions to support adoption.
Home-based care executives interviewed by Home Health Care News say AI tools will not improve staffing, scheduling or administrative work unless employees adopt them, making training and empathetic change management central to implementation. The report draws on industry leaders and a survey of 20 providers, which found varied approaches to staff training and widespread concern about employee trust and buy-in.
The survey asked providers about managing workplace changes tied to AI tools. Forty percent of respondents said their organizations had no formal employee training; 20 percent reported vendor-provided training and another 20 percent an internal training program. All respondents worked for organizations with one to 20 locations. More than half said their organizations provide Medicare-reimbursed skilled home health, and 66 percent said they provide personal home care, either private-pay or Medicaid-reimbursed.
Survey respondents most often identified staff trust or buy-in as the largest gap to AI adoption. Popular approaches included introducing tools in phases before full integration, visible leadership endorsement and naming change champions or “super users.” Those approaches are intended to involve staff in implementation and give employees support as they learn unfamiliar systems.
At Tribute Home Care, Director of Strategic Planning and Project Management Galip Gencer said the organization first asked department leaders to set their priorities, then developed tools to support those plans. He told HHCN that designated AI key users from each department took part in early work on internally developed tools. The approach, he said, was meant to make implementation reflect each department’s needs rather than allowing the technology to dictate the work.
Adoption Can Shape AI Results
The report highlights a practical distinction for care providers: buying or building an AI tool does not establish that it will be used effectively. Employee adoption can affect whether a tool changes scheduling, documentation or other daily tasks. For home-based care organizations facing staffing and administrative pressures, a slow or uneven rollout may delay anticipated operational benefits.
Introducing a system can also temporarily reduce productivity while staff learn new processes. Emily Kraeter, TheKey’s chief people officer, described this as a “J” curve: performance may dip before it improves. That adjustment can be difficult for workers with daily targets and little time for training. Leaders therefore have to weigh the time required to learn a tool against immediate workloads, and communicate that early friction does not by itself show whether a system will succeed over the longer term.
The stakes include workforce confidence as well as efficiency. If employees feel excluded from decisions or fear that technology threatens their role or professional identity, they may be less willing to use it. The report presents empathy, involvement and skills development as management strategies; it does not establish that those methods guarantee adoption or measurable gains.
Care Providers Test AI Tools
Home-based care organizations are exploring AI for work such as scheduling, staffing and documentation. In a separate HHCN pulse survey cited in the report, 73.3 percent of providers said they were exploring potential AI uses, piloting tools or integrating them in selected departments. That figure combines organizations at different stages and does not mean that all have deployed AI broadly.
The report also describes differing experiences with specific tools. CommonSpirit Health at Home CEO Trisha Crissman said some frontline employees were accustomed to documenting on tablets and were slower to adopt ambient scribing, which relies on conversational assessment dialogue. She said the organization had underestimated the change-management effort and that adoption was slower than expected. Tribute CEO John Sneath, meanwhile, said schedulers may prefer established processes while a new agent takes time to set up.
The survey findings reflect a limited group: 20 providers, all from organizations with no more than 20 locations. The results provide a snapshot of those respondents, not a measure of all home-based care companies. The report does not specify a representative sampling method or provide results broken down by tool type.
“The reason they fail wasn’t because, for the most part, the solution didn’t do what it needed to do. It was the adoption of the solution didn’t actually happen.”
— Greg Meyers, chief operating officer at TheKey
Long-Term Results Remain Unreported
The report does not provide evidence showing whether the approaches described led to sustained adoption, improved productivity or better care outcomes. It also does not identify the AI products in enough detail to compare their performance, costs or effects on different roles. The survey’s 20 responses are a small sample, and the report does not establish how closely they represent the wider home-based care sector.
It remains unclear how long employees in the organizations studied needed to become comfortable with the tools, how much training was ultimately provided, or whether the initial productivity dip later gave way to gains. The report also describes employee concerns about lost productivity and professional identity but does not quantify how common each concern was or establish that all providers faced the same barriers.
Providers Must Track Adoption
The report identifies no scheduled industry-wide milestone or follow-up study. For providers considering or expanding AI use, the next steps described by executives include setting department-specific goals, involving staff early, assigning internal champions and providing time and support for training. Those measures may help organizations learn where workers encounter friction, but their effectiveness will depend on each tool and workplace.
Further reporting or provider data would be needed to establish whether phased rollouts and staff training improve sustained use or productivity. For now, the reported experience points to an implementation process that may take longer than a technology purchase or pilot alone suggests.
Key Questions
What is the main finding of the report?
Home Health Care News reports that employee adoption is a major challenge in home-care AI projects. Executives cited training, trust and support during early implementation as key parts of change management.
What did the provider survey find about training?
Among 20 respondents, 40 percent said their organizations had no formal employee training. Twenty percent reported vendor-provided training and another 20 percent an internal training program.
Which AI uses are discussed?
The report discusses tools related to scheduling, staffing and documentation, including an ambient scribing tool and a scheduling agent. It does not provide a detailed comparison of products.
Does the report show that these strategies improve productivity?
No. Executives describe approaches such as phased rollouts and staff champions, but the report does not provide results proving that these strategies lead to sustained adoption or productivity gains.
How representative is the survey?
The survey included 20 providers, all from organizations with one to 20 locations. The report does not establish that the respondents represent the entire home-based care sector.
Source: rss
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