Scaling care with agentic AI: Home-based care predictions for 2026 with Adrian Schauer

Adrian Schauer: 00:00
What we’re starting to see is that the people, whether it’s coordinators, clinical supervisors, are able to do a lot more of the human engagement work, and they’re not stuck behind a computer filtering, pushing workflows around themselves. I would say this is extremely exciting for me to see this all come to fruition.

Erin Vallier: 00:30
Welcome everyone. I’m a regional director at AlayaCare, and I am thrilled to be joined by AlayaCare’s co-founder and CEO, Adrian Schauer. Today we’re going to be unpacking his top five predictions shaping home-based care in 2026.

Adrian Schauer: 00:48
This is becoming an annual tradition for us, Aaron.

Erin Vallier: 00:51
Yeah, it is. I get to like peer inside your head.

Adrian Schauer: 00:55
A scary proposition.

Erin Vallier: 00:56
Right. So let me start by quickly talking about AlayaCare. AlayaCare is an end-to-end home-based care platform, and we support the entire client lifecycle. That’s intake, scheduling, authorizations, care planning, mobile app, visit optimization, all of it. We do reporting, billing payroll. We’ve got you covered, soup to nuts. But what really sets us apart is our integrated AI capabilities. And that helps agencies do things like save time, improve quality of care, and operate much more efficiently. Whether it’s automating tasks or servicing insights, AI is built right into our platform to support better outcomes at scale. So out of AlayaCare, we like to say that our mission is to give you the how so that you can focus on your why, which is delivering outstanding care. All right. We’ll start by reflecting a little bit on 2025 and see what predictions actually shook out from last year. And then we will move into the five predictions for this coming year, starting with AI agents and daily operations, moving into data interoperability and collaboration, and then AI at the point of care, workforce design, and then finally evidence-based leadership, followed by some Q&A. So with that context in mind, let’s rewind for a moment, shall we?

Adrian Schauer: 02:25
And who doesn’t like being graded on their predictions? Thank you, Erin, for leading off with this.

Erin Vallier: 02:30
Exactly, exactly. Let’s see how good you are. Let’s see if the universe has given you an accurate eight-ball, you know, every year that you could shake it. So at the end of 2024, at about this time last year, Adrian joined me on our Home Health 360 podcast to share his predictions for 2025 and beyond. And that episode became one of our most watched and most downloaded shows. And that just tells you just how hungry this audience is for a credible view of the future. In that conversation, Adrian, you talked about three big themes. You talked about agentic AI moving from simple rule-based automation to something that’s much more proactive and collaborative. You talked about a home care flywheel. And boy, wasn’t that the theme internally at AlayaCare for a while too. And this is small continuous improvements compounding over time. And then you talked about the importance of the caregiver experience as a competitive advantage and not just a nice to have. And you also said something that stuck with me when it comes to your predictions. You’re often right, but a little bit early. And often being too early feels like being completely wrong. So let’s start there. When you look back at that podcast now, what did you get right in 2025 and what surprised you?

Adrian Schauer: 03:52
We start with the first prediction around agentic AI becoming more proactive and collaborative. A year ago, AlayaFlow and AI agents, at least for us, were kind of a twinkle in my eye. Through these last 12 months, we’ve gone from recognizing a trend to building the platform to delivering agents, to then actually delivering the agents and to now seeing them live out there, kind of generating business outcomes for our customers. I’m going to go ahead and give myself positive marks on the first one. On the home care flywheels, so you talked about the 1% improvements compounding over time. Totally agree with that. Really, in home care, the flywheel goes from happy caregiving staff to clients and patients getting great outcomes, and then that feeding back into getting more referrals, getting superior financial results. And for the most part, I would say we have seen that flywheel spinning well for our customers. Maybe where I didn’t totally get it right was what are the external influences on the success of a home-based care program? And I didn’t get the politics right. I probably did not expect as much financial pressure really in all the jurisdictions where we do business. But here I’ll give myself a partial score because whereas the stuff that can be controlled as a home-based care provider does live by that flywheel, there are external factors that have to be controlled for as well. I think that is still true. But one of the few spots that has become a little bit easier over the last year or two years has been on the labor market pressures. Obviously, it’s not a solved problem. Recruitment and retention are still very important. But employee experience as a strategy to not only retain but also attract caregivers. I do think most of our customers who were doing well viewed employee experience in this way and that looked at what they could bring to the table in culture and tools and experience to create an environment where people want to work and do their best work.

Erin Vallier: 05:56
It’s important to keep those frontline workers very happy and in their seats. I think you did pretty good in 2025. And I want to connect the big ideas into a big moment for us as a company. And for many of you who actually joined us in Jersey City or in Toronto, we held our Better Outcomes 2025 conferences. And that’s where we unveiled AlayaFlow, which is our AI-powered workflow platform that brings these agentic AI predictions into real operational workflows. This wasn’t just a slideshow and a keynote, right? This was a full launch of a platform built to power a family of AI agents right inside AlayaCare Cloud. Super exciting. At this launch, we introduced three agents that map almost directly to what you described in that 2025 episode, Adrian. We have a vacant visit scheduling agent. That agent automatically finds qualified replacements when a caregiver can’t make a shift. It sends those offers, it can communicate with those workers, and it will escalate to a human if a match is not secured. And that helps prevent missed care and it rescues your back office from having to spend time failing those visits. We also have a visit verification agent that triages and resolves failed visit verifications, maintains compliance across your organization and accuracy without the endless manual steps to clean up those visits. And we also have a recommended care plan agent embedded right into care planning that helps clinicians generate consistent and personalized goals and interventions much faster. Now, when you listen back to that 25 predictions episode and you look at a liya flow and what how it stands today, what goes through your mind as you reflect on a liar flow going from prediction to an actual product?

Adrian Schauer: 07:56
It was definitely a highlight of my year giving that onstage demo at Better Outcomes. I like to get the blood pumping. This was software fresh off the presses. The response as we demoed was really kind of everything I would have hoped. So that was really exciting. Today, playing with AI as part of the offering is often seen as like, let me get an experiment done, but not necessarily make major changes to how I operate. I think that experimentation era is ending. And now it’s the hey, if I’m going to be competitive in my business going forward, I actually have to find a way to change how I operate using modern technology. And the AI agents for us as a software provider are a total game changer. In the era of software that is ending, we viewed our role as providing tools that help users achieve business outcomes. Now we see our role as delivering business outcomes directly. Even in the way we’re pricing our agents, is on a per business outcome basis. It’s total alignment between what the tools we provide do and what business value is for our customers.

Erin Vallier: 09:12
It’s very exciting. It makes the barrier to entry and using these tools very low or non-existent. So that’s exciting. So essentially in 2025, we moved from just talking about agentic AI to actually shipping it. So we went from a podcast episode to a real platform with early adopters, with live demos of better outcomes and a clear roadmap towards general availability of these agents by March of 2026. So with that in mind, your 2025 predictions, the launch of AlayaFlow, and everything we’ve learned from early access, it’s time to look ahead, Adrian. Let’s see what you have in store. First prediction is AI agents becoming essential to daily home care operations. In your 2026 Outlook, you talk about moving from pilots to practice, agents that handle real work like documentation, risk detection, and routing information so staff isn’t buried in administrative tasks. You look at tools like Layla, which is AlayaCare’s AI assistant for natural language questions, with AlayaFlow managing the workflow side, all with one goal. Let’s give people more time for care and not more time on their screens. So with that in mind, I have a question for you. What convinces you that 2026 is the year agents become infrastructure rather than just a side project?

Adrian Schauer: 10:45
It’s hard to call this a prediction because we’re actually seeing it happen today. As you mentioned, we’re in the beta phase with some of our leading customers. We’re still a month and a half from general availability of these agents. But what we’re seeing is our customers really rethink what should the people in my organization be doing versus what can I rely on my software and on AI agents to do? What we’re starting to see is that the people, whether it’s coordinators, clinical supervisors, are able to do a lot more of the human engagement work, and they’re not stuck behind a computer filtering, pushing workflows around themselves. I would say this is extremely exciting for me to see this all come to fruition.

Erin Vallier: 11:32
That’s a good segue into question number two here. I want some practical wins. Tell me some stories here, and how do you think this is going to evolve over the coming year?

Adrian Schauer: 11:41
Remember the three agents you mentioned them at the outset? There’s the visit verification agent, the vacant visit filling agent, and there’s the care plan generation agent. What we’re seeing on the first two is if I walk into a typical home care agency, there are a lot of folks in the coordination team that are executing these processes where it’s actually fairly algorithmic. If a visit started late and there’s a task that should have been completed that wasn’t completed, what happened? Someone can tell you in natural language, well, I’ll look at the location, I’ll look at the time, I’ll see if the shift was covered, then maybe I’ll call or text the caregiver and I’ll ask them why, and then I’ll take that and I’ll turn it into a reason resolution code, and then I’ll pass the visit verification through, et cetera, et cetera. The AlayaFlow agents are able to do all of that themselves, including having natural language conversations with our caregivers, with the clients directly. It’s been super interesting to watch.

Erin Vallier: 12:47
It sounds like we’re saving a lot of people time and effort it takes to do their job so they can focus on really what matters. So we’ve mentioned the three that we’ve started with. We’ve got vacant visit scheduling, care planning, and visit verification. We started with those because those are three major pain points that we hear of over and over. But what I want to know and what all these people want to know, I’m sure of it. What’s next moving into 2026 in terms of agent use cases?

Adrian Schauer: 13:17
We didn’t come up with these in a vacuum. We spent a lot of time with dozens of our customers looking at where the opportunities were. So we did pick the three highest value use cases. There are a couple of key workflows that did not make the cut of the first three, but are then going to be fast following in terms of other agents. Intake, lots of potential for agents because you’re basically taking a bunch of information from different sources, you’re making some probabilistic decisions, you’re synthesizing information, and you’re using that to create the client file and take the next step in a workflow, maybe checking all. So uh intake certainly. And then on the revenue cycle as well, that’s a really good candidate for agentic automation. So those are the two domains coming up quickly. And then just smaller kind of agents that enable the results from the core use cases. So things like confirming caregiver availability and so on. You can take those into an agent or even from a scheduling point of view, rather than just filling to shift visits when there’s a call-off. I know that I could optimize it, but maybe I’m not doing it today because who has time to make a hundred phone calls to shift visit times and visit assignments? And now the agents can do things like that. So that’s kind of where we’re thinking in terms of the next wave of use cases.

Erin Vallier: 14:39
Oh man, if I’m a provider listening to this, I’m so excited, especially with the intake, because that’s a lot of cross-organizational coordination and outreach, insurance. Do we have the staff? Do we have the skill set? All of it. And if an agent can take the lion’s share of that, that’s huge.

Adrian Schauer: 14:56
Yeah, and also do it in a very predictable way. Mistakes you make at intake can cause lots of operational issues downstream.

Erin Vallier: 15:04
100%. Okay, let’s move on to our second prediction, which is data interoperability will start driving real collaboration. You paint a picture of disconnected systems giving way to shared standards where a hospital discharge automatically triggers a home care intake, and coordinators get timely alerts, and families can follow progress all in one place. You also tie this to compliance, where AI can flag gaps in EVV or documentation before an audit hits your desk. So, given that vision, Adrian, how do you see interoperability practically changing day-to-day work for providers and what milestones do you expect in 2026?

Adrian Schauer: 15:48
I see kind of two categories that fall within interoperability. The first category is from other parts of the health system into home care. And then the second type is within the home care agency, if I have disparate systems that manage human capital and other things versus actually doing the operational clinical side of the operations, those need to work well together. So we start in the first category. We are seeing more and more electronic referral bundles. But even if it’s a stack of eFax documents coming in, the great thing about AI is that it can go off, read those PDFs, come up with the right information, and then put it in the right place and take the next step in a workflow. So there’s big progress happening there. Milestones, I would say, you asked about KPIs. It would be things like time from admission to first visit, how quickly I can process referrals, when I get to billing, do I have all the information I need because I collected it completely upstream? So those are some of the KPIs we would watch to see if interoperability is really delivering the value we want it to.

Erin Vallier: 17:01
And today, everyone knows that if systems are not connected, then you rely on a human to enter the same data over and over into disparate systems. So where do you see duplicate entries and handoffs creating the biggest cost for providers today?

Adrian Schauer: 17:17
We call this kind of swivel chair workflow management. I go into this piece of software, do my thing, then move over to the other piece of software, do my thing. And in 2026, that’s fairly inexcusable as a source of inefficiency in agencies. The key workflows kind of track the roles you would have in your organization. So it would be from intake to coordination, from coordination to billing, then also into the human capital and payroll functions. So everywhere we want fully integrated systems and light care brings tools like Connector to the table that can help kind of seamlessly stitch together those systems.

Erin Vallier: 17:57
Absolutely. Reduce the error rate, which has a downstream impact on your financials for sure. You kind of touched on this. You mentioned a few KPIs that we’re going to be watching to track how interoperability is changing our day-to-day. But is there anything else you want to add? Rekeys, claim edits, audit findings. What are KPIs that signal progress in this area?

Adrian Schauer: 18:19
I would say a master KPI would be about back office efficiency. So how much back office cost and/or staff do I have to power a given amount of frontline care that’s delivered? So that’s really at the top level. And then you hinted exactly at some of the other kind of component pieces that would add up to efficiency there. We’ll talk about it on the last prediction around the customer maturity model, but definitely keeping a quantitative view on how the business is performing will be essential.

Erin Vallier: 18:50
Absolutely. So next prediction zooms in on the frontline. This is where agents support caregivers at the point of care. That’s exciting. And you describe in 2026 as the turning point where tech finally fits around the visit, where caregivers can pull up things like histories or they see recent changes or they get just in time guidance without jumping in between a bunch of systems or screens. And you’re clear that this isn’t about replacing clinical judgment, right? That’s important. It’s about less after hours paperwork and a lot more confident decisions in the home, which is super important. So, what do you think point of care AI support will actually feel like for caregivers in 2026? And what experiences do you expect to become mainstream? Things like ambient listening, risk flags, just in time prompts, like talk to us here.

Adrian Schauer: 19:45
You put your finger on two of them. If you think about the experience of delivering home based care, it’s actually one of the toughest jobs in healthcare because you aren’t surrounded by your colleagues. You are really kind of on the coal face making Decisions and it can be a scary and lonely place to be practicing. But there are some tools that can be brought to bear that really help with that. Those who are familiar with Alaya Care will know Layla, that is our AI assistant. And so I could be on the doorstep about to head into a home. I’m going to see Mrs. Smith. And I might want to know what’s changed since the last time I was here. What are the greatest risks for Mrs. Smith? And I can pose these questions in natural language. Oh, now I see a diagnosis I’m less familiar about. I can chat with Layla to get more information. So there’s a real empowering knowledge interface available there through Layla. I think that’s a big deal. And then the second one you talked about is the ambient scribing tool. We’ve also just released our voice to forms tool. And there it really allows me as a caregiver to be present with my client, to look them in the eye, to not be sort of scattered between, well, I’ve got to go chart this thing, telling me again what you said. Okay, I’ve got to go chart this thing. You start the mic in the app, you do your intervention, and then whatever form of clinical documentation gets fully populated, obviously verified before submitted, because this is a clinical document, but just amazing in terms of what it does for the experience of being able to be empowered and pressed with your clients.

Erin Vallier: 21:29
I love that. I read something this morning and it said attention is the currency of love. And I love that because that’s what we do when we go into the home. We’re providing care, we’re giving them love and making sure they’re safe and cared for in their home. You kind of answered this question, but I’m curious if you have anything to add. Which tasks do you think are going to be offloaded first from caregivers so that they can actually manage their caseload more effectively and not on the weekends?

Adrian Schauer: 21:55
Yeah, just being able to do all my walking out of the home with my documentation fully done. That’s the top of the list.

Erin Vallier: 22:02
That is huge. All right. So let’s talk about the next one. This is a good one. What is the right balance between AI autonomy and human in the loop? And how are tech providers going to continue to strike that balance as AI continues to become more advanced? It can do math now, like complex math. A few weeks ago it couldn’t. And now it’s like thinking like a human. So how are we going to keep this balance here?

Adrian Schauer: 22:27
Yeah, so there will never be a replacement for the clinical judgment of a nurse or a practitioner. What we’re seeing in practice where we’re deploying these agents is an escalation to take a next step when there’s a level of uncertainty or when it’s a clear kind of pivot point in the judgment of the person responsible. What I think we’ll see over time, if I keep getting escalated, hey, we think this thing changed. Do you want to do the next step? If you’re doing nothing but clicking yes, 99% of the time, then you might say, you know what? I think I’m confident now the agent can take this step in the workflow. Let me skip these or let me tighten up the criteria of when I need an escalation versus when the agent can just progress with its workflow. I think this balance will shift over time, and it’ll only shift right to the extent that the agent is right close to 100% of the time.

Erin Vallier: 23:23
I know we focus on starting very small with a small scope and letting it earn trust. That’s super important. How do you predict that all of these changes and like all these tools that we’re implementing, how is that gonna affect frontline metrics? Like what can providers expect on things like documentation time, quality of first visit, caregiver retention? What do you expect?

Adrian Schauer: 23:46
No one chooses to go into home care because they love filling out forms in a parking lot. There is a unified win-win around let people spend time caring for their clients, and then everything else should go down to as close as zero as possible. I would say that’s the primary metric.

Erin Vallier: 24:04
That makes me smile. Your fourth prediction tackles the workforce head-on. You say that a shortage will continue. It has continued every year and gotten larger every year, but in 2026, we should start to rebuild from within, designing the work around stability and skill. Now, you talk about predictive scheduling that matches caregiver strengths to client needs, smarter communication for people working independently, and AI assistance that strip out administrative friction. And the home healthcare news and a liar care survey actually backs this up. I said the leaders expect real progress from steadier schedules, stronger workforce management, and simpler daily tasks. So with that in mind, when you look ahead, how do you see leaders practically redesigning their workforce bottle around stability and skills in 2026?

Adrian Schauer: 24:57
I think it’s kind of this trend that has been happening for the last few years of caregiving being a profession, not a gig economy job. Obviously, nursing and therapy, those have been more professionalized than personal caregiving historically. What we’re seeing now is the conditions being put into place to really invest in your caregiving, your aid population, and continue to up-skill, try and get really kind of full workloads so it’s less precarious of a job and more consistent hours. So I think that trend will continue certainly for the leading providers.

Erin Vallier: 25:35
So when do you expect that these improvements are going to translate into easier recruitment and a more professional career path for the caregivers?

Adrian Schauer: 25:44
It depends a little bit on what else is going on in the economy. As other parts of the economy get hotter or slow down, the relative benefit of being in home care can go up or go down. There was an interesting study a couple of years ago showing which jobs are most at risk of disruption from AI. And at the bottom of the list was home care aid. So I think the relative value of this job versus other jobs in the economy will continue to go up. And I think ultimately that’s going to help recruitment.

Erin Vallier: 26:17
That’s awesome. The need is certainly going to continue to go up, that’s for sure. So by the end of 2026, what does a mature agent-enabled organization actually look like day to day? And what impact will that have on workforce stability?

Adrian Schauer: 26:34
First of all, a mature agent-enabled organization will be more profitable than one that isn’t. No profit, no purpose, no money, no mission. You pick your alliteration. But there’s financial challenges in this space, and being able to concentrate more resources on frontline care, I think is good for everyone. I also hope to see less drudgery in the delivery of home-based care, kind of writ large. It’s interesting. We have better outcomes in Toronto. We had Steve from ParaMed on stage in one of the panels, and he was talking about how he helps his team get over a version to AI. Says, well, I actually start with a question. Tell me the three things in your job that you hate the most. And invariably the answer he gets back is near the top of the list of tasks that he’s looking to automate with AI. I think it can definitely be a win-win on this front.

Erin Vallier: 27:26
Sounds like it. That’s super exciting. Let’s dive into prediction five. Leadership’s going to shift from intuition to evidence. You write the empathy and experience are still essential, but in 2026, leaders will also rely on real-time metrics instead of only retrospective reports. AI and analytics give them a clear view of operations and outcomes so that they can, for example, show how caregiver stability reduces hospitalizations. And they can use that to argue for higher contract values. You also flag the change management side of things, which is huge. New systems often bring friction. So leaders are going to have to guide their teams with transparency and have a learning mindset.

Adrian Schauer: 28:12
So, from my point of view, if you can orient your organization around the unit or the units of business value that are actually delivered, right? And that could be a great patient outcome because of caring moments you deliver, right? You could frame it in any way you want, but there will be a way to measure it. And the more you can orient efforts around those measurable outcomes, the easier alignment will be to get in your organization. As a partner to our customers, we have attempted to put a framework around the different aspects of value within a home care organization. And we’ve framed that in what we call the customer maturity model, where we have key performance indicators around all the aspects of a home care organization. And we have benchmarked those against your peer so you can see where you’re leading and possibly where you’re lagging, and then what some tools or tactics might be to improve from there. But it’s really interesting how you operationalize that and what tools you need. How do you need the data framed so you can actually orient everyone around the same set of goals and see whether you’re succeeding or not against those goals?

Erin Vallier: 29:25
So you wanted to skip to the QA because I think we have some questions. So, folks, that wraps up the 2026 predictions. We’ve chatted a lot about our agentic AI. So if you want to learn more about AlayaFlow, you can also say yes, please contact me and we’ll be sure to reach out and schedule a conversation. Okay, let’s go to the poll questions here. Can you please elaborate on the care plan generation agent?

Adrian Schauer: 29:55
Yeah, 100%. So as inputs, the care plan generation agent basically takes your assessment form, it combines it with information you have in the patient profile, which could be diagnoses, demographics, other things. And then typically you will have a care plan library from there. And so what the agent does is it combines those data sources, suggests a care plan, a personalized care plan for that client, but that fits within your clinical practices. And then your clinical supervisor or whoever’s actually creating the care plan can, of course, edit that suggested care plan if needed, but that goes seamlessly from the assessment to a suggested care plan.

Erin Vallier: 30:39
What safeguards are put in place for agents?

Adrian Schauer: 30:42
There were some hilarious hallucinations as we were building this thing. You know, if you asked Layla, what visits do I have tomorrow? And the scheduler API returned that you had no visits tomorrow, whatever LLM we were using would say, Oh, well, you have uh brunch and then you’re going to see a movie. The LLM was so keen to please that it would make stuff up. So if you look at the actual design of the AI and AlayaCare, the guardrails were there. So you have a supervisor agent that understands the intent of the question, and then it calls subagents. So then in that example, it would call the scheduler agent, it would retrieve your scheduled visits, and then it would form the response based only on that data with prompt engineered around it so that it doesn’t hallucinate stuff. So that’s on the Layla front, and then on the agent front, you basically have deterministic workflows with probabilistic nodes in there. The agent can’t go off the rails. So it’s a little slightly different answer for every use case, but yeah, absolutely, we have safeguards in place. Often we’ll recommend starting with reactive before you move to proactive. So launch Layla, let your users understand when you put something in, what comes back, get them more familiar with how to work with an LLM, and then you can start to do more of the proactive agentic tools. So that would probably be my advice on how to start. So Alison, sounds like you’re in Ontario. And yes, Supply Ontario does have an approved vendor list for AI scribes. They’re more oriented at the kind of physician setting. Our scribing tool is built right into AlayaCare. You’re able to utilize that. You don’t have to go through Supply Ontario. This is integrated right in the AlayaCare product. How are you addressing system app latency that can be introduced by API? I could take that in one of two areas, right? One risk would be that the agents are running so rampant that they slow down the app because they’re making so many calls and slowing down the database. You know, that should not be the case with a well-designed agent, but we do have rate limiting on the APIs. And again, the system should be auto-scaling to the demand. You know, maybe DM us specifically if you have a use case there, but there should be no trade-off between system latency and AI.

Erin Vallier: 33:16
All right. Before we completely wrap up, I want to invite you to our next session that builds on everything Adrian shared today. It’s going to be a round table on January 21st called People Plus AI, Empowering Home-Based Care Workforce of the Future. It’s going to focus on how providers can harness AI while staying true to the relationship-first nature of the industry, which I think is important. We’re going to hear from industry leaders on how they’re using AI to reduce administrative burden, make life easier for their caregivers, and protect the relationship-driven heart of home-based care. Thank you, Erin, and thanks to everyone for joining. Until next time, everyone, take care. Home Health 360 is presented by AlayaCare and hosted by Erin Vallier. First, we want to thank our amazing guests and listeners. Second, new episodes air every month. So be sure to subscribe today so you don’t miss an episode. And last but not least, if you like this episode and want to learn more about all things home-based care, you can explore all of our episodes at alayacare.com/homehealth360 or visit us on your favorite podcast platform.