The real AI story in HCBS is human
The conversation about artificial intelligence in healthcare often begins with algorithms, automation, and futuristic tools. In HCBS, it should begin somewhere else: with a direct support professional sitting beside a person in their home, listening carefully, noticing a change, and helping that person live with greater independence, dignity, and choice.
That human relationship is the heart of care. It is also exactly why AI matters.
Across healthcare and long-term services and supports, demand is rising while workforce capacity remains strained. The U.S. Bureau of Labor Statistics projects employment of home health and personal care aides to grow 17% from 2024 to 2034, with about 765,800 openings each year on average. At the same time, providers must manage documentation, scheduling, training, compliance, billing, communication, and quality reporting—work that is necessary, but can pull attention away from the person being supported.
Used responsibly, AI can help close that gap. Not by making care less human, but by removing friction around the humans who deliver it. Moreover, according to Medicaid and CHIP Payment and Access Commission (MACPAC) “There is a national shortage of workers who provide HCBS to Medicaid beneficiaries.”
Five ways AI can strengthen HCBS right now
The strongest near-term use cases are not science fiction. They are practical improvements to daily operations and care coordination.
1. Give documentation time back to care
AI-assisted tools can help turn structured staff inputs into draft progress notes, summarize approved records, flag missing fields, and reduce repetitive data entry. Every output should still be reviewed by an authorized human, but a reliable first draft can reduce after-hours paperwork and help teams document more consistently.
2. Identify risk earlier
Patterns are difficult to see when information is scattered across shifts, systems, or weeks. Properly governed analytics can surface changes in incidents, missed appointments, medication-related observations, sleep, mobility, behavior, or staffing. The value is not an automated verdict. It is an earlier signal that prompts a qualified person to look closer.
3. Make scheduling more resilient
In HCBS, an open shift is not simply a scheduling inconvenience; it can disrupt continuity, trust, and safety. AI-supported workforce tools can help forecast coverage gaps, match qualified staff to individual needs and preferences, and recommend options when plans change—while managers retain final control.
4. Strengthen compliance and quality
AI can help scan approved operational data for incomplete documentation, approaching credential expirations, overdue training, unusual billing patterns, or recurring incident themes. That can shift compliance from a last-minute scramble to continuous readiness and give leaders a clearer view of quality trends.
5. Improve communication without losing the personal touch
With appropriate consent and privacy protections, AI can help draft plain-language updates, translate routine communications, summarize care-team discussions, and tailor educational material. The final message should come from a person who understands the individual and the context. AI can prepare the canvas; people should make the meaning.
The guardrails are part of the innovation. Healthcare AI can be wrong, biased, overconfident, or insecure. In HCBS, where services affect people with disabilities, older adults, families, and frontline workers, those risks demand more than a checkbox.
Responsible adoption should include:
- Human review for decisions that affect services, safety, rights, eligibility, staffing, or payment.
- HIPAA-aligned privacy and security controls, including clear rules for what information may enter an AI system.
- Vendor due diligence covering data use, retention, model training, access controls, audit logs, and breach responsibilities.
- Testing for accuracy and bias across the people and communities the tool will serve.
- Plain-language transparency for employees, individuals, and families when AI meaningfully influences a workflow.
- A defined escalation path when a tool produces a questionable result—and the authority to stop using it.
BOTTOMLINE: Automate the burden, not the relationship
Providers do not need to begin with a sweeping AI transformation. Start with one narrow, low-risk problem that consumes staff time and has a measurable outcome. For example, ask three questions:
- Did it save meaningful time?
- Did it improve quality or access?
- Did the people using it trust the process?
The competitive advantage will be more humanity—not less. The organizations most likely to benefit from AI will not be those that deploy the most tools. They will be those that use technology with the clearest purpose: helping people live fuller lives in their homes and communities, helping frontline professionals succeed, and helping families feel informed and confident.
AI cannot build trust with a person over months or recognize every nuance in a home. It cannot replace compassion, judgment, accountability, or presence. But it can help ensure that human capacity is spent where only humans can make a difference. That is the opportunity in front of the HCBS field: not artificial care, but intelligently supported care.