AI and Aging at Home: A Primer for Providers and Digital Health Companies

Introduction

The United States is undergoing a major demographic shift that is placing increasing pressure on a health care system that is ill-equipped to meet the complex needs of older adults:

• will turn 65 each day through 2027, while the population aged 85 and older will by 2030 and triple by 2060.
• older adults manage multiple chronic conditions and lives with Alzheimer's disease, which require intensive coordination and ongoing care.
• report wanting to age at home, but current systems lack the infrastructure to support complex home-based care at the scale needed.

The gap between preferences and capacity creates urgency to identify tools that empower care teams and increase access to resources that help older adults age in place. Artificial intelligence (AI) holds significant promise to bridge this divide by enabling more personalized, proactive, and robust support for older adults, their families, and the care workforce that supports them.

AI–enabled technologies, including provider-facing tools and direct-to-consumer offerings, can mimic human intelligence to analyze information, recognize patterns, make predictions and share information in real-time. Early applications of AI, such as chatbots and clinical decision support tools, are helping providers make sense of complex data to promote patient health and independence at home, support families with care navigation, and assist an overburdened caregiver workforce. For these solutions to scale, however, they must integrate with existing technology systems and clinical workflows, be designed with real-world needs in mind, and be backed by sustainable policy and reimbursement frameworks. Below, we examine how AI supports aging in place and outline key actions providers and digital health companies can take to accelerate adoption.

How AI Can Support Aging in Place

Managing Complex Needs and Enabling Independence: of older adults who live at home do so alone, making care coordination more difficult and increasing the risk of loneliness, which is as a contributor to poor cognitive and mental health outcomes.

• AI-powered tools use predictive analytics to identify fall risks through movement pattern data, flag drops in blood sugar levels, and detect dementia-related behaviors like disrupted sleep. Real-time insights prompt timely and personalized interventions by care teams to effectively manage chronic conditions and prevent emergency situations.
• AI is also showing promise in supporting behavioral health. suggests that conversational AI chatbots are effective at treating symptoms of depression and anxiety for those unable to access human therapists.
• To promote independent living, voice-activated AI care companion technologies can engage users in conversations, lead mobility exercises, play memory games, and enable messaging with family.

Making Sense of Complex Health Information and Navigating a Fragmented System: of Medicare beneficiaries see five or more physicians annually—a number that will continue to grow as care has shifted towards specialists. Coupled with the fact that older adults than any other age group, this fragmentation can pose serious safety risks.

• AI can collect, summarize and interpret disparate health data to ensure families and caregivers have the information they need to make informed care decisions. 
  • For example, electronic health record (EHR) patient portals are using AI to generate plain-language summaries alongside imaging results to ensure patients and caregivers understand the findings and follow through on next steps such as appointment scheduling.
• To further address the care coordination burden, EHR vendors have built AI-powered agents to communicate with patients via text to complete pre-visit preparation, answer common questions and manage prescription refills.

Supporting the Caregiver Workforce: As demand for long-term care at home grows, so will the need for home care workers. PHI, the nation’s leading authority on the direct care workforce, that nearly nine million direct care jobs will need to be filled by 2032, with the majority of those roles in the home care industry. Despite their essential role, home care workers often face low wages, limited benefits,  and unpredictable part-time schedules, making it difficult to recruit and retain staff. Without new policy or technology solutions, more responsibility will fall on the providing unpaid care to aging loved ones.

• AI-enabled tools can support the paid home care workforce by optimizing staffing decisions, triaging patient needs, and streamlining time-consuming tasks like documentation and communication with families. 
  • For example, home care provider platforms are leveraging AI to match caregivers to clients based on skills, proximity, and existing client relationships.
• The goal of these tools is to surface potential risks before they arise, reduce administrative burden and free home care workers to spend more time meaningfully engaging with clients.

Opportunities to Accelerate Adoption of AI to Promote Aging in Place

While early use cases suggest AI can meaningfully support older adults and those caring for them, providers and digital health companies will need to work together to build tools and user experiences that address real-world needs and achieve widespread use. Three focus areas warrant further action by providers and digital health companies, including building user trust and AI literacy, aligning solution design, and advancing policy and coverage frameworks.

Building User Trust and AI Literacy: Some people remain cautious about using AI. Concerns around data privacy and the risk of fraud or hacking, especially with sensitive personal health information, hinder broader adoption. To address this, providers and digital health companies should:

• Expand digital literacy programs for older adults and caregivers.
• Implement AI governance frameworks to provide structure for responsibly adopting, testing and scaling the use of AI.
• Create plain-language AI user guides that explain AI solution capabilities, what data is collected, and how data is protected.

Aligning AI Solution Design: AI tools need to be built with the needs of older adults and their caregivers in mind and must integrate into existing technology systems and care workflows. To improve usability and fit, providers and digital health companies should:

• Prioritize interoperability with existing technology, especially electronic medical records, to unlock access to critical health data and a broader range of use cases.
• Apply principles to tailor tools to the unique needs of different users.

Advancing the Policy and Coverage Landscape: A consensus has yet to be reached on how to value the work performed by AI tools or how to reimburse their use in care delivery. State and federal policymakers have taken , which has created a difficult landscape to navigate for providers and developers investing significant resources to build solutions. To support progress, providers and digital health companies should:

• Share their views through public comment opportunities like the , which seeks input for how to better leverage digital technology for Medicare patients and providers.
• Engage with industry bodies such as the AMA’s , to advocate for coding solutions that recognize and support the use of AI.
• Seek new opportunities to use AI tools in real-world settings and innovative reimbursement models through programs like , the , or other initiatives.

AI’s role in aging and home care will only expand. Keeping human-centered design principles at the forefront will be key to developing and scaling solutions that make aging in place safer, more accessible, and more sustainable for individuals, families, and the workforce that supports them.

For more information on how your practice or company can lead in this space, please email or .