AI technologies like machine learning (ML), natural language processing (NLP), computer vision, and robotics are used to help with problems related to aging and dementia care. From 2021 to 2026, the National Institute on Aging (NIA) invested almost $40 million in pilot projects to create AI tools that improve care for older adults with Alzheimer’s and related dementias. These projects cover areas like remote monitoring, decision support, education for patients and caregivers, and better communication between doctors and patients.
About 27 pilot projects supported by the NIA’s Artificial Intelligence and Technology Collaboratories (AITC) focus on software for users, environmental sensors, wearable devices, and smartphone technology. These projects center on thinking ability, chronic age-related health issues, decision-making help, and educational resources for patients, caregivers, and healthcare providers. Nearly all (96%) of these projects use machine learning, showing how common AI is in this field.
Almost half of the projects focus on basic science to better understand the biology behind aging and dementia. This knowledge helps make the technology more useful because it is based on new research. Small businesses and startups play a big role in these innovations, often working with universities and healthcare groups.
At Case Western Reserve University, a team is working on an AI-powered robot called Ruyi. This robot uses sensors, AI to track movement, and interactive features to help older adults who live in senior homes, especially those in early stages of Alzheimer’s. Ruyi can move around the home, watch how a person walks, talks, and does daily activities, and send updates to caregivers and doctors.
The robot offers companionship and monitoring to keep people safe and comfortable. Philip Cola, a professor on the project, said the robot helps with care and support but does not treat the disease itself. People using Ruyi can even name it to feel more connected to the robot.
The study has several parts to test how residents and caregivers feel about Ruyi, check the technology, and see how it fits into the daily work of staff. The results may help medical managers learn how to add AI robots to long-term care and solve staff workflow challenges.
Almost half of the projects create easy-to-use software. Virtual assistants and chatbots talk to patients and caregivers to share educational information, send medication reminders, and offer behavioral coaching. These AI tools can answer individual patient needs, which helps provide personalized care and medical advice. This is very important for people with memory problems.
These tools help with decision support by giving timely information. They also lower caregiver workload and improve connection between patients, caregivers, and healthcare teams. Chatbots also help medical administrators deal with common questions and training needs without always needing staff.
AI and machine learning are now part of systems for early detection and tracking of Alzheimer’s and related dementias. For example, some researchers use AI to study biological data like genetics to find markers of the disease and learn how it works. Projects funded by the NIA include fast saliva tests and AI-based screening tools that are easy to use and do not require invasive methods.
Techniques like imaging and clinical data use machine learning to help doctors make more accurate diagnoses and create better treatment plans. AI processes large amounts of clinical data and helps spot early signs of cognitive problems. It also tracks disease changes more precisely.
These new tools provide chances for healthcare IT managers to add advanced diagnostics into electronic health records (EHR), improve sharing of data between doctors, and make clinical decision support better.
Wearable devices and mobile health tools use AI to watch health signs, activity, and behavior all day long. They can notice changes in walking, sleep, or social behavior that might mean cognitive decline or other health issues. AI helps by giving feedback or alerts to caregivers and doctors if something unusual happens.
These sensors are very useful for older adults who live alone at home. They let doctors and caregivers keep track from a distance, extending care beyond the clinic visits.
Dr. Zahra Rahemi from Clemson University says AI and machine learning can help lower health gaps in Alzheimer’s care, especially for racial and ethnic minorities. Her studies show that AI tools should respect cultural differences and help with advance care planning in minority groups.
Advance care planning is less common in immigrant and underrepresented communities because of cultural views and stigma related to dementia. Dr. Rahemi’s projects use AI data science to detect risks better and promote fair care ways that fit the special needs of diverse older adults.
Healthcare administrators should include AI tools that understand and adjust to cultural differences. This helps meet legal and ethical rules and builds patient trust and participation.
The Massachusetts AI and Technology Center for Connected Care in Aging and Alzheimer’s Disease (MassAITC) is one example of working together to bring AI tools from research into real healthcare. The center does needs assessments and talks with many stakeholders to support projects that test and improve AI technologies for home and community care.
MassAITC offers access to labs for early testing and helps move AI tools into clinical and home care. Their teamwork between researchers, doctors, developers, and caregivers is a good example for hospital managers and IT staff who want to add AI solutions for better care coordination and remote patient watching.
AI-powered phone systems like those made by Simbo AI can take care of routine talks with patients. These systems can book appointments, send reminders, handle medication refill requests, and do first symptom checks without staff help. This reduces calls that busy staff must handle and improves patient access to quick information. This is important for older adults with memory problems and their caregivers.
For clinics focused on Alzheimer’s care, AI communication tools can provide clear, patient-centered, and understanding conversations that respect memory challenges.
AI tools help clinical teams keep track of patient care plans and reminders. For example, machine learning tools linked to EHRs can alert doctors about follow-up visits, medication changes, or new tests. These alerts help manage chronic conditions common in Alzheimer’s and related dementias.
Practice managers can use automation to flag patients who might need more social or home support. This improves teamwork between clinicians, social workers, and caregivers.
AI tools using natural language processing (NLP) can help doctors by writing down clinical notes or summarizing patient talks. This cuts down on paperwork and lets doctors spend more time caring for patients.
In memory clinics, where detailed notes about behavior and thinking are needed, NLP can pull out important data for tracking disease over time. IT managers can use these tools to improve how clinical records are handled while making sure data stays secure.
Using AI and technology in the care of older adults with Alzheimer’s and related dementias shows promise in improving healthcare across the United States. By using machine learning, robots, virtual assistants, and workflow automation, medical practices can provide better care, work more efficiently, and engage patients more. Careful planning, strong leadership, and teamwork between technology creators, healthcare workers, and administrators are needed to make sure these tools help older adults and their families in real ways.
The a2 Collective aims to fuel innovative AI and technology solutions to support aging adults, particularly those with Alzheimer’s disease and related dementias, by distributing nearly $40 million over five years for pilot projects.
The fourth cohort consists of 27 pilot projects focusing on user-centered applications of AI and technology to enhance care, health outcomes, and quality of life for older adults.
Each selected project in the a2 Pilot Awards receives up to $200,000 in direct costs over a one-year period.
The a2 Collective is funded by the National Institute on Aging, part of the National Institutes of Health, through its Artificial Intelligence and Technology Collaboratories program.
The projects utilize various technologies, including AI-driven software, virtual assistants, environmental sensors, wearables, and smartphone enhancements.
Cohort 4 focuses on cognition (52%), decision support and education for older adults, caregivers, and physicians (44%), and chronic age-related conditions (44%).
The projects aim to enhance remote monitoring, improve physician-patient communication, tailor care, and provide education for patient-caregiver dyads.
The majority of pilots plan implementation in both home settings and hospitals, with a significant increase in projects focusing on chronic conditions.
Almost all projects (96%) incorporate machine learning to improve health outcomes, along with natural language processing (37%) and computer vision (30%).
Cohort 4 shows an increased focus on basic science research (48%) and chronic conditions, indicating a shift towards integrating advanced research methods with practical applications.
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