By 2050, over 1.5 billion people, nearly one in six globally, will be aged 65 or older, according to the UN. This unprecedented demographic shift is straining conventional healthcare systems, driving up chronic disease management costs and intensifying the caregiver shortage. As traditional models buckle under rising pressure, AI-led digital interventions present a path forward, redefining how we deliver elderly care and mitigate health risks with precision.
Simultaneously, the healthcare workforce is projected to face a shortfall of 15 million professionals by 2030 (World Health Organization). Combined with the skyrocketing cost of elderly care due to chronic conditions, longer life expectancy, and the increasing need for specialised care, these shifts call for a systemic change.
Artificial Intelligence (AI)-led digital interventions are fast emerging as critical enablers, offering a blueprint for aging societies to deliver timely, efficient, and value-based care. From preventing chronic illnesses using predictive analytics, improving the quality of care with AI-powered tools to lowering healthcare costs by streamlining administrative tasks, predicting hospital admissions and optimising staff allocation, AI-led digital interventions have the potential to optimise multiple aspects of elderly care.
This blog explores how AI-led digital interventions can help healthcare providers manage cost, streamline operations, and improve the quality of elderly care.
Revolutionising Senior Care with AI
AI has a vital role to play in revolutionising elderly care, offering personalised solutions, supporting caregivers, and actively managing age-related health challenges. Here’s how AI-led digital interventions are transforming elderly healthcare:
- Improving operational efficiency and resource optimisation: AI can automate and help streamline administrative work like task scheduling, billing, and insurance claims, improving operational efficiency and reducing the burden on healthcare providers. By optimising resource allocation, planning shifts, and forecasting staffing needs, AI-powered systems help cut costs and reduce caregiver burnout, enabling them to focus more on patient care. These advantages are already evident in practice. For instance, UK’s National Health Services employs AI to predict hospital admissions and optimise staff allocation, resulting in reduced wait times, better patient outcomes, and lower costs.
- Enabling caregivers to make real-time decisions: Through real-time health updates, early warnings, and data-driven care recommendations, AI systems help caregivers prioritise tasks, eliminate guesswork in critical moments, and make decisions without delay. Such AI-generated insights help caregivers to move away from crisis management and focus on delivering personalised, high-quality care.
- Reducing emergency room admissions: AI models can analyse patient data to identify high-risk individuals early, enabling preventive care that reduces emergency room admissions and expensive hospitalisations. AI support tools also provide proactive guidance on symptom monitoring for the elderly, often directing them to primary care instead of the ER. This proactive approach not only allows for the early detection of health issues but also helps alleviate the burden on healthcare systems.
- Detecting illnesses early with wearables and remote monitoring devices: AI-equipped wearable devices help detect signs of acute illnesses such as myocardial infarctions, brain strokes, or lung infections like pneumonia and COVID-19. Such detection is both faster and cheaper than manual detection. Furthermore, AI-driven remote monitoring devices help track vitals, detect falls, identify anomalies, and alert caregivers about potential health issues, reducing the need for in-person visits while maintaining quality care.
- Identifying social conditions impacting elderly health: Leveraging AI and ML models allow caregivers to identify social determinants of health, like specific living conditions and neighbourhoods that the elderly are particularly vulnerable to. These insights are vital for healthcare providers, enabling them to make timely interventions, reducing the likelihood of health complications, and preventing repeat occurrence of hospitalisation.
AI-led digital interventions are driving systemic change in elderly healthcare. By automating administrative tasks, streamlining workflows, and enabling preventive care through advanced diagnostics and patient data analysis, AI is contributing significantly to reducing operational overheads, bringing down the cost of healthcare while continuing to raise the quality of care. But the role of AI goes well beyond automation and preventive care.
Advancing Personalised Support for Seniors
Besides cost savings and increased operational efficiency, AI solutions are also reshaping how care is delivered to the elderly by enabling a more proactive and personalised approach to healthcare. Here are a few ways AI-driven solutions are improving the quality of elderly care:
- Virtual Health Assistants (VHAs): AI-powered VHAs are transforming the nature of elderly care. VHAs provide seniors with 24/7 support, simplify medication reminders, monitor symptoms, and even send alert to caregivers and doctors when something is off. With AI-enabled wearables, VHAs can handle routine tasks, guide the elderly through their appointments, refill prescriptions, and reduce the burden on caregivers.
- AI-augmented telehealth platforms: Telehealth platforms leverage the latest technological infrastructure, including AI, to connect the elderly with doctors and healthcare providers remotely, improving access to elderly healthcare, while reducing healthcare costs. Through online video consultations and monitoring devices, doctors are able to diagnose and treat patients remotely, which is especially helpful for seniors in rural or underserved areas.
- AI/ML modelling in personalised medication: AI–and ML–based modelling has brought personalised medicine from the realm of fiction into reality. Having successfully predicted stem cell differentiation, cell fate, and gene expression using algorithms trained on pre-clinical and clinical studies, AI/ML modelling is fast advancing personalised medicine for the elderly and could soon lead to widespread personalisation for all patients.
Real World Applications of AI in Elderly Healthcare
AI solutions developed for elderly healthcare are already redefining elderly care and improving their quality of life. Here are a few examples of how healthcare providers are leveraging AI to serve the needs of the elderly:
- Intuition Robotics’ ElliQ, an AI companion robot: ElliQ by Intuition Robotics is an AI-based companion robot that is designed to provide emotional support and companionship to older adults while also monitoring their health. Now in its third generation, the empathetic robot proactively engages with the elderly, stimulates cognitive function, suggests activities, initiates conversations, sends health updates to caregivers, and fosters a sense of independence among the elderly. Similarly, AI robots are being used in elder care facilities in Japan to provide emotional support and monitor health metrics. These robots help reduce caregiver burden and ensure seniors receive constant attention.
- Anvayaa Kin C
are (India) and Cera Care (UK): Senior care providers like India’s Anvayaa Kin Care and UK’s Cera Care are leading from the front in AI-driven personalised elderly care. The integration of AI is enabling these digital-first home healthcare services to assist the elderly with health, emergency, and daily care needs. - AgeWiser: An AI-driven wellness app for seniors, AgeWiser provides personalised support to the elderly, offering a holistic approach for care and wellness that focuses on improving cognitive health and mobility. Such AI-powered apps also detect abnormalities in exercise patterns, aid in early anomaly detection and intervention, and promote wellness among older adults.
- CarePredict: A digital health platform, CarePredict combines AI-driven solutions, advanced analytics, and remote sensing technology to continuously monitor seniors’ health. Its AI-powered wearable devices and home kits track daily activities, identify signs of early decline, and enable caregivers to intervene before conditions worsen.
Navigating the Challenges of AI Adoption in Healthcare
While AI is being infused into healthcare in many forms and becoming increasingly pervasive, healthcare providers must address several challenges to ensure its safe and ethical use.
- Securing sensitive patient data: Safeguarding patient data is the biggest challenge for healthcare providers adopting AI-driven solutions. Since AI relies on sensitive patient data to personalise solutions, healthcare providers must implement strong encryptions, regularly perform security audits, and limit access to prevent breaches.
- Addressing AI algorithm bias: Biases in AI’s training data can compromise care quality and undermine faith in healthcare providers. Tackling them requires diversifying development teams, addressing biased data samples, auditing AI systems for fairness, and ensuring human oversight in sensitive cases.
- Bridging the digital divide: Many seniors struggle with accessing or using AI-driven healthcare solutions. To bridge this digital divide, healthcare providers and caregivers need to educate the elderly on the benefits of AI-powered healthcare solutions, provide hands-on training and support, and involve their families in the process.
Smarter Future for Senior Healthcare and Wellness
Although not a panacea for all the challenges of our age, AI is an invaluable catalyst for change and transformation that healthcare systems need to meet the growing demands of elderly care. Be it advanced predictive modelling, AI-powered wearables, telehealth platforms, or companion robots, AI-driven solutions are changing every facet of elderly care. Not only are they preventing illnesses and reducing hospitalisations, but they’re also cutting down on healthcare costs, improving accessibility to healthcare in underserved regions, and turning once-speculative concepts like personalised medicine into reality.
As traditional healthcare services continue to bear the brunt of a rapidly aging world, AI-led digital interventions can breathe new life and transform elderly healthcare for the better. Healthcare providers must also address concerns surrounding AI adoption in the industry. AI is not here to replace human caregivers – it's here to empower them. With the right approach, AI solutions can make healthcare more efficient, affordable, and accessible for our aging population. At the same time, collaboration between governments, healthcare providers, and tech companies will be key to ensuring AI solutions are both ethical and accessible.
At Infosys BPM, we help healthcare providers integrate AI and GenAI into their services and make healthcare services for the elderly more efficient, affordable, and accessible. Get in touch with our team today and navigate your next responsibly.
