The Future of Long-Term Care in the Age of Artificial Intelligence

Abstract:

Artificial intelligence (AI) is transforming industries, and long-term care is no exception. With the advent of large language models and agentic (capable of achieving independent outcomes) AI, aging services providers must rapidly adapt to harness benefits while mitigating risks. This article explores the latest advancements in AI, the importance of data readiness, opportunities to enhance care and workforce efficiency, and challenges and ethical considerations providers must navigate. As the window to define responsible AI use in long-term care narrows, the sector must take proactive steps to ensure these technologies serve older adults with dignity and effectiveness.

Key Words:

artificial intelligence, long-term care, AI ethics, elder care, workforce, data driven care, AI adoption, agentic AI 

Artificial intelligence (AI) has moved from a futuristic concept to an everyday reality. Large language models (LLMs), such as OpenAI’s GPT, Google’s Gemini, and Anthropic’s Claude, demonstrate AI’s ability to process vast amounts of information, generate human-like responses, and assist with decision-making. AI’s presence in healthcare is rapidly expanding, with applications ranging from predictive analytics to personalized care planning, and will continue to accelerate processes including advanced research and pharmaceutical testing.

In long-term care, where increasing demand, staffing shortages, and changing payment models create pressure, AI offers a compelling opportunity to improve efficiency, enhance resident outcomes, and empower care teams. However, as AI adoption accelerates, aging services providers must understand its capabilities and limitations to ensure responsible and effective implementation.

Recent Advancements in AI

In late 2022, the world was introduced to ChatGPT, a remarkable tool with access to a vast wealth of digital information. GPT stands for “Generative Pre-Trained Transformer”—generative being the operative word. At the time, the tool was very good at generating content like text, photos, and even videos. Competition emerged for ChatGPT and the tools’ capabilities continued to mature.

As 2024 drew to a close, the world was introduced to the emergence of “agentic AI”—systems capable of reasoning, making decisions, and autonomously completing complex tasks.

Imagine that in 2022, if a person wanted to see a concert by their favorite musician, they could use AI to generate information about tour schedules, locations, and venues. In just 2 years, those same tools can not only present the user that information, but buy tickets to the concert, book a hotel, and make dinner reservations. The intelligence is transactional, or “agentic,” and able to reason much like a human can.

These AI models can integrate with enterprise applications (large-scale software systems designed to manage and automate core business processes in an organization, including electronic health records) to generate care recommendations, and even automate aspects of clinical and administrative workflows.

Key advancements driving AI adoption in long-term care include:

• Enhanced Natural Language Processing (NLP): AI can interpret unstructured text from physician notes, resident care plans, and family communications.
• Predictive Analytics: Machine learning models can identify at-risk residents, allowing for early intervention in falls, pressure ulcers, and cognitive decline. This may be via electronic health records, point-of-sale resident engagement, CRM (customer relationship management) or via wearables, smart-home devices, access controls, etc.
• AI-Powered Virtual Assistants: Conversational AI tools provide 24/7 support for residents and staff, offering medication reminders, companionship, and administrative assistance.
• Computer Vision AI: Can collect a host of data points with completely contactless encounters via optical sensors (cameras) to synthesize data points. From detecting falls to measuring gate, and even collecting biometric vital information, these tools have significant use cases in a long-term care environment.
• Voice AI Assistants: Voice AI assistants like “Alexa” have been around for some time. But as Amazon announced in February 2025, Alexa will gain the Anthropic LLM and become “Alexa+.” Alexa+ will be a supercharged version of Alexa, creating significant opportunities for older adults to converse with AI. Imagine an Alexa device that is able to remind residents to take medication, perform tasks for them, and even serve as a meaningful social companion.
• Automation in Administrative Tasks: AI-driven scheduling, documentation, and claims-processing reduce staff burden, allowing caregivers to focus on resident interaction.

These advancements signal a paradigm shift in how long-term care providers must think about data and AI readiness.

Data Readiness: Positioning Aging Services for AI Integration

To leverage AI effectively, aging services providers must first assess their data landscape. AI thrives on high-quality, structured data, yet many organizations struggle with siloed, inconsistent, or incomplete datasets. Tools like ChatGPT are very eager to answer questions or complete tasks, but without contextual data, those answers and tasks may provide false or misleading information (known as “hallucinating”), causing undesired results. Providers hoping to capitalize on the promise of AI should be laying foundations for presenting their data to AI today. The following steps are critical:

• Standardizing Data Collection: Ensuring resident records, care plans, and operational data are structured and accessible.
• Integrating Systems: Bridging gaps between electronic health records, remote monitoring devices, and workforce management systems to create a holistic data ecosystem. This opportunity is significant, particularly in aging services. Nearly all other healthcare delivery is episodic in nature, giving providers a quick glimpse into a patient’s health. Long-term care, senior living, and other elements of aging services have a unique opportunity to perpetually collect data on residents. AI will benefit from the vast amounts of data available to it and be able to detect trends or anomalies in the data.*
• Implementing Data Governance: Establishing policies for data accuracy, privacy, and security to maintain compliance and ethical AI use.

* Ethically, it would be wise on the part of the providers to share with residents or those who hold power of attorney what information is being collected and how it will be used.

Organizations that prioritize data readiness will be well-positioned to harness AI’s full potential.

Opportunities for Aging Services Providers

AI presents transformative opportunities for aging services providers, particularly in two key areas:

From Reactive to Proactive, Wellness-Focused Care

The use of data and AI supports hyper personalization for person-centered care, relationship-based sales (i.e., building trust and connection prior to offering solutions), and team member engagement. It will give aging services providers uncanny insights into the products that provider organizations develop, the services they provide, and the experiences they create.

Healthcare as we know it will become significantly more personalized, preventive, holistic, service-rich, and outcomes-based. AI will accelerate modern medicine, too. Clinicians will be able to simulate the impacts of treatments, medications, and strategies to discern the most effective outcomes.

It is very likely that entire generations of people will begin to live for a longer period of time as a result of these advancements in healthcare (many articles have been and will continue to be written about the economic impacts of people living well past 100). AI will help healthcare providers with early disease detection, personalized wellness plans, and AI-driven remote monitoring tools. Traditionally, long-term care operated reactively, treating conditions after they had manifested. The ways in which AI enables a proactive, wellness-focused model is discussed below.

Addressing Workforce Challenges

The aging services sector faces significant compression with workforce challenges. These workforce challenges are at least partially due to an increased demand for services for Baby Boomers, due to their large cohort size. But AI is offering a new type of worker, the “digital agent.”

Digital agents will be autonomous participants in the workforce for nearly every organization and will work collaboratively with human counterparts. These digital agents will be very effective at handling routine automated tasks like documentation, scheduling, compliance reporting and other administrative burdens. Digital agents also will leverage AI for care coordination, providing the right data to the right caregiver at the right time to ensure seamless continuity of care between caregivers, nurses, therapists, and physicians.

In the tech sector, there exists the concept of a “digital twin.” A digital twin is formed by using all the available data to create a “twin” of a person, building, or scenario and then being able to simulate effects of actions against it. For example, the digital twin of a building could enable the simulation of a weather event against the real building; likewise, digital twins could allow simulations of the impact of staffing ratios against a population of people. When the potential applications of digital twins combine with agentic AI and contextual retrieval (the sharing of data from a data warehouse), this combination will produce meaningful digital agents for completing tasks and automating workflow. Many of the “behind the curtain” activities that happen in aging services will be augmented by digital agents freeing up workforce members to be present and engaged in resident interactions to enhance job satisfaction and outcomes.

Challenges in AI Adoption

Despite AI’s promise, long-term care providers will encounter challenges during its adoption, including:

• Resistance to Change: Staff and leadership may be hesitant to trust AI-driven decision-making.
• Data Privacy & Security: Ensuring compliance with HIPAA and safeguarding resident information from breaches or misuse is complex.
• Technology Integration: Aligning AI tools with legacy systems and workflows without disrupting care delivery may present an obstacle.
• Cost & Return on Investment (ROI) Concerns: Upfront investment in AI infrastructure may be a barrier for some organizations, requiring careful financial planning.
• Workforce Disruption: As more people recognize the impact AI will have on their roles and responsibilities, there will be more resistance to using it.

Potential Pitfalls of AI in Long-Term Care

While the capabilities of AI paint a picture of positive impacts on aging services, there are some caveats.

Yes, LLMs are getting better and better with every incremental release, but there remains a risk that the model can hallucinate, or that there may be bias within the model. As these technologies are employed in workflows, human oversight will become critical, as will accountability for the result(s) AI is augmenting.

The challenge for everyone involved in this evolution will become dependency. AI is on a fast track to becoming general intelligence that will soon surpass the intelligence of human beings (if it has not done so already). The AI we use today is the worst AI we’ll use for the rest of our lives. It will become very natural for humans to become “lazy thinkers” and trust the AI.

AI will accelerate capabilities of physical robotics. Incremental advancements in robotics over the past few decades will be exponentially accelerated by applying AI. Robots will be able to discern, think, and interact with our lives in ways never before seen.

Yet, in aging services, the foundational value of the service we provide is meaningful social and emotional connection. If we’re intentional about the way we use AI, we can create efficiencies that allow us to lean into our greatest proposition—not automate it. My hope is that we can responsibly embrace AI to enhance care, improve outcomes, and strengthen the relational and social dimensions of our work. I believe in a future where technology supports, rather than dictates, the rhythm of daily life—where digital agents do not micromanage every minute, but instead enable people to live with greater dignity, independence, and connection.

As with so many new technologies, the regulatory landscape for AI in healthcare is evolving. It will require aging services providers stay informed and adaptable, both to the technology and the regulations. Proactive governance and ethical AI frameworks are essential to mitigate these risks. While the opportunity for responsible innovation is significant, there is also a very real risk that if aging services providers don’t lead with thoughtful, values-based implementation, others may define AI’s role in ways that don’t prioritize resident well-being. Large, corporate-owned providers, in particular, have not always been recognized for centering residents’ best interests. This makes it all the more urgent for mission-driven organizations to take the lead in shaping an ethical, person-centered future for AI in aging services.

The Shrinking Window to Define Responsible AI Use

The aging services sector has limited time in which to shape how AI is integrated responsibly. If providers do not take the lead in defining ethical AI use, technology companies, regulators, or external stakeholders may dictate the terms instead. To ensure AI aligns with the values of long-term care, organizations must:

• Develop AI Governance Committees: Establish interdisciplinary teams to oversee AI strategy, ethics, and implementation.
• Engage with Policymakers: Advocate for regulations that support innovation while protecting vulnerable populations.
• Educate Staff and Residents: Promote AI literacy to build trust and transparency in its applications.

By proactively embracing AI while safeguarding resident dignity and well-being, long-term care providers can position themselves at the forefront of responsible innovation.

Conclusion

Artificial intelligence is poised to reshape long-term care, offering unprecedented opportunities to enhance wellness, improve efficiency, and address workforce shortages. However, successful adoption requires thoughtful preparation, ethical considerations, and a commitment to maintaining the human element in care. As AI continues to evolve, aging services providers must act now to ensure these technologies serve older adults with respect, compassion, and effectiveness.

Joe Velderman is vice president of Innovation for Cypress Living in Fort Myers, Fla., and  leads technology and innovation initiatives in aging services. He serves on the advisory council for the State of Florida Health Information Exchange (HIE) Committee under the Agency for Health Care Administration.

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