Staying Spry with the Help of AI

Artificial intelligence (AI) is transforming the way older adults experience healthcare and daily life. One of the most visible trends is the growth of AI-powered social companions that help seniors stay connected and engaged at home. For example, ElliQ, an AI companion robot developed by Intuition Robotics, uses conversational prompts and personalized reminders to help older adults with medication, activity suggestions, and social interaction while fostering independence and reducing feelings of isolation. Programs deploying ElliQ have shown high levels of engagement and reduced loneliness among senior users.

Some of these platforms are delivered on familiar devices such as Smart TVs, with conversational AI that can offer medication reminders, memory games, simple calls with loved ones, and casual conversation for seniors who are challenged with seemingly ‘complex’ devices like traditional smartphones or apps. Users often interact with these AI companions daily for wellness check-ins, social engagement, and reminders to stay active.

 

A Friendly Chat as a Health Check

In addition to robots, chat- and voice-based companions built with natural language AI are advancing conversational engagement for cognitive support. These systems are designed to be accessible and intuitive, lowering the technical barrier for older adults and helping monitor subtle changes in cognition while providing everyday interactions that support mental engagement. (Research in machine learning (ML) for cognitive assistance and conversational AI underscores the potential for such tools, though specific commercial data on products like QuikTok remains emerging.)

 

AI Checking a Sore Spot

AI is also extending into remote monitoring for wound care and chronic health conditions. Research tools like WoundAIssist enable patients to use smartphones to document wounds with photos, and the system applies AI to help clinicians monitor healing progress and flag potential complications. This type of telehealth application can reduce unnecessary in-clinic visits, particularly valuable for older patients with mobility challenges.

 

Care to Share with AI?

Beyond direct care tools, AI is beginning to support workflow changes in clinical care and treatment development. In Utah, the first state-level pilot program now allows an AI chatbot to autonomously renew routine prescriptions for certain non-controlled medications under careful oversight, reducing clinician burden and potentially improving access for patients with chronic conditions.

In drug development and clinical trial design, the U.S. Food and Drug Administration (FDA) recently qualified the first AI tool specifically for liver disease treatment development, indicating broader regulatory acceptance of predictive analytics to design more efficient and targeted clinical studies.

 

AI + PHI = Dx

AI’s role in medicine also includes connected devices and diagnostics. The FDA maintains a list of AI-enabled medical devices that have met regulatory requirements for safety and effectiveness, and machine learning-driven diagnostic tools now span domains ranging from imaging to cardiology.

One example of diagnostic AI is the Aidoc CARE1™ Foundation Model, which has achieved FDA clearance for clinical use and represents a new generation of AI that assists radiologists by detecting and triaging critical findings rapidly, helping clinicians focus on urgent cases.

These innovations occur alongside evolving regulatory frameworks. The FDA’s comprehensive draft guidance on AI-enabled device lifecycles sets expectations for transparency, performance monitoring, and safety throughout development and post-market activity, emphasizing that AI tools must be evaluated continuously as they are used in real clinical environments. The agency has also issued requests for public comment on measuring real-world performance of AI medical devices to strengthen oversight and ensure safety after deployment.

Other healthcare trends involving AI include predictive health analytics that use large datasets to identify risk factors for major diseases. For example, recent research has shown that sophisticated models trained on sleep study data can predict long-term risk for many conditions common in aging populations — including dementia and heart disease — by analyzing physiological signals from a single night’s sleep.

 

May AI Help You?

Finally, virtual AI assistants integrated with wearable devices can help with appointment scheduling, symptom triage, medication adherence support, and passive monitoring, improving care coordination and chronic disease management for older adults. (Multiple reports on machine learning use cases in healthcare outline these functions and the potential for better patient engagement and outcomes.) 

AI has the potential to improve access and continuity of care, enhance early diagnosis, support chronic condition monitoring, and drive smarter drug development. At the same time, robust oversight and continuous evaluation will be essential to ensure that these tools deliver safe, equitable, and meaningful benefits for older adults and the broader healthcare system.

 

 

How do You Manage Risk with AI? With Duty of (Patient) Care.

To successfully approach managing risk in the age of AI, organizations that use tools and devices with AI should incorporate reasonable security into their risk strategy.

Establish reasonable security through duty of care.

With HALOCK, organizations can establish a legally defensible security and risk program through Duty of Care Risk Analysis (DoCRA). This balanced approach provides a methodology to achieve reasonable security as the regulations require.

 

 

Review Your Security and Risk Posture

 

 

References

Broadbent, E., et al. “ElliQ, an AI-Driven Social Robot to Alleviate Loneliness.” Journal of Aging Research & Lifestyle, 2024. (Wikipedia)

“ElliQ | Companion Robot for Seniors, Older Adults & Aging.” ElliQ.com. (ElliQ)

“ElliQ Proactive Care Companion Initiative.” Office for the Aging, New York State, 2025. (Office for the Aging)

Hagen, J. “Utah Allows AI to Renew Prescription Drugs Autonomously.” MobiHealthNews, Jan. 6, 2026. (MobiHealthNews)

“Utah Launches First-in-the-Nation Trial That Lets AI Renew Your Prescription.” The Washington Post, Jan. 8, 2026. (The Washington Post)

“FDA Issues Comprehensive Draft Guidance for Developers of Artificial Intelligence-Enabled Medical Devices.” U.S. Food and Drug Administration, Jan. 6, 2025. (fda.gov)

“Artificial Intelligence-Enabled Medical Devices.” U.S. Food and Drug Administration. (fda.gov)

“Request for Public Comment: Measuring and Evaluating Artificial Intelligence-Enabled Medical Device Performance in the Real World.” U.S. Food and Drug Administration, 2025. (fda.gov)

“Aidoc Secures Landmark FDA Clearance for Foundation Model AI Solution.” Aidoc, 2025. (Healthcare AI | Aidoc Always-on AI)

“FDA Approves First AI Tool for Liver Drug Development.” Reuters, Dec. 9, 2025. (Reddit)

Robbins, J. “Health Rounds: AI Uses Sleep Study Data to Predict Health Risks.” Reuters, Jan. 7, 2026. (Reuters)

Multiple sources on machine learning use cases in healthcare, including virtual assistants and wearable integration.

 

Penetration Testing for Healthcare Organizations

 

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Review Your Security and Risk Posture

 

 

Be Our Guest at FutureCon Chicago 2026

Enjoy breakfast and lunch while connecting with colleagues and industry executives.

Session: Why AI Can’t Fix Your Cyber Risk (and Might Be Making It Worse)

Speaker: Chris Cronin, ISO 27001 Auditor |  Partner, HALOCK and Reasonable Risk  |  Board Chair, The DoCRA Council

DATE: Thursday, January 29, 2026

WHERE: Live In Person | Virtual | Hybrid @ Chicago Marriott Oak Brook

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