Inside the Growing Role of Artificial Intelligence in Supporting Older Adults with Luka Zrnic

As populations age and healthcare systems face mounting strain, artificial intelligence is increasingly being explored as a tool to support older adults, caregivers, and long-term care models. Luka Zrnic, a healthcare and technology strategist with a background in gerontology and digital health, has worked across private, public, and non-profit sectors on aging, longevity, and AI-enabled care initiatives. In this interview, he discusses how AI is beginning to reshape senior care, from preventative health and home-based support to emerging assistive technologies. He outlines the opportunities and design challenges that will define the next decade of AgeTech innovation.

1. Your work sits at the intersection of aging, technology, and healthcare strategy. How do you see AI reshaping the way society supports older adults over the next decade?

AI will be transformational for senior care – both in terms of direct impact and as an enabler of emerging technologies. This will be borne out of necessity due to demographic trends (by 2034, the US is expected to have more people aged 65+ than children), which is creating an increasingly severe caregiver crisis, adversely impacting both seniors and caregivers.

When considering direct impact, AI has the potential to ease the ever-widening caregiver shortage and reduce the cost burden, including by automating administrative tasks and by partially moving chronic disease management upstream (i.e., from labor-intensive and costly later-stage illness to prevention and early management). 

In terms of leveraging AI as an enabler, AI is the foundation for emerging technologies that will bridge software and the physical world – particularly assistive robotics – which will be pivotal in senior care due to the improbable scenario of an organic surge in caregiver supply.

2. You have a background in gerontology and digital health. What gaps did you see in aging-related care and technology before the rise of modern AI tools, and why were those gaps so difficult to close?

Technology hasn’t been lacking in functional capability. The real barrier is low adoption and retention, driven by three key factors:

• Low perceived value vs. cost: Seniors often did not see benefits clearly outweighing the required effort and monetary cost of the new devices
• Relatively low confidence with technology: Many seniors, particularly in past generations, lacked the digital literacy and/or confidence for effectively using technology 
• Suboptimal and stigmatizing design: Products often felt “medicalized” and/or patronizing, reflecting a misunderstanding of seniors’ needs / wants and basic human psychology

The recent proliferation of LLMs is expected to close accessibility gaps for users with low technical savviness, with increasingly advanced voice AI capabilities (which are approaching human-like interaction) playing a leading role.

3. As someone who works across private, public, and non profit sectors, what early uses of AI in AgeTech do you believe are already improving day to day quality of life for older adults?

As we are witnessing a significant shift from institutional to home-based care models (seniors prefer to age at home and payers are aligning incentives to reduce cost), there is significant traction in technologies enabling this paradigm shift by minimizing risks in home environments (to improve health outcomes and reduce hospital re-admissions) and by easing at-home care friction (by streamlining scheduling and reimbursements for home care).

4. Many people think of AI in terms of software, but you have also looked at technology that connects digital intelligence with physical assistance. How do you see AI enabling future hardware such as in home support tools or caregiving robots?

Fall monitoring and prevention devices have been in the market for a long time and are already creating a positive impact. They are climbing up the penetration curve – increasingly used in institutional settings and gradually spreading through households. It’s a matter of time before they become mainstream, given the devastating impact of falls (more than a quarter of seniors fall each year and the second- / third-consequences are often devastating). AI will continue to improve accuracy and usefulness, in turn driving adoption.

Technologies such as caregiving robots will be transformational, but are still far from mainstream adoption given functional and affordability constraints. However, AI is already creating a pull-forward effect and toda,y 10-20 years seems plausible for mass consumer adoption. Given structural, intractable challenges (i.e., demographic / workforce dynamics) and despite the need to always prioritize human contact, these technologies will play a pivotal role in both quantity and quality of care.

5. What role do you think AI can play in helping older adults maintain independence, whether through personalized care plans, smart home environments, or proactive health monitoring?

When thinking from first principles, independence largely hinges on three key things: basic activities of daily living, general self-management and care, including medical adherence, and safely moving through space while minimizing risks (of falls for all seniors and of getting lost for seniors with cognitive impairment). 

As AI increasingly shifts from reactive chatbots (asking a question and the LLM responds) to proactive AI agents (completing end-to-end tasks at specified times), AI will increasingly act as an extension of the care team (not a replacement but rather a complement/multiplier). The agent use cases will range from anomaly detection (e.g., mobility decline / gait changes) to medical adherence (e.g., reminders for lifestyle habits and medicine intake).

6. From your work in public health and longevity-oriented care, where do you see the greatest potential for AI to improve health outcomes for aging populations on a large scale?

Longevity has two components – the number of years a person lives (lifespan) and the proportion of those years spent in good health (healthspan). Healthspan is the most critical as it means quality of life. However, most people do not prioritize health until a serious illness occurs. Although it’s never too late to start, optimizing healthspan ideally starts at an early age. 

AI has a significant role to play in driving primary prevention (preventing diseases before they begin), secondary prevention (diagnosing diseases early to prevent or reverse progression), and tertiary prevention (curing diseases or halting progression). As a large share of chronic disease is preventable by addressing behavioral risk factors, AI has an unprecedented role in increasing health access by offering everyone personalized support (with the caveat that this requires a strong focus on social determinants of health to enable adoption).

7. Trust and accessibility are key issues in any technology used by older adults. Based on your experience, what design principles should innovators prioritize to make AI powered tools truly helpful and easy to adopt?

Universal design will be increasingly necessary as our population rapidly ages. On the one hand, accessibility needs to be fostered by deeply understanding the common issues of seniors, especially hearing, vision and dexterity challenges. On the other hand, adoption hinges on designing for attractiveness vs. fostering a feeling of incapability and patronization. 

To foster trust in AI technologies, satisfying three key pillars will prove foundational: reliability, simplicity and data security. Churned users of AgeTech are unlikely to re-adopt technology – once trust is broken, it is difficult to re-establish.

8. Looking ahead, what developments in AI driven AgeTech are you most excited about, and how do you think they will redefine aging and long term wellbeing?

In the short term, I’m most excited about proven tools that help accelerate de-institutionalization and drive better health outcomes, such as fall detection and prevention. In the long term, autonomous technologies (AI agents / humanoid robots) will be a non-negotiable necessity to deliver the right level of care at scale.