By: Angelica Burlaza
As advanced economies age and growth forecasts dim, one CEO argues that the key to protecting productivity may lie not only in pensions, robots, or immigration policy, but also in how we design future buildings and integrate artificial intelligence into everyday spaces.
Dr. Eric Balki, an AI and aging expert who is also the CEO and Chairman of TriPyramid Group, which, amongst its portfolio, has healthcare and technology companies, and serves as an honorary research fellow at Lancaster University, has recently authored a comprehensive Research Paper calling on the World Health Organization to update its influential Age-Friendly Cities and Communities model. The WHO framework currently encompasses eight domains, ranging from transportation and housing to social participation and community support.
Dr. Balki proposes adding a ninth domain, Technology and Artificial Intelligence, explicitly recognizing intelligent systems and built environments as core infrastructure for aging societies.
“We’ve treated technology as an add-on rather than a structural feature of age-friendliness,” he argues. “That no longer matches the reality of how people live, work, and age, especially with improving life expectancies.”
Dr. Balki’s path into this debate is quite broad. He has an academic background spanning Physics, Information Management, Law, and Finance, capped by a PhD in Aging and Longevity. Professionally, he straddles both research and application. That mix of disciplines informs his central claim: an aging population, if left unaddressed, will put pressure on GDP and labor markets in Western economies, a concern widely echoed in mainstream economic research.
Recent analyses from international institutions have similarly warned that aging populations will slow output growth unless offset by higher productivity, longer working lives, or new technologies. Dr. Balki reimagines this problem, focusing on how architecture and AI might help offset it.
The WHO’s age-friendly framework already emphasizes outdoor spaces, transportation, housing, and buildings. However, in most applications, these domains are still treated as static, including ramps, benches, lighting plans, and transport routes.
Dr. Balki argues that this static approach in the age of AI is no longer sufficient for societies where older adults are expected to remain active in the labor force for longer and in cognitively demanding roles. As governments are forced to increase retirement ages, there is a need for a paradigm change, he argues.
He outlined the role AI can play, helping older adults stay productive as a “digital partner” that reduces cognitive and physical load. AI agents can summarize long documents, draft emails, prepare reports, and structure meetings, thereby helping with information overload and administrative work. AI tutors and adaptive learning platforms can personalize training materials, adjust pacing, use more precise language, and provide instant explanations, making them ideal for returning to learning.
Employer initiatives, such as internal learning platforms, skills-based talent management, and “reverse mentoring” between younger and older staff, could use AI to track skills transfer and suggest tailored learning paths, thereby opening new roles rather than pushing older people out.
AI can also help with smarter matching between volunteers and roles by analysing volunteers’ skills, interests, availability, and location, and matching them to an organization’s needs. In these fitting roles, someone’s experience will really matter, not just “any open slot.”
AI and digital tools can also enable remote or micro-volunteering, which is ideal for those with limited mobility or energy, such as editing documents, mentoring online, assisting with translations (with AI support), moderating forums, or completing short “micro-tasks” from home. Moreover, AI translation and transcription can make it easier for older volunteers to work across languages or with hearing difficulties.
Lifelong learning and digital skills are now seen as essential to healthy aging and participation. UNESCO and others explicitly discuss lifelong learning for older adults, particularly in relation to digital skills and bridging the “digital divide.” AI can make those learning environments much more age-friendly by adjusting difficulty, speed, and format based on how someone is doing: more visuals, more repetition, or step-by-step guidance if needed.
For individuals with vision or hearing impairments, AI can adapt content into larger text, provide audio descriptions, or add captions without requiring a separate human intervention. Together, these features make it far more realistic for older adults to reskill for new work, learn for volunteering roles, or just study for personal interest.
Dr. Balki described these as “AI-enabled environments,” designed to be cognitively responsive to older adults. Offices, healthcare facilities, and public buildings use sensors and AI models to adapt in real time to the needs of aging users. This may include systems that help with older adults’ working memory, as well as spatial layouts and wayfinding designs that ease navigation and reduce cognitive load, aided by digital prompts and adaptive signage. The goal, he says, is not simply comfort or accessibility, but preserving cognitive performance in later life and thereby extending productive working years.
In Dr. Balki’s mind, AI is not a gimmick but a technology that will transform design for these environments. Rather than tracking individuals in a granular or invasive way, he envisions AI systems that work largely at the level of patterns and conditions: identifying when particular task types, times of day, or environmental configurations correlate with drops in performance or higher error rates among older workers, and then adjusting the environment accordingly. In principle, such systems could help organizations assign cognitively appropriate workloads, optimized for individuals, and remove environmental stressors in workplaces, clinics, or senior housing that may contribute to early exit from the labor force.
Balki frames this as a natural evolution of the WHO’s existing domains of “outdoor spaces and buildings,” “communication and information,” and “community support and health services,” arguing that intelligent systems now sit at the intersection of all eight domains.
Dr. Balki is passionately calling for Technology and AI to be formalized as a separate domain in the WHO’s age-friendly framework, rather than being treated as an implicit cross-cutting theme.
He suggests the new domain could cover, among other things:
- Standards and guidelines for AI-assisted age-friendly design in workplaces, homes, and public spaces.
- Ethical and privacy principles for data used to adapt environments for older adults.
- Integration of digital tools into national and local age-friendly strategies, alongside transport, housing, and health.
The idea would not replace the existing eight domains, but reframe them through a technological lens. For example, seeing transportation as not just physical networks, but digitally coordinated systems that help older adults plan, navigate, and adapt to changing conditions.
Demographic trends are not in dispute. Many high-income countries are already dealing with shrinking working-age populations and rising old-age dependency ratios.
Where the debate remains is how much technology and environmental design can realistically offset the macroeconomic drag. While technologies like artificial intelligence can boost productivity, they likely won’t be enough on their own to counter all the economic challenges caused by rapidly aging populations.
Dr. Balki acknowledged these limits but argued that ignoring the integration of AI and technology into built environments leaves noticeable gains on the table. In his view, age-friendliness should extend beyond access ramps and social programs to encompass measurable cognitive and economic outcomes, including the ability of older adults, if they choose, to remain productive in knowledge-intensive roles.
The systematic transformation of architecture and space enabled by AI and technology has the potential to partially offset the decline in GDP caused by labor shortages linked to aging populations. The exact scale of that impact, he notes, will depend on adoption, investment, and policy; however, he has demonstrated the use of advanced statistical models, utilizing large-scale computing, which indicate that this could result in a 0.8-1.4% increase in the USA and a 1.2-1.6% GDP increase in the UK.
The WHO Age-Friendly Framework, first developed in the mid-2000s, helped cities and countries structure their responses to aging around eight concrete domains of liveability.
Dr. Balki’s call for a ninth domain comes at a time when aging is increasingly framed not only as a social and health issue but also as a question of competitiveness and productivity. Governments, multilateral lenders, and think tanks are all publishing analyses on the economic implications of demographic change and the potential role of technology in response (IMF).
Whether his specific proposal, to place Technology and AI in the WHO’s age-friendly canon, gains traction remains to be seen. However, the underlying question he raises is likely to persist: if aging populations threaten to slow GDP growth and strain labor markets, how far can smarter environments, guided by AI, help mitigate this trend?
For Dr. Eric Balki, at least, the answer starts with treating architecture not as a backdrop to aging, but as an active tool for reshaping its economic impact.
