This session will explore how tools such as AI-driven monitoring systems, predictive analytics, digital care planning platforms, and assistive technologies can potentially enable more proactive, personalized, and efficient care for older adults and people with complex needs. Participants will examine examples of technologies that are being designed and deployed to reduce staff burden, improve safety, support early intervention, and strengthen communication among care teams, residents, and their families.
At the same time, the session critically addresses the practical and ethical challenges that accompany digital transformation in long-term care settings including data privacy and cybersecurity, algorithmic bias, transparency and accountability in AI-supported decision-making, and the risk of technology undermining human relationships in care. Practical barriers such as cost, infrastructure limitations, interoperability, staff training, and digital literacy among users will also be discussed. Special attention will be given to consent, autonomy, equity, and the inclusion of residents, staff and caregivers in technology design and implementation.
This session aims to equip leaders, clinicians, and policymakers with a grounded understanding of how AI and digital technologies can be adopted thoughtfully and sustainably - enhancing care without compromising trust, dignity, or resident-centered values in long-term care environments.
Learning Objectives:
At the completion of this session, learners will be able to:
Identify and evaluate key AI and digital technology applications in long-term care settings, including their potential benefits, limitations, and appropriate use cases for improving care quality and operational efficiency.
Analyze the practical, ethical, and legal challenges associated with implementing AI and digital technologies in long-term care settings, with particular attention to privacy, consent, bias, equity, and the preservation of resident-centered care.
Apply a structured framework to inform responsible decision-making about technology adoption, including stakeholder engagement, implementation readiness, and strategies to balance innovation with trust, dignity, and resident autonomy.
