Chronic disease and population ageing are placing unprecedented pressure on health systems worldwide. These challenges are compounded by a maldistribution of the healthcare workforce, rising clinician burnout, and the increasing cost and time required to train health professionals. At the same time, population movement—through migration, career changes, and shifting demographics—further strains an already fragile system. Against this backdrop, artificial intelligence and digital technologies are often presented as transformative solutions. Yet the promise of AI in healthcare can only be realised if it is implemented thoughtfully, ethically, and in partnership with those who deliver and receive care.
This keynote explores the opportunities and tensions at the intersection of AI, healthcare delivery, and chronic disease management. While digital tools have the potential to support earlier diagnosis, personalised care, and more efficient health systems, their successful adoption depends on more than technological capability. A sustainable future requires an affordable healthcare system, a digitally literate workforce, and genuine co-design involving clinicians, technologists, and people with lived experience of illness. Patient-centred design, diverse community representation, and collaborative development must underpin the creation, implementation, and evaluation of new tools.
Significant barriers remain. Healthcare professionals receive limited training in digital technologies, while cultural differences between medicine—grounded in accountability and patient care—and the commercial technology sector can undermine trust. Interoperability between health systems remains poor, administrative burden continues to rise, and many digital tools enter the market without the level of regulatory scrutiny applied to medicines or medical devices. Questions also persist around cybersecurity, data sovereignty, and the secondary use of health data. The rapid growth of AI, including large language models, raises further concerns regarding reliability, safety, and the risk of convincing but incorrect outputs.
Beyond technical considerations, forced or poorly implemented technological change can increase clinician distress and hinder adoption. Meaningful integration of AI requires ongoing relationships between developers and healthcare systems, continuous training, and a commitment to lifelong learning among clinicians. Rather than a “set-and-forget” approach, digital transformation must be iterative, responsive, and supported by sustained dialogue between stakeholders.
This keynote will examine what is working today, what remains uncertain, and what is required to ensure AI improves health outcomes—particularly for people living with chronic disease. Ultimately, the goal is not to replace clinicians but to enable them to spend more time doing what matters most: building therapeutic relationships, applying clinical judgement, and delivering compassionate care. Ensuring that AI strengthens, rather than fragments, the healthcare system will require rigorous evaluation, strong governance, and a shared commitment to equity, safety, and trust.
