AI for All Must Mean Health for All: Why Canada’s AI Strategy Needs a Public Health Roadmap

Canada’s renewed AI for All strategy marks a welcome shift from investing primarily in artificial intelligence research towards accelerating its responsible adoption across society. This ambition is both timely and necessary. Yet, if AI is truly to benefit all Canadians, one of its greatest opportunities, and arguably one of its greatest responsibilities, lies in public health.

Public health differs fundamentally from clinical medicine. While clinical AI primarily supports decisions for individual patients, public health AI informs actions that affect entire populations. It must draw on diverse and often complex sources of information, including epidemiological, environmental, behavioural, demographic, mobility, and socioeconomic data to support disease prevention, health promotion, emergency preparedness, and programme development and delivery. In this context, AI can help anticipate risks, guide early interventions, and prevent health crises before they reach the hospital door.

Canada enters this new era from a position of considerable strength. It has internationally recognised expertise in artificial intelligence, mathematical modelling, epidemiology, and public health, together with a publicly funded healthcare system and rich population-level data resources. Yet these assets remain fragmented across institutions and jurisdictions, limiting their capacity to support coordinated, timely, and evidence-informed decisions.

A national Public Health AI Roadmap must therefore go beyond broad commitments to adoption, greater collaboration, and improved data sharing. It should establish a modern approach to embedding trustworthy AI within public health systems, enabling proactive, population-level action that improves health, strengthens resilience, and generates lasting societal and economic benefits.

Canada spends nearly $400 billion annually on healthcare [link], yet only a small proportion is directed towards prevention and public health. Meanwhile, ageing populations, chronic diseases, and emerging infectious threats continue to place growing pressure on health systems. AI could help shift this balance from reactive care towards proactive prevention by transforming diverse data streams into timely and actionable intelligence. Achieving this potential, however, will require more than new technologies and AI-assisted tools. It will require coordinated approaches to adoption, governance, linkable data infrastructure, and continuous evaluation.

The challenge is no longer whether Canada can develop world-class AI. It is whether Canada can embed it effectively, equitably, and responsibly within routine public health practice.

What Should a Public Health AI Roadmap Include?

Public health should treat AI not simply as another digital technology or analytical tool, but as a strategic capability for protecting population health.

First, the roadmap should help move public health from reactive response to proactive action. AI-enabled systems should support earlier detection of emerging threats, more timely interventions, and continuous learning from changing evidence and outcomes.

Second, Canada must move beyond fragmented data environments towards integrated intelligence. Health, environmental, behavioural, demographic, and socioeconomic information should be connected in ways that support timely analysis while protecting privacy, security, and public trust.

Third, AI systems must be developed with communities, not simply for them. Public health decisions are shaped by local circumstances, lived experience, and social determinants of health. Transparency, equity, accountability, and meaningful public participation should therefore be embedded throughout the design, deployment, and evaluation of AI-enabled systems.

Finally, Canada’s greatest investment should be in people. The future public health workforce must be able to work across artificial intelligence, computational and mathematical modelling, epidemiology, social sciences, and public policy. Professionals who can translate complex analyses into trusted and timely decisions will be as important as the technologies themselves.

Encouragingly, the infrastructure required to support this roadmap is already emerging across Canada. For example, Centre of Excellence in AI for Public Health Advancement (AIPHA) [link] is bringing together AI, mathematical modelling, public health, and cross-sector partnerships to develop trustworthy decision-support systems for healthcare and population health, and Artificial Intelligence for Public Health (AI4PH) [link] is advancing equitable AI and big data skills for public health research and practice. Complementary training initiatives such as the NSERC CREATE Mathematical Innovations for Precision Public Health [link] are helping build the interdisciplinary workforce required to translate AI innovation into meaningful public health outcomes. These efforts, together with Canada’s broader network of AI institutes [link], provide a strong foundation on which a national Public Health AI Roadmap can be built.

AI for a Healthier Canada

Canada has spent more than a decade establishing itself as a global leader in artificial intelligence. The next decade must be defined by how effectively that leadership improves people’s lives.

The true measure of the AI for All strategy will not be the sophistication of our algorithms, but the health and resilience of our communities. A dedicated Public Health AI Roadmap is the recipe for translating Canada’s leadership and technological capabilities into measurable public benefit. It can help build a healthier, more equitable, and more prosperous nation.