Milestones Newsletter | Issue 15, Summer 2026
As artificial intelligence continues to reshape healthcare, PCMCH is exploring resources that help us think critically about innovation, ethics, privacy, equity and patient care. Here are a few of the resources currently on our reading list:
Pan-Canadian AI for Health (AI4H) Guiding Principles
A foundational Canadian framework outlining principles for the responsible adoption of AI in healthcare, including person-centred care, equity, privacy, transparency and Indigenous data sovereignty. A useful starting point for anyone thinking about AI governance in health systems.
WHO: Ethics and Governance of Artificial Intelligence for Health
The World Health Organization’s landmark guidance on the ethical use of AI in healthcare. The report explores opportunities, risks and six key principles to ensure AI serves the public good while protecting human rights and patient trust.
Artificial Intelligence (AI) at CIHI
The Canadian Institute for Health Information (CIHI)’s overview of how AI may transform Canada’s health system, including its work on AI governance, workforce readiness, data quality and responsible implementation. The page also links to free learning modules on AI, data and ethics in healthcare
First Nations and Artificial Intelligence (Chiefs of Ontario)
This paper explores AI from a First Nations perspective, examining issues such as algorithmic bias, governance, data ownership and Indigenous rights. It offers an important reminder that discussions about AI must also include Indigenous data sovereignty and community-led approaches to technology.
The AI Frontier: From Exploration to Enduring Transformation (Harvard Business Publishing)
Many organizations have adopted AI, but few have achieved meaningful impact. This article examines how leadership, workforce readiness and a culture of continuous learning can help transform AI investments into lasting organizational value.
Canadian Businesses’ Use of AI: What the Evidence Shows (Bank of Canada)
Drawing on national survey data, this article examines AI adoption, productivity, workforce impacts and business readiness, offering an evidence-based look at how organizations are moving from experimentation to real-world implementation and value creation.
