'AI for All' and Canada’s last mile in healthcare

By Michael Sung, Jessica Lovett

Canada has been building toward this moment since 2017, when it became the first country to launch a national artificial intelligence strategy. That first phase produced the science and the talent to advance it. AI for All1, the federal government's newest strategy, turns toward application: the data foundations and health uses that put that science to work in care.2

Healthcare is where the federal government has placed its earliest bets. The strategy names health as its first mission and funds it accordingly; the Health Sector Data Space draws $100 million to widen access to secure, standardized health data for research and clinical trial readiness. A parallel $100 million goes to Project VITAL, extending it across more provinces and enabling analysis over hospital datasets while patient information stays governed within the province where it originates. The $200 million AI Missions program aims its investment at specific health outcomes rather than broad research capacity. The federal direction is unmistakable: from building AI capacity toward putting AI to work in care. 

The Last Mile in specialty care

Specialty and complex care should welcome that shift, because this part of healthcare has its own “last mile”. A therapy can be approved and clinically indicate for the patient, and still leave a long path before the first dose. Coverage has to be confirmed, information has to move between offices, and the therapy itself has to be coordinated and then sustained well after treatment begins.

This is the terrain Innomar knows. For more than 20 years, we have supported patients and providers through treatment journeys that are hard to travel alone, working in the space between a prescription and the start of therapy, where small delays harden into larger barriers.

That vantage should shape how Canada approaches health AI. Canada holds strong clinical and hospital data and AI for All builds on it with genuine intent. The next layer lies beyond the hospital, in the patient pathway itself: the access and coordination work that decides how quickly a prescribed therapy reaches the person waiting for it. Used with care, AI can take on the repetitive parts of that work, organizing intake and speeding follow-up when a journey stalls. 

Where patients feel the difference

  
Innomar is already putting that idea into practice. Through AI-powered Intelligent Document Processing and Natural Language Processing, we are tackling one of the biggest barriers in specialty care: the manual movement of information from healthcare documents into the patient support pathway. Enrollment forms, special authorization forms, prescriptions and receipts all carry details that can affect timing; when AI helps extract, interpret and process that information more efficiently, teams can spend less time on manual review and more time on the cases that need human judgment. That is practical AI in specialty care: automation used carefully, close to the patient pathway, to reduce burden and help treatment start sooner. 

As governments carry this agenda forward, Innomar's part stays close to the ground: easing what patients have to navigate and shortening the distance between a prescription and its treatment, with automation brought in by judgment, where it can lift weight from patients and the providers caring for them. Likewise, AI in healthcare earns its place when it shortens the road from diagnosis to treatment, and when patients feel that difference in how soon care reaches them. 

Canada’s National Artificial Intelligence Strategy: AI for All: https://ised-isde.canada.ca/site/ised/en/canadas-national-artificial-intelligence-strategy-ai-all

The governance of artificial intelligence in Canada: Findings and opportunities from a review of 84 AI governance initiatives: https://www.sciencedirect.com/science/article/pii/S0740624X24000212; Securing Canada’s AI advantage: https://www.pm.gc.ca/en/news/news-releases/2024/04/07/securing-canadas-ai

The information provided in this piece does not constitute legal or medical advice. Innomar Strategies Inc. and its parent Cencora, Inc. strongly encourage the audience to review available information related to the topics discussed to rely on their own experience and expertise in making decisions related thereto. Further, the contents of this piece are owned by Innomar Strategies, and reproduction is not permitted without the consent of Innomar Strategies.