If your organization is:
You are not alone.
But the gap between experimentation and real impact is where most hospitals fail.
AI in hospitals is not a technology challenge.
It’s a systems, risk, and leadership challenge.
Across Canada, hospitals are stuck because:
This is a practical, implementation-focused conference designed to help you move from pilots to real outcomes.
You will learn how to:
No theory. No hype.
Real-world lessons from:
You will leave with:
This is where you move from experimentation to execution.
Join us in Toronto on 24–25 September.
Brochure download
University Health and Social Services Integrated Center of West Central of Montreal
Assistant Professor (part-time), Department of Medicine, University of Toronto
The safe, effective, and responsible use of AI in healthcare depends on strong policy, data, and system foundations. This session will provide a federal perspective on AI in healthcare, outlining progress to date, and highlighting innovation across Canada. The focus will be on the critical role of data governance, system readiness, and coordination in enabling AI, with early insights for healthcare leaders navigating this transition.
Elizabeth Toller, Director General, Health Care Strategies, Health Canada | Santé Canada
This session explores the “imagination gap” holding Canadian healthcare back from scaling AI beyond isolated pilots. While tools like AI scribes are gaining traction, structural barriers—ranging from a national compute deficit to unclear liability frameworks—continue to delay high-impact clinical adoption. Moving beyond the hype, we will examine the real constraints shaping AI implementation, including procurement models, infrastructure investment, and organizational readiness. The session will provide a practical roadmap for overcoming risk aversion, closing the AI literacy gap, and enabling scalable, enterprise-wide AI integration across the healthcare system.
Gagan Grewal-Sagoo, Transformation Lead, Humber River Health
Most hospitals are actively piloting AI, yet few initiatives have achieved full-scale implementation. This session explores the deeper structural, cultural, and human factors at play. While challenges like fragmented data are well known, the root issue is often more fundamental: healthcare data reflects human behavior, and humans are inherently variable, context-driven, and unpredictable. When this variability is captured as structured data, it limits consistency, trust, and ultimately the scalability of AI solutions.
Anne Forsyth, Director, Hospital Data Transformation, Canadian Institute for Health Information (CIHI)
Developing an AI strategy in a publicly funded healthcare system comes with unique constraints — from limited resources and complex governance structures to strict accountability and risk management requirements. This session explores how hospital and health system leaders are building practical, implementable AI strategies that align with clinical priorities, funding realities, and regulatory expectations. You will learn how to prioritize the right use cases, define clear ownership, secure internal buy-in, and create a roadmap that moves beyond experimentation to sustainable, system-wide impact.
Jeremy Theal, Chief Medical Information Officer, Alberta Health Services
Building AI capability inside a hospital is no longer optional, but how you do it will define success or failure. This session explores the key decision every organization faces: do you train your existing teams, hire new talent, or partner externally? We will break down the trade-offs between speed, cost, control, and long-term sustainability, and examine how leading hospitals are structuring their AI capability models. The focus is on practical decision making, what works, what does not, and how to build an approach that can scale.
Zach Kilburn, Chief Digital Officer, Horizon Health Network
AI in hospitals is full of pilots, but short on results. This session focuses on what actually works. Through real case studies, we will explore how hospitals are using AI to improve outcomes, reduce pressure on teams, and optimize operations. You will learn what made these implementations succeed, what challenges had to be overcome, and how to apply these lessons to scale AI in your own organization.
Damian Jankowicz, Ph.D., Executive Vice President, Chief Information and Artificial Intelligence Officer, Unity Health
This session explores how AI is being applied in a real hospital setting to improve both medical education and patient care. Through a detailed case study, you will learn how AI tools are supporting clinical decision-making, enhancing training for healthcare professionals, and improving patient outcomes. The session will walk through the full journey from identifying the use case to implementation, including key challenges, stakeholder alignment, and measurable results. The focus is on practical insights you can apply within your own organization to drive meaningful, scalable impact.
Nihal Haque MD FRCPC, Assistant Professor (part-time), Department of Medicine, University of Toronto
AI will not scale in hospitals without clinician trust. This session focuses on the frontline reality, why clinicians push back, where trust breaks down, and what actually changes behavior. We will explore how to design, introduce, and integrate AI in a way that clinicians accept and use, from transparency and validation to workflow integration and training. The session will highlight what works, what fails, and how to move from resistance to adoption.
Girish N Nadkarni, MD, MPH System Chair, The Windreich Department of Artificial Intelligence and Human Health Director, The Hasso Plattner Institute for Digital Health at Mount Sinai Chief AI Officer, The Mount Sinai Health System
As AI evolves beyond copilots and chat-based tools, healthcare organizations are beginning to explore more advanced, agentic use cases where AI can take action and automate workflows. In this session, Island Health will share how they are applying tools like Copilot to support clinical workflows and Claude to streamline operational tasks, effectively introducing AI as “extra hands” across the organization. The focus will be on where this is already delivering value, which workflows are best suited for this approach, how these systems are being implemented safely, and what early lessons healthcare leaders should consider as agentic AI becomes more embedded in day-to-day operations.
Graham Payette, Executive Director - Intelligent Automation and Artificial Intelligence, Island Health
Discover how North York General is deploying SmartER Zones - an AI-powered approach to dynamically optimize patient flow in one of Ontario’s busiest emergency departments. This session will highlight how real-time algorithms support earlier clinical assessment, reduce wait-related risks, and enhance safety during peak demand, while keeping decision-making firmly in clinicians’ hands. Learn how co-design with frontline teams and rigorous testing enabled safe implementation, and explore early results and future scaling opportunities aligned with a 24/7 care model.
Duska Kennedy, Vice President Strategy & Digital Health, CDO, North York General Hospital
Andrea Ennis, Director of the Emergency Services Program and Nursing Resource Team, North York General Hospital
This session explores how AI is being applied across healthcare to improve patient outcomes while addressing cost pressures. Using real-world examples, we will look at how AI supports earlier diagnosis, more efficient workflows, and better decision-making. The session will focus on practical lessons, what’s working today, and what healthcare communicators need to understand to support and communicate these initiatives effectively.
Jeremy Petch, PhD, Founder, CREATE (CentRE for dAta science and digiTal hEalth), Hamilton Health Sciences
Canada is a global leader in AI innovation, yet healthcare adoption remains largely confined to pilots. While interest in tools like AI scribes continues to grow, scaling these solutions across organizations has proven far more difficult.
This session will examine the structural factors behind that gap—privacy obligations shaped by frameworks like PIPEDA, evolving regulatory expectations from Health Canada, fragmented infrastructure, and unclear accountability when AI is introduced into clinical workflows.
Rather than offering quick fixes, this discussion will focus on the realities healthcare leaders are navigating today: where progress is stalling, where risk is being over- or under-estimated, and what early adopters are doing differently. Attendees will leave with a clearer lens on how to approach AI implementation decisions within their own organizations.
Kathy Malas, MPO, GCHlthMgt , Chief Quality, Innovation, Artificial Intelligence and Value Officer; Director of OROT, University Health and Social Services Integrated Center of West Central of Montreal
Most hospitals are experimenting with AI. Very few are successfully scaling it.
This hands-on workshop is designed for healthcare leaders who are under pressure to move beyond pilots and deliver real, system-wide impact. While many organizations have tested AI in isolated use cases, the real challenge lies in turning those experiments into sustainable, integrated solutions that work across clinical and operational environments.
This session focuses on what it actually takes to make that shift. We will break down the key decisions that determine success or failure, from selecting high-value use cases and building the right governance model to aligning stakeholders, managing risk, and integrating AI into existing workflows. Drawing on real-world examples, the workshop will address the structural and cultural barriers that prevent scale, including fragmented data, unclear ownership, clinician resistance, and lack of measurable outcomes.
Participants will work through their own organizational context, identifying where AI can deliver value, what is currently blocking progress, and how to move forward with a clear and practical approach.
This is not a technical session. It is a practical working session focused on helping you make better decisions, faster, in a high-risk and fast-moving environment.
Radisson Blu Toronto Downtown
Address: 249 Queen's Quay West, Toronto, ON M5J 2N5, Canada
Phone: +1 437-886-9667
This harbourfront hotel in Toronto city centre features on-site dining as well as a rooftop patio with a seasonal pool. A mini-fridge and coffee maker are included in each guest room.
A large work desk and flat-screen TV are common to all rooms at Radisson Blu Downtown Toronto. A pool, harbour or city view may be featured in these rooms.
Showcasing regional ingredients, Watermark Restaurant specializes in Canadian cuisine. Light snacks are served at Radisson Admiral’s Watermark Lounge, along with local beers and wines.
A fitness centre is among recreational facilities available at Radisson Blu Downtown Toronto.
Union Station is about 15 minutes’ walk from this hotel. Several attractions, including the CN Tower, Hockey Hall of Fame and lively Chinatown, are also within 15 minutes’ walk. Billy Bishop Toronto City Airport is 2 km away.
This program can also be delivered as a tailored in-house training for your organization. We adapt the content to your industry, objectives, and level of maturity, focusing on real challenges your teams face and the decisions they need to make. In-house formats allow your people to align on a shared approach, work through relevant scenarios, and build skills they can apply immediately.
If you’re exploring an in-house option, tell us a bit about your team, priorities, and timing, and we’ll recommend the right format.
Contact us about in-house training
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