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
Hospitals are not suffering from a lack of innovation. They are struggling with fragmented data, disconnected workflows, growing capacity pressures, and a growing number of AI pilots that fail to translate into meaningful system-wide change. Drawing on Medtronic Canada's experience across the continuum of care, this keynote explores why the future of AI in healthcare is not about deploying more algorithms, but about redesigning how information, workflows, and clinical decision-making come together to improve patient care.
Through real-world examples and practical insights, Maisie Cheung and Kevin Bernard will examine the critical challenges that continue to limit AI adoption in hospitals, including integration, governance, clinician trust, workflow design, and information architecture. They will also explore emerging concepts such as AI-enabled hospitals, connected care pathways, simulation and digital twins, and continuous learning health systems.
Attendees will leave with five practical ideas to help move their organizations from isolated AI initiatives toward more connected, sustainable, and impactful approaches to healthcare transformation.
Maisie Cheung, Senior Director of Strategic Marketing & Commercial Innovation, Medtronic Canada
Kevin Bernard, National Leader, Integrated Health Solutions, Medtronic 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
Hospital coding is one of healthcare's most critical, and least visible, information workflows. Every day, highly skilled health information professionals transform complex clinical documentation into standardized data that drives funding, health system planning, research, quality improvement, and public policy. Yet despite decades of investment in digital health, this process remains largely manual, creating growing pressure on a limited workforce while slowing access to the data that health systems depend on.
This session explores why clinical coding represents one of the greatest opportunities for meaningful innovation in health data. Drawing on Canada's national experience with health information standards and large-scale hospital data, we will examine the operational, governance, and workflow challenges that make coding far more complex than simply applying AI to medical records. Participants will gain insight into why high-quality structured data depends as much on governance and clinical workflows as it does on technology.
By focusing innovation on one of healthcare's most foundational yet overlooked capabilities, the session will challenge participants to rethink how automation can strengthen, not replace, the trusted data infrastructure that underpins modern health systems.
Anne Forsyth, Director, Hospital Data Transformation, Canadian Institute for Health Information (CIHI)
Administrative load is quietly consuming clinical capacity. Staff are spending the majority of their time on faxed requisitions, manual scheduling, and phone queues. Rishi Nayyar, CEO and co-founder of PocketHealth, walks through how coordinated AI agents automate the non-clinical steps of care within existing systems, the measurable staff-hour and FTE gains real health networks are seeing, and the guardrails required to deploy safely in a public-system environment.
Rishi Nayyar, CEO and co-founder, PocketHealth
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
Artificial intelligence (AI) is increasingly recognized as a transformative force in health care, yet many hospital leaders face challenges in moving from awareness of AI to its safe, ethical, and effective implementation. In response, the Ontario Hospital Association (OHA), in partnership with the University of Waterloo's WatSPEED program, developed the Artificial Intelligence Knowledge Translation (AI KT) Program to build executive readiness for AI adoption across Ontario hospitals. The program was designed specifically for hospital executives and senior leaders, combining foundational AI education with practical guidance on strategy development, governance, risk management, workforce readiness, and organizational transformation within the Canadian health care context.
The curriculum emphasized responsible AI adoption through a framework of governance, patient safety, ethics, privacy, equity, and regulatory compliance, while also exploring how AI can support improved clinical outcomes, service delivery, workforce sustainability, and system performance. Participants were encouraged to apply concepts through work projects and strategic planning exercises focused on identifying high-value opportunities for AI within their organizations. The program introduced leadership frameworks such as the "replace, reimagine, and recombine" model to help executives evaluate AI's potential to redesign care processes and organizational workflows.
Evaluation findings demonstrated strong uptake and positive participant experiences across Ontario hospitals, with representation from diverse hospital types and regions. Survey results indicated that participants perceived the learning as highly relevant to their current and future work and valued the practical, implementation-oriented approach. The program highlighted the need for ongoing provincial leadership in AI governance, knowledge sharing, implementation support, and workforce development. Findings suggest that sector-wide knowledge translation initiatives can play a critical role in accelerating responsible AI adoption, reducing duplication of effort, strengthening organizational readiness, and supporting coordinated health system transformation.
Imtiaz Daniel, Chief Innovation and Transformation Officer, Ontario Hospital Association
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
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
TBC
TBC
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
Everyone talks about AI's potential in healthcare, but what does "value" actually mean once you move past the pilot stage? Dr. Laura Rosella, Chief Scientist at Trillium Health Partners, breaks down value as a concrete equation: better patient outcomes paired with lower system costs, not one at the expense of the other. Drawing on her work leading AI strategy at one of Canada's largest hospital networks, she'll walk through how Trillium evaluates which AI initiatives are worth pursuing, how outcomes and cost savings are measured in practice, and what it takes to turn a promising model into a system that actually moves the needle. A grounded look at what "value" means when AI meets the realities of hospital operations.
Dr. Laura Rosella, Chief Scientist, Trillium Health Partners
AI is no longer a future technology problem. Rather, it is an executive operating-model problem across care, research, and education. This means taking a thoughtful approach to digital transformation that spans across related institutions. In AI, data and standardized workflows are keys to success. In this talk, Alex describes his model for key leadership competencies required for digital transformation in our current moment: data, AI, business processes, and change management.
Dr. Alex Sévigny, APR, FCPRS, Tenured Associate Professor of Communications Management, McMaster University
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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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