Key takeaways
- Automate high-volume clerical tasks first. Chart summaries, results review, follow-up scheduling, and patient portal triage reclaim measurable hours and reduce burnout.
- Design for multi-step workflows, not point solutions. Agentic automation that interprets, decides, and books across systems creates real capacity and better patient flow.
- Make adoption a workforce strategy. Segment nursing roles, co-design with frontline teams, and align with enterprise governance, so change feels natural, safe, and valuable.
During Bamberg Health’s Healthcare Innovation Summit, a panel moderated by Jean Aouad, EVP at Petal Health, explored how automation and AI are reshaping healthcare workflows to ease administrative burden and unlock clinical time.
The discussion brought together leaders from McGill University Health Centre, University Health Network, and Alberta Health Services to share what’s working now and what’s next.
Why this matters
Administrative burden present a capacity challenge to care providers and their patients. Every hour spent navigating charts or managing follow-ups is an hour away from patients. The panel focused on practical ways automation and AI can reclaim that time and improve access without compromising safety or experience.
Here are five themes that came out of the discussion that are evolving healthcare delivery right now.
1. Where automation delivers today
Panelists highlighted real-world examples already making an impact:
- Results-to-follow-up automation: Reviewing pathology or imaging results, determining intervals, and booking appointments that close loops that stall care.
- Patient portal triage: Drafting responses to reduce backlog while maintaining human oversight for safety.
- Chart summarization: Surfacing key events and disease history in seconds instead of minutes scrolling through notes.
The metric that matters? Hours reclaimed and redeployed, as well as how that translates into shorter wait times, fewer missed follow-ups, and better continuity.
2. Redefining roles: What stays human, what becomes automated
As automation moves beyond single tasks, the human contribution to care is being reframed. Algorithms can assist with assessment, triage, decision support, and coordination, but they can’t replace the relational, ethical, and nuanced judgment at the heart of clinical practice.
Teams are already adapting through:
- Partial automation in triage
- Digital agents handling coordination tasks
- Connected care systems recommending schedules and clinician availability
The leadership challenge: define the right mix of human and automated steps with clear accountability and governance. What was emphasized repeatedly is the ongoing need to keep the ultimate decision-making human. AI and automation are tools to speed up information analysis. Decisions are human.
This is the basis for how Petal’s Automated Scheduling works. Automation based on layered rules, absences, and staff preferences that reduce administrative burden but puts the administrator in the driver’s seat.
3. Intelligent automation across the care journey
The panel underscored a critical insight: the real value of automation emerges when it moves beyond isolated tasks and connects the entire care journey where systems interpret data, make decisions, and execute actions across multiple touchpoints without constant human intervention.
The biggest gains come from end-to-end workflows, not isolated tools. Think:
- Interpret results → synthesize data → decide next action → book follow-up → notify care team
- Conversational chart queries that compress minutes of searching into seconds
- Cross-system orchestration linking scheduling, on-call, and patient messaging
This reframes ROI from “feature adoption” to capacity creation, reducing backlogs and improving patient flow that allows for the consistent delivery of more care.
4. Patient value and safety: The non-negotiables
Patients want timely answers and fewer handoffs. Remote monitoring for conditions like heart failure shows how automation improves experience. But safety is critical: automated messaging can misjudge severity without guardrails.
This requires clear design principles:
- Escalation thresholds with clinician-in-the-loop
- Audit trails for automated actions
- Transparency so patients know when automation is used and how oversight works
This also leads to greater needs around data safety and security for patient and health delivery organization (HDO) information. Understanding connected systems and where data is stored becomes more important than ever, especially when many systems store data outside of Canada.
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Scaling responsibly: Strategy and co-design as an organization
AI initiatives thrive when aligned with institutional priorities and supported by governance, IT, and procurement. Co-design with frontline teams ensures solutions meet real needs and integrate seamlessly. This means change management isn’t top-down implemented, but built on alignment, not persuasion or coercion.
Execution principles:
- Target high-friction workflows first
- Design for end-to-end automation with clear oversight
- Quantify capacity gains and reinvest in access
Communicate benefits in clinician language: fewer clicks, fewer callbacks, fewer missed follow-ups, and more patients helped.
The bottom line
Automation and AI are not about replacing clinicians. They’re about restoring time to care. Start with clerical-heavy workflows, build agentic automation across the journey, invest in workforce readiness, and embed governance. Done right, AI and automation become a capacity strategy, rather than a tech initiative.
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