Health workforce

The Canadian healthcare industry is at a breaking point. Healthcare professionals are reporting record levels of stress and burnout, and the proportion of Canadians without access to a regular care provider is worsening over time. The growing complexity of care and administrative burdens are amplifying these pressures, impacting the health of our systems and the people they serve.

At the heart of the capacity crisis:

• Workforce shortages are wickedly complex issues each with unique context, retention factors, and structural barriers in the policy, education and care delivery systems.
• Burnout levels are at an all-time high, with many healthcare leaders and professionals reporting emotional exhaustion, high workloads, and reduced ability to deliver high-quality care.
• Change is constant across the system with new models of team-based care, new technologies, new performance outcomes, new financial pressures to solve, and new expectations of the workforce. Simply put – transformation is a state of being.

Meeting this moment calls for innovative approaches. The reality is that no amount of additional training alone will close the structural capacity gap. Even with recruitment incentives and expanding seats in healthcare training and certification programs, it will take years to grow the workforce. With the current pressures, this is time we do not have. The healthcare system must embrace new and innovative ways to capitalize on its existing talent.

This is where AI comes in – not as a replacement for skilled leaders and healthcare professionals, but as a set of tools that can amplify their impact, working smarter, and improving overall well-being.

AI is most powerful as a workforce enhancer, not as a replacement. By taking on routine and time-consuming tasks, AI allows leaders and healthcare professionals to focus their time and energy where it matters most – delivering compassionate, high value care. Rather than replacing people, AI amplifies their impact, enabling a more efficient, person-centred healthcare system.

There are three key opportunities where AI can be leveraged to support the healthcare workforce:

• Reduce administrative burden: AI-powered tools, such as medical scribes, can capture patient encounters in real-time and summarize them into structured clinical notes. This can significantly cut down on time spent on documentation, enabling providers to spend more time on care.
• Support clinical decision-making: AI can facilitate quicker and more accurate decision-making by synthesizing patient data and comparing it against vast medical knowledge bases. This streamlines the diagnostic process and minimizes unnecessary follow-ups, saving time and mental energy for healthcare professionals. By reducing decision-making fatigue, AI not only enhances the quality of clinical judgment but also fosters a healthier work environment, contributing directly to improved healthcare professional well-being and lower rates of burnout.
• Optimize scheduling: Staff scheduling can pose a complicated task, with the need to match patient demands, provider availability, and individual preferences. AI can use predictive analytics to forecast demand and create optimized shift schedules which factor in individual preferences, improving both efficiency and satisfaction. Further, using AI for scheduling can help reduce burnout by reducing instances of back-to-back shifts and balancing schedules to minimize overwork, leading to improved morale and job satisfaction.
  

Not even the most advanced AI solutions can be successful without adoption by the workforce they are designed to support. Effective implementation is dependent on building trust, competence, and engagement, which can be achieved through:

• Governance and transformation leadership: Access to AI tools can support healthcare leaders in streamlining operations and reducing administrative burdens freeing up valuable time to support their teams more effectively. Unlocking AI’s potential requires clear management oversight, robust governance and ongoing change management. This means establishing accountable decision making, risk controls and outcome monitoring from the outset. Prioritizing AI as part of broader health system transformation efforts requires not only an investment in technology, but also strong leadership to guide cultural shifts, align strategic goals and ensure AI delivers measurable value among competing priorities.
• Training and upskilling: For AI to be effective, it is critical that leaders and healthcare professionals understand both how and when to use it. This involves not only providing tailored training programs, but also assessing workforce readiness using frameworks such as KPMG’s AI Maturity Assessment, allowing organizations to determine their AI maturity level and tailor upskilling initiatives accordingly. Critical focus areas, such as interpreting AI-generated insights and embedding them into routine workflows, should be prioritized. Time and practice are crucial to mastering new skills such as interpreting AI-driven outputs, as well as fostering long-term trust in AI systems amongst healthcare professionals.
• Fostering collaboration and innovation: AI adoption is most successful when clinical and administrative teams are involved early in the process. By including them in the selection and design process, organizations can ensure the tools meet user needs and align with existing workflows. This collaborative approach also helps to create a supportive environment where healthcare professionals feel comfortable bringing forward new ideas and ways of working.
• Ongoing evaluation: At the outset of implementing AI tools, healthcare organizations should define key performance metrics and an operational definition of “value” that aligns with their strategic goals and context. AI tools should be evaluated for both accuracy and impact. Evaluation and validation should be proportional to the tool type and stage of deployment (e.g. fit for purpose testing for early prototyping and internal pilots vs rigorous validation and governance for organization-scale rollouts and external use). Building trust in AI also means having the courage to pause or discontinue pilots and tools that are not achieving their intended outcomes. Ongoing evaluation through regular assessments and feedback can be used to measure their effectiveness in reducing workload, improving quality of care, and enhancing staff well-being.

Powering up an AI-enhanced workforce can be one of the most consequential solutions to Canada’s health workforce crisis. New ways of working do not need to be imagined – we are already there. Leveraging AI presents a real and practical opportunity to make bold moves to support the health workforce – improving experiences, reducing administrative tasks, and enhancing decision making. By investing in the right tools, training, and culture, healthcare leaders can leave a lasting impact on Canada’s healthcare system and expanding the capacity to care.