How AI is changing healthcare work and skills
How can artificial intelligence help healthcare systems address workforce shortages while improving working conditions and patient care? On September 22, the Center for Resilient Health at the Stockholm School of Economics brought together researchers, healthcare leaders, and practitioners to explore how AI is reshaping healthcare work, professional skills, and organizational decision-making.
Healthcare systems face growing pressure from staff shortages, recruitment difficulties, and increasing demands on healthcare professionals. Artificial intelligence offers opportunities to reduce administrative work, support clinical decisions, and improve efficiency. But introducing AI into healthcare is not simply a matter of adopting new technology. It also requires changes in how work is organized, how professionals develop their skills, and how healthcare organizations make decisions.
These questions were at the center of a roundtable organized by the Center for Resilient Health at the Stockholm School of Economics on September 22.
The event began with a panel discussion moderated by Anna Essén, Associate Professor at House of Innovation. The panel featured Marleen Huysman, Professor at Vrije Universiteit Amsterdam and House of Innovation; Bomi Kim, Assistant Professor at House of Innovation; and Robert Svebeck, AI Strategist at Region Stockholm.
The panel was followed by roundtable discussions involving participants from healthcare organizations, industry, research, and public administration.
AI is changing work, not just replacing tasks
A central theme was that AI's greatest potential may lie in changing how healthcare work is organized rather than replacing healthcare professionals.
Participants discussed applications ranging from clinical documentation and scheduling to triage, decision support, and patient self-management. By reducing time spent on repetitive or administrative tasks, AI could allow healthcare professionals to focus more on clinical judgment and patient interaction.
However, making individual tasks more efficient does not necessarily improve the healthcare system as a whole. When AI speeds up one part of a care pathway, bottlenecks may emerge elsewhere.
Participants therefore emphasized the importance of looking at entire workflows rather than introducing AI tools in isolation.
New skills for an AI-enabled healthcare system
As AI becomes part of everyday healthcare work, professional competence will also need to evolve.
Healthcare professionals may increasingly need to evaluate AI-generated recommendations, recognize their limitations, and determine when human judgment is essential. At the same time, participants raised concerns about deskilling - the risk that excessive reliance on automated systems could weaken important professional knowledge.
Different roles will require different capabilities. Frontline staff need practical skills to use AI safely, specialists need to understand validation and clinical applications, and managers and senior leaders need the competence to assess organizational, financial, legal, and technical implications.
The challenge is not only to train healthcare professionals to use AI, but also to determine which skills must be preserved as technology takes on new tasks.
Can AI make healthcare jobs more sustainable?
Another important question was whether AI could help healthcare organizations attract and retain staff.
Reducing administrative burdens, improving scheduling, and allowing professionals to spend more time on meaningful patient care could contribute to better working conditions.
Yet participants also noted that the effects of AI on employment may be uneven. Some tasks and roles may disappear or change, while new responsibilities emerge.
AI alone cannot solve workforce shortages. Its contribution will depend on how organizations redesign jobs, support professional autonomy, and create sustainable working environments.
From promising pilots to lasting change
The roundtable also highlighted the challenges of implementing AI beyond individual pilot projects.
While testing new applications can be relatively straightforward, introducing them across healthcare organizations requires access to data, appropriate infrastructure, clear responsibilities, and coordination between different parts of the system.
Participants emphasized the need to balance local experimentation with shared standards and governance.
Measuring the value of AI also requires a broader perspective. Benefits may include improved access to care, reduced stress, better working conditions, and more time for patients - outcomes that are not always captured by conventional productivity or cost measures.
Building more resilient healthcare systems
The discussions pointed to a shared conclusion: realizing AI's potential in healthcare requires organizational change as much as technological innovation.
Healthcare organizations need to develop new capabilities, establish clear accountability for AI-supported decisions, and evaluate how technology affects both professionals and patients.
The roundtable also highlighted the importance of ensuring that AI-enabled healthcare benefits patients with different levels of digital competence, rather than widening existing inequalities.
For the Center for Resilient Health, the event was part of an ongoing effort to connect research with the practical challenges facing healthcare systems.
As AI becomes increasingly integrated into healthcare, the central question is not simply what the technology can do, but how it can be used to support better care, stronger professional competence, and more sustainable working lives.
