For a healthcare leader, the promise of AI becomes meaningful when it changes something on the floor: a nurse has more time with a patient, a manager spends less time resolving staffing issues, or a team can respond more effectively when care needs change.
That is the opportunity healthcare organisations should be designing for. Introducing a tool is only one step. Making the tool’s capacity useful requires decisions about how work is organised, who does it, and how teams are supported.
McKinsey’s recent article, The real future of work in healthcare, offers a useful starting point. Its analysis of US healthcare argues that technology investments need to be accompanied by changes to workflows, roles, and operating models.
For workforce leaders, this raises a practical question: when technology gives people time back, what happens to that time?
One of the greatest mistakes healthcare leaders make is assuming that implementing new technology automatically translates into improved efficiency or better outcomes. Having led nursing operations and workforce transformation initiatives, I have learned that we must first understand the reality of how work gets done, the challenges our teams face, and whether our current processes are designed to support success. Technology should never be the starting point of transformation. It should be an enabler of a clearly defined strategy that gives clinicians more capacity to do what matters most, which is delivering safe, compassionate, and patient-centred care.
Start with the work people need to do
Before deciding what to automate, leaders need a clear view of the work itself.
Where are staff repeating information? Which handoffs create delays? Which activities require clinical expertise, and which could be supported differently? Where does the process make it harder for people to deliver the care they are qualified to provide?
Those questions help establish whether a task should be simplified, removed, reassigned, or supported by technology.
They also bring clinical and operational teams into the same conversation. A process that looks efficient on paper may create extra work during a busy shift. Staff need a strong voice in identifying those consequences and shaping a workable alternative.
Connect time saved to workforce planning
Consider a hypothetical example: a documentation tool saves several minutes per clinician during a shift.
That could be valuable. But those minutes may be spread across different people, locations, and times of day. They do not automatically become an additional staffed hour when a unit needs it most.
Workforce planning provides the connection between a process improvement and its practical use.
Leaders need to understand where capacity becomes available, how predictable it is, and whether it aligns with patient needs. They can then assess what it means for workload assumptions, skill mix, schedules, and deployment decisions.
Patient acuity, clinical judgement, scope of practice, and safe staffing requirements remain essential to those decisions. A reduction in task time alone is insufficient grounds for reducing staffing.
Throughout my experience leading nursing operations and supporting workforce management transformation, I have seen how fragmented scheduling processes, inconsistent staffing practices, and limited visibility into workforce data can create unnecessary administrative work for nurse leaders. In one healthcare organisation, the opportunity was not simply to introduce more technology, but to examine how staffing decisions were being made, identify opportunities for standardisation, and better align scheduling practices with operational and clinical demands. What became clear through that work is that technology alone does not create capacity. The real value comes when leaders use improved processes and actionable workforce information to make more proactive staffing decisions, reduce avoidable administrative burden, and redirect attention towards supporting nurses and the delivery of care.
Make adoption part of the operating model
A redesigned process needs people who understand how to use it and managers who can make it work.
If responsibilities change, teams need clarity about ownership, escalation, and accountability. If a tool produces recommendations, staff need to understand when to use them and when human judgement takes precedence.
Training should reflect the situations people face during a shift. Managers also need support to recognise when a new process creates friction and to act on feedback.
This makes adoption an ongoing leadership responsibility. It belongs alongside workflow design, workforce planning, and technology implementation from the beginning.
Workforce Technology Adoption Pulse | Simms & Associates
Measure whether care and work improve
Time saved is a useful measure, but it is only the beginning.
A workforce improvement should be assessed through a balanced set of outcomes: time available for patient care, workload distribution, overtime and premium labour use, staffing responsiveness, and staff experience. Relevant quality and safety measures should inform the assessment too.
The measures will differ by organisation and initiative. What matters is agreeing in advance what improvement should look like—and checking whether it reaches the teams and patients it was intended to benefit.
Give workforce strategy a place at the table
As healthcare organisations explore AI, workforce leaders have an essential role in connecting ambition to daily operations.
They can help translate changes in tasks into realistic roles, skills, staffing assumptions, and schedules. They can also identify where proposed efficiency depends on conditions that do not exist in practice.
If I could ask healthcare leaders to take one step before their next AI investment, it would be to bring their clinical, operational, and workforce leaders together to conduct a real, honest assessment of how work is currently performed and where the greatest opportunities for improvement exist. We must be intentional about identifying the problems we are trying to solve, establishing meaningful measures of success, and engaging the people who will ultimately use the technology. My experience has reinforced that successful transformation is not measured by the sophistication of the tools we implement, but by the impact those tools have on our people, our processes, and the quality of care we deliver.
The opportunity is to make deliberate choices about how newly available capacity supports patients and staff. That is where workforce strategy can turn the promise of AI into a meaningful improvement in care.
Is your workforce model ready for the way care is changing?
Simms & Associates helps healthcare organisations connect workforce strategy, operational processes, and workforce management technology. Our Workforce Planning & Productivity Review provides a starting point for exploring where planning and deployment could better support your care delivery goals.
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Source and further reading: McKinsey, “The real future of work in healthcare,” 2 July 2026