Healthcare’s workforce has a scale problem, but new model is emerging

Demand for care keeps rising, but the workforce is not keeping up. According to Experian Health's 2026 State of Patient Access Survey, 64% of providers say staffing shortages reduce patient access — up from 57% the year before. Patients expect faster, more responsive service. Hiring alone is no longer enough to close the gap.

Most operations still depend on people to move work forward. Routine tasks take time, and follow-up often depends on who is available. When teams are stretched, things slip. A patient may leave a visit expecting next steps and never hear back. Others miss follow-ups altogether because no one had time to reach out.

But a different model is taking shape. Health systems are starting to shift work between human agents and AI, creating a hybrid workforce that can extend capacity while preserving the human judgment patients rely on.

Toward hybrid work

Automation has been part of healthcare operations for years, but its impact has been limited. Traditional IVR systems and rule-based tools were designed for predictable requests. But in practice, patient interactions are rarely straightforward. A patient might call to schedule an appointment and then ask about medication or raise a new concern. They may be anxious or unsure of what they need. These interactions require context and the ability to adjust in real time.

That is why most workflows remained dependent on human staff. Automation alone could not take on complex work without breaking down.

New forms of AI support conversations that are less predictable. They can follow a patient across multiple turns in a conversation and adapt when the topic shifts. They can also work together, with different systems handling different parts of a task. This allows more of the interaction to move forward without interruption.

The result is a new model for how work gets done. Instead of relying entirely on people, organizations can begin to distribute tasks between AI and human agents.

This is the rise of the hybrid workforce. AI agents take on work that is repetitive or difficult to scale. They can manage large volumes of interactions and remain available outside of standard hours. Human agents focus on situations that require judgment or empathy, stepping in when a patient needs reassurance or when an issue becomes more complicated.

Consider an outreach call related to colorectal cancer screening. The AI agent begins the conversation with the right context. The patient responds by shifting topics and says they are experiencing vision problems. In a traditional system, the interaction would stall because the question does not match the script.

In a hybrid model, the conversation can continue. The AI agent recognizes the change and gathers relevant information. It pulls context from connected systems and clarifies the patient’s concern. When clinical judgment is needed, a human agent joins the interaction and takes over.

The transition feels natural to the patient. There is no need to repeat information. The conversation can move forward.

Reach without staff

Tasks that once required a nurse or care coordinator can now be supported on a larger scale. More patients can be contacted after discharge. More follow-ups happen without adding staff. Care teams can focus their time where it matters most: their patients.

Patients receive answers more quickly. They spend less time navigating the system. They also respond to how the interaction feels. Voice and tone influence trust, and many organizations now design AI voices to reflect local communication styles. This helps create a sense of familiarity during interactions that may already feel stressful.

Scalable operations

For this model to work, AI needs access to the right data and clear operating boundaries. It must recognize when an interaction can move forward autonomously and when it should transition to a human. Customer experience automation platforms help manage this by bringing data, workflows, and decisioning together, so interactions happen in context and with the right level of oversight.

What this ultimately changes is not just efficiency but how healthcare work itself is distributed.

The repetitive, transactional “ask and answer” interactions that have traditionally consumed contact center teams can increasingly be handled by AI agents. Tasks like appointment scheduling, prescription refill requests, eligibility checks, reminders, and basic navigation no longer require a person at every step. That creates the opportunity to elevate the role of the human workforce rather than simply reduce it.

As AI absorbs routine interactions, human agents can focus on the moments that require empathy, critical thinking, clinical coordination, and judgment. These interactions are often more complex and take longer, but they are also where the greatest value exists. Guiding a patient to the right specialist, helping someone navigate a chronic condition, preventing care gaps, improving adherence, or ensuring follow-through after discharge has a far greater impact on outcomes and financial performance than simply answering a call faster.

This transition will require intentional workforce planning. Health systems and payers will need to retrain and hire for a different type of role: teams equipped to manage high-value patient engagement, care coordination, and next-best-action guidance rather than high-volume transactional work. Success will depend on organizations preparing their workforces to operate alongside AI, not in competition with it.

The workforce challenge in healthcare is not going away, but it is evolving. Organizations that rethink how work is divided between humans and AI will be better positioned to meet rising demand, reduce pressure on staff, and deliver a more connected and reliable experience for patients and members.

Over time, the largest return on investment will not come simply from automation itself. It will come from the ability to continuously guide patients and members toward the right actions to better manage their health. Health systems and plans that can proactively engage people, close care gaps, improve adherence, and influence healthier behaviors at scale will ultimately deliver better outcomes, stronger experiences, and more sustainable financial performance.

Patty Hayward is the general manager of healthcare and life sciences at Talkdesk.