Staffing shortages, appointment backlogs and relentless pressure to improve cost to serve while meeting rising expectations and complex regulations — healthcare organizations are navigating a perfect storm. While automation offers a powerful solution by reducing administrative burden, ethical AI adoption and successful implementation requires a unique, human-centered approach.
In the webinar “AI, Access and Burnout: A People-first Roadmap for Health System Resilience,” Lukas Voss, Becker’s Healthcare’s Custom Content Writer, Scott Peters, TaskUs’ Division Vice President, Business Development & Strategic Growth and Rachel Lutz-Guevara, TaskUs’ Division Vice President, Trust & Safety, explain the roadmap and explore three areas organizations must focus on.
Prioritize clinician governance and wellness
When it comes to using AI in clinical environments, governance is a top priority. Many clinicians don’t trust AI yet. Take nurses, for example. A Becker’s Healthcare survey revealed that “only about one-third trust AI for administrative and clinical work.”
So how can healthcare organizations adopt AI responsibly? To address the trust gap, they must treat technology as a support for frontline staff and let experts make the final call.
“We have to move toward considering how clinician-led governance can be a part of the solution in AI companies,” says Rachel. “If you’re infusing AI systems and tools, it’s critical to still allow clinical sovereignty and veto power. Clinicians should continue to use their judgment to better understand patient care and experience.”
Additionally, having tools handling routine tasks leaves providers with high-touch, emotionally demanding engagements. That could potentially increase compassion fatigue. To counteract this, Rachel advises prioritizing workforce wellness and “building psychological stamina” by:
- Clearly communicating the why behind AI adoption
- Providing adequate skills-based training
- Hosting skills groups and dedicating time away from high-stress tasks
- Having clinically informed support groups or wellness check-ins to assess workforce mental health
Design solutions to improve experiences for all
The second key area of focus involves overcoming a common pitfall: narrowly focusing AI efforts to solve either patient or provider challenges. This single focus undermines systemic improvement. Scott emphasizes the need for a holistic, human-centric solution.
“Opportunities to innovate to become more operationally efficient start to emerge when we take in those needs and experiences of all stakeholders,” explains Scott.
True efficiency comes when solutions simultaneously benefit both parties. One example is streamlining prior authorizations to accelerate patient care while reducing administrative frustration for frontline staff.
Start with low-risk use cases
While technology offers transformative power, rushing AI adoption in healthcare carries significant financial and operational risk, especially in this regulated industry. Scott advises taking a calculated approach, focusing on safety and measurable value.
“Adoption of AI where AI is low risk and the return of investment (ROI) is more clearly defined is the responsible approach right now,” he says.
So how can organizations identify where to start? Partners can help determine what to:
- Eliminate: Workflows where no one should be manually doing (low-risk, high-volume tasks perfect for AI)
- Delegate: Processes consuming valuable resources that could be utilized elsewhere (tasks to outsource or automate)
- Retain: Critical functions that only human experts should handle and adds unique value
Ultimately, knowing when to pause, allow regulatory systems to mature and build internal AI governance is crucial. Failure to do so risks wasted investment and creates new frustrations instead of solving existing ones.
Get more in-depth insight and real-life examples of successful AI applications in healthcare.
