AI Tools May Support, But Not Replace, Oncology Nursing Care

At the 51st Annual Oncology Nursing Society (ONS) Congress, Matthew Byrne, PhD, RN, CNE, principal product manager for generative artificial intelligence applications at Mayo Clinic, discussed how artificial intelligence (AI) technologies are reshaping oncology nursing practice while emphasizing the continued importance of human-centered care.

During the session, titled “Human First, Tech Forward: Nursing in the Age of AI,” Byrne explored both the opportunities and risks associated with AI integration in oncology nursing workflows, education and patient care.

AI Applications Continue Expanding in Oncology Care

Byrne outlined foundational AI concepts, including machine learning, deep learning, generative AI and large language models, while highlighting their growing relevance in healthcare settings.

According to the presentation, AI applications in oncology may support areas including clinical decision-making, workflow automation, symptom management, patient education, imaging analysis, clinical trial matching and personalized care planning.

Slides from the presentation also highlighted the increasing use of ambient AI technologies capable of converting voice and video interactions into clinical documentation, flowsheets, orders and workflow tasks.

Byrne additionally discussed AI-assisted administrative functions such as pre-drafting patient portal message responses, which may help reduce caregiver strain and administrative burden while improving efficiency.

“There continues to be concern that these AI technologies make mistakes and can resurface bias,” Byrne said during the presentation.

He emphasized that nurses remain responsible for reviewing and validating AI-generated information.

“The nurse must ensure that the content itself, the readability and accuracy are consistently meeting institutional standards, but also the patient expectation and the patient context,” Byrne explained.

Balancing Innovation With Human-Centered Nursing Care

Throughout the session, Byrne stressed that nursing expertise must remain central to AI implementation in healthcare environments. Presentation materials emphasized maintaining “relationship & human-centered” care while preserving compassion, dignity, touch and presence in increasingly technology-driven healthcare settings.

The session also addressed how oncology nurses may help guide the ethical development and implementation of AI technologies by improving AI literacy and participating in design and deployment decisions.

“We have to be involved in the development, the testing and the deployment of these technologies, so that we protect our practice,” Byrne said.

According to Byrne’s presentation, nurses should “lead with your knowledge and experience to ensure high touch in our high tech care environments.”

AI May Help Personalize Patient Education

The presentation highlighted patient education as one area where AI tools may significantly support oncology nursing workflows.

“I think patient-centered education is an area that could be incredibly helpful to busy nurses and to anxious and complex patients,” Byrne said.

He explained that AI technologies may help deliver educational content in more personalized and accessible ways while supplementing traditional discharge materials and educational resources.

“I can see that AI can be used to supplement our teaching and really allow for a slowing down of that process, so it can be paced and repeated and personalized to meet each patient’s need in that patient context,” Byrne said.

Byrne also discussed the possibility of future AI-driven educational systems that patients may access at any time through conversational interfaces.

“What I’m already starting to see ... is that we’re going to see 24/7 accessible and interactive options where patients can actually dynamically converse with the content,” he explained.

Risks of Bias, Data Quality and AI Literacy

The presentation highlighted several challenges associated with AI adoption in healthcare, including bias, misinformation, intellectual property concerns, privacy issues and inequities resulting from incomplete or poor-quality data. Byrne repeatedly referenced the concept of “GIGO” (“garbage in, garbage out”) to explain how flawed data may negatively influence AI-generated outputs. According to Byrne, inaccurate, incomplete or biased data may contribute to flawed clinical decision-making, delayed care, misdiagnosis and patient harm.

“Bias continues to be both an overt and hidden part of healthcare,” Byrne said. He also discussed concerns surrounding information literacy and the growing use of online educational platforms and AI-generated content.

“Unfortunately, there is evidence to suggest that nurses need to build up their tech literacy,” Byrne said, noting that clinicians may sometimes rely on unreliable online sources for medical information.

AI May Support Symptom Management and Workflow Efficiency

Byrne additionally explored hypothetical oncology use cases involving AI-assisted symptom management.

He explained that AI systems may help support intake processes, evaluate evidence-based interventions, improve medication safety and identify urgent symptoms requiring escalation.

“The work I’m involved with is never done to replace the nurse, but rather to help expedite and standardize information gathering, and then to support our decision making,” Byrne said.

Byrne noted that AI systems may help clinicians synthesize large volumes of patient information more efficiently.

“There’s really no way that we can keep track of all of that and put it all together very, very quickly in the moment,” Byrne said regarding the growing amount of healthcare data generated during patient encounters. “That’s where AI helps us.”

Nurses Remain Essential in the AI Era

Despite rapid technological advancement, Byrne repeatedly emphasized that AI should augment — not replace — oncology nursing expertise. Closing presentation slides stated that AI cannot “replace you or your judgement,” “match your experience as a nurse,” or “mimic your empathy, support, and guidance.” The presentation concluded that oncology nurses will continue to play a critical role in determining how AI technologies are safely and ethically integrated into clinical care environments.

“We are the sentinels, we are the last one,” Byrne said. “There are times when we need to say, ‘Nope, that doesn’t make sense here.’”

Reference

Byrne M. Human First, Tech Forward: Nursing in the Age of AI. Presented at: 51st Annual Oncology Nursing Society Congress; 2026.