Artificial intelligence is making inroads across oncology—from training the next generation of clinicians to handling after-hours patient questions—but experts warn that thoughtful, deliberate integration is essential. Dr. R. Lor Randall of UC Davis Comprehensive Cancer Center argues that AI should be used to deepen clinical understanding, not shortcut it. He cautions that many AI tools default to affirming users rather than challenging them, and urges clinicians to actively configure these tools to push back and provoke deeper thinking.

On the patient interaction front, Randall acknowledges that AI's 24/7 availability and improving social adaptability make it an increasingly attractive option—especially given the economic pressures driving healthcare toward automation. But he stresses that the irreplaceable human element in cancer care, rooted in shared experience and human connection, will keep clinicians in demand, albeit in evolving roles. In orthopedic oncology specifically, AI shows promise in tumor detection, 3D surgical planning, robotic-assisted resection, and surveillance—but always as a force multiplier, not a substitute for oncologic judgment.

Key Takeaways:

• Set AI tools to challenge, not affirm—avoid defaulting to settings that prioritize user satisfaction over critical thinking
• AI can assist with documentation, tumor board prep, and surveillance imaging, reducing administrative burden and freeing up time for patient connection
• Every AI tool in oncology requires rigorous external validation, especially given the small, heterogeneous datasets typical of rare musculoskeletal tumors

Why it matters: As economic pressures accelerate AI adoption in healthcare, oncologists who proactively shape how these tools are used—rather than resist them—will be best positioned to preserve the quality and humanity of cancer care.