AI is everywhere in community oncology labs and clinics. But most practices still struggle to make it part of daily care. At the 2026 COA Payer Exchange and Innovation Summit, leaders faced a blunt reality. More than 80% of oncologists and operations heads say they use or test AI. Only 19% have put these tools into real practice. The gap is wide. Patients and providers feel the drag.
Shiela Plasencia, senior director of practice support at COA, set the tone. She called for less talk, more proof. Debra Patt, MD, PhD, MBA, FASCO, president of COA and executive vice president of policy and strategy at Texas Oncology, cut straight to the point: “I don’t think there is hype, actually, right now…. I’m very excited about the palpable changes that I see.” She pointed to DeepScribe for dictation and Canopy’s electronic patient-reported outcomes (PRO) platform. These tools let nurses reclaim up to 80% of their time for direct patient care. Less paperwork. The impact is real. But cost, cybersecurity, and workflow confusion still block wider use.
In a 2026 survey, 79% of oncologists said they are comfortable using AI for treatment decision support, but only 19% reported actually using predictive AI models in practice.
June Lanoue, president of hematology at Johnson & Johnson Innovative Medicine, brought numbers from J&J’s Oncology Care Index. AI use in oncology jumped from 15% to 45% in a year. Still, most practices are stuck in pilot mode. “There’s a big difference between strategy vs implementation, execution, and adoption,” Lanoue said. She pushed back on the idea that AI replaces staff. Automation should free up clinicians from paperwork. That way, they can focus on patients. Tech must help, not disrupt. Staff should not be left scrambling.
COA has made innovation a permanent job. Instead of a short-term task force, it set up a standing AI & Digital Transformation Committee. The goal: give independent practices a real voice. Patt laid out the plan. The committee maps out operational change, pushes for buy-in, picks tech partners, and manages the human side. Their work is changing how practices pick vendors. Now, security, compliance, and smooth workflow integration are must-haves. Not just technical skills.
Not all vendors measure up. Patt and Lanoue both shared stories. Flashy demos often fail under pressure. Quiet partners with real community oncology experience get results. Practices now demand scalability, flexibility, and seamless links to electronic health records. These are non-negotiable. Patt said true partners help manage change, not just install software. Her own practice doubled patient enrollment in electronic PROs after switching to a vendor who understood patient engagement.
According to the Oncology Care Index, AI adoption in community oncology rose sharply from 19% in 2025 to 49% in 2026, with nearly 40% of practice administrators reporting similar levels of use. However, cost, cybersecurity, and uncertainty about workflow impact remain the main barriers to scaling these technologies.
Clinical trials are a sticking point. Most US cancer patients get care in community settings, but trial participation is low. Patt called for AI-driven decision support to flag trial-eligible patients before appointments. She also wants the FDA to allow telemedicine screening and remote labs, especially for rural patients. Lanoue pointed to real-world trials in community clinics that have already shaped National Comprehensive Cancer Network guidelines. One example: the new use of tocilizumab for outpatient bispecific therapy. The shift is clear. Complex treatments like bispecific and CAR T-cell therapies are moving from hospitals to outpatient clinics. Remote patient monitoring, like Patt’s work with Canopy, lets teams catch complications such as cytokine release syndrome earlier.
The panel looked ahead. Patt pictured agentic AI systems guiding patients from referral to treatment. No more delays from fragmented care. Lanoue set a bold goal: raise US clinical trial participation from 8–10% to 50%. She wants new therapies to reach community clinics as fast as academic centers. But the human factor stays central. During Q&A, Sibel Blau, MD, raised concerns about AI risk. Patt was clear: “Nobody wants doctors to be replaced by AI. We just want AI to give us more knowledge at our fingertips and greater reach, and I think that the human-in-the-loop element is really critical to safety.” Lanoue agreed. Trust and relationships—not just clinical skill—keep patients in community oncology.
These lessons ripple through advanced therapies. See recent coverage of cell therapy trial launches. The message is simple. Tech alone will not fix cancer care. AI must fit into the daily work of clinicians and patients. Real change needs strong partnerships, solid infrastructure, and flexible rules. Only then will digital transformation move from hype to healing. The next chapter will be written by those who deliver real value at the point of care. Not by the flashiest tools.
