AI in Care Delivery Isn’t Personal—It’s Transformational
Mindset Shifts for the Clinical Workforce
Trellis Usher, Founder & CEO, Nova Health Labs
OpenAI’s recent launch of the Deep Research feature inside ChatGPT has stirred up a lot of conversation in tech and healthcare circles—and rightly so. The ability to quickly analyze, synthesize, and summarize credible information from across the web isn’t just a new trick. It’s a powerful tool with real implications for how we conduct research, make decisions, and deliver care in complex healthcare environments like oncology.
But if we’re being honest, the tech isn’t the hard part. The real challenge? People.
After more than 20 years leading workforce and organizational transformation in corporate settings—and now in my role at the intersection of AI and cancer care delivery—I’ve learned that successful adoption of any new technology is 70% mindset, 30% mechanics. It’s not enough to roll out new tools. We need to help people—especially our clinical professionals—shift how they see their work and their role in it.
Here are two mindset shifts I believe are critical as we introduce AI into cancer care and healthcare more broadly:
1. AI Is Not Here to Take Your Job—It’s Here to Help You Reimagine It
This is where a lot of the fear shows up. But we need to reframe the narrative: AI is not personal. It’s practical.
Just like we embraced email, online scheduling, or electronic health records, AI tools like Deep Research are the next wave of support—not competition. These tools excel at repetitive, time-sensitive, and cognitively heavy tasks that drain our time but don’t always require human judgment or empathy.
Clinical professionals spend an enormous amount of time chasing information, cross-checking studies, summarizing data, answering phones, transcribing messages, or writing reports. Deep Research and similar AI tools can do that work in seconds—freeing up humans to focus on what we do best: connecting, caring, analyzing with nuance, and making decisions under pressure.
For professionals whose roles today are heavily task-based, this isn’t a threat—it’s an opportunity. You are uniquely positioned to help determine where AI fits, what should be automated, and what absolutely should not be. But that starts with openness and curiosity. You’ve got to be willing to explore, test, and partner with the technology—not fear or resist it.
2. Understanding Your Workflow Is No Longer Optional
The second shift is one many clinicians never get trained on: process thinking. Understanding your non-clinical and operational workflows—step by step, task by task—is essential if you want to integrate AI meaningfully.
Too often, when new tools come along, people jump to extremes. Either they assume an entire role can be automated (unlikely), or they believe their work can’t be touched at all (also unlikely). The truth is in the middle. But to find it, you need to map the workflow, define where the inefficiencies are, and get clear on what parts of your work are ripe for automation.
This doesn’t just help the tech succeed—it helps you reclaim your time and refocus your energy on higher-value activities.
Of course, I recognize that this can feel like just one more thing layered onto already overstretched care teams. Most clinicians didn’t go into medicine to think about process design or systems change. That’s why support matters. Change management, workflow redesign, job analysis, and AI integration need to be part of the practice transformation strategy—not an afterthought.
At Nova Health Labs, we’re not just building smart tools. We’re building the support systems around them so that clinicians can truly benefit from AI—without being overwhelmed by it.
Because in cancer care, every moment matters. And the more we can remove friction from the system, the more energy we can put back into what counts: the patients.
How is your practice preparing clinicians and staff for this next era of work? And what support do they need to make the most of AI in practice? We’d love to hear from you.
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