Highly skilled clinicians are burning out under administrative burdens. They spend 20 to 30 minutes documenting each visit, take work home to finish notes after hours, and have less time for the part of medicine they trained for, putting hands on patients.
Eric C. Gardner has led strategy and innovation initiatives across major healthcare organizations, integrating AI into clinical and operational workflows because he believes AI is the answer to unlocking clinicians from these burdens.
When AI is positioned as something done to clinical teams rather than with them, resistance is inevitable. Driving AI adoption requires anchoring technology in real operational pain points, establishing clear governance from day one, and investing in change management as much as technology.
Anchor AI in Real Operational Pain Points
Start with a problem the frontline already has and cares about. Document the burden before implementing anything.
“You identify that problem and the AI will help clearly remove those frictions,” Gardner explains. “When you start working through the workflows and start implementing these things, and you remove that friction from the team, that really helps set an anchor for that technology.”
Common pain points include documentation processes, prior authorization work for specialty appointments, staffing efficiencies, and access constraints to actually seeing patients. When AI clearly addresses these burdens, adoption follows because clinicians experience immediate relief from work they never wanted to do in the first place.
Gardner has seen ambient documentation technology reduce post-appointment administrative work from 20 to 30 minutes to seconds. The software records patient encounters, filters out non-clinical conversation, and documents only clinically relevant information, including coding and orders. “The technology has advanced to where 99% of the documentation is spot on, exactly what the provider would have documented,” Gardner notes.
Providers still quality-check the output, but the cognitive and time burden disappear. This is clinicians getting hours back every week to focus on patients instead of typing.
Establish Clear Governance From Day One
The second step is bringing clinicians, IT, compliance, legal, and operations into the same conversation from the beginning.
“You define the data ownership, the risk threshold, and success metrics up front and align the team on this process so that it prevents rework in the future,” Gardner explains. “If you don’t have a clear objective and everyone understands where we’re going, then there tends to be a lot of rework that happens.”
Most healthcare organizations are clinician-led. They couldn’t do the work without clinicians, so having their buy-in early and ensuring they understand practical applications, guardrails to protect patients and providers, and clear rules about where humans remain in the loop builds organizational confidence that allows technology to scale.
Invest in Change Management
Technology adoption fails when organizations invest in software but not in the people who must use it.
“Invest in change management as much as you’re investing in the technology,” Gardner emphasizes. “Change is difficult for everyone, and that pushback is inevitable.”
Early in his career, a leader introduced Gardner to “Who Moved My Cheese,” a book about leading change management and understanding different personalities involved in change. Change management requires training, transparency, and communication so clinicians understand what’s happening, what the next steps are, and where the organization is going.
Gardner has worked with organizations implementing predictive analytics that synthesize hundreds of pages of patient history into digestible summaries. “Providers review a summary before they go into the room, and it’s like you’re talking to your best friend,” he explains. “You understand that they’ve had all these different things happen in their life, and the most recent scans or tests that were relevant to the visit, all that is pulled forward.”
Understanding a patient’s cancer journey across hundreds of pages, labs, and exams, digested into a paragraph or two, removes cognitive burden while enabling more intimate, informed conversations with patients. But only if clinicians trust the technology, which requires transparent communication about how it works and what safeguards exist.
Remove the Burden, Not the Humanity
“What really inspired me was that we’ve got fantastic folks, well-trained, highly skilled clinicians that are just so burdened with administrative tasks that they’re getting burnt out,” Gardner explains. “AI is really the answer to helping us unlock those burdens so they can focus on the fun parts of clinical care, putting hands on the patient, eyes on the patient, versus worrying about typing up a note.”
When AI works as intended, clinicians spend seconds reviewing documentation instead of 30 minutes typing notes. They walk into patient rooms fully informed about complex medical histories. They focus on patients instead of administrative tasks.
That’s not automation replacing humanity, it’s technology removing barriers so humanity can do what it does best.
Connect with Eric C. Gardner on LinkedIn for insights on AI adoption in healthcare systems.
