In healthcare the first phase of AI adoption is to create trust

Healthcare leaders face a difficult truth. In a world of tight budgets and constant staffing pressure, every dollar spent on AI is a dollar not spent somewhere else. “58% percent of healthcare leaders report that AI is either fully embedded in or is a core component of their operations; the remaining respondents are exploring or in the early stages of adopting AI,” according to the KPMG Intelligent Healthcare report.¹ However, “60 percent of nurses in the US do not trust their employer to prioritize patient safety when implementing AI tools.” So, if nurses and physicians conclude that leadership decided to invest in AI instead of investing in people, trust may collapse before you can hold the first training session.²

Before anyone can be asked to adopt a tool, leaders must earn trust in the journey itself.

Leaders need to be able to communicate why this matters now, who and what will be protected, how safety and quality will be proven, and how the benefits will show up in the daily lives of those delivering care.

Trust is built when leaders speak candidly about intent and trade-offs, invite frontline voices into the design, and explain changes clearly. It grows when people see that AI can provide value by reducing administrative burden while elevating the valuable time spent on clinical decision-making, team coordination, and direct patient care.

To help build trust, consider anchoring early AI decisions and communications around the 3 “P’s”. These are levers you can pull in communications with your workforce. The 3 “P’s” are more like a menu than an exact recipe. You know your people best; pick and choose the elements that address your people’s concerns:

Trust = Purpose + Protections + Proof

Purpose

State the “why” and explain how AI is more than a productivity play. Tie AI to outcomes that clinicians and staff value, for example:

Fewer after-hours notes,
Clearer patient communication,
Faster coordination, and
Safer decisions at points of risk.

71 percent of leaders say their organizations have achieved efficiency improvements with AI technology, but the key is to translate this into outcomes, so your employees buy into the same purpose you do.³

Protections

Name non-negotiables up front. For example:

Clinical judgement remains in charge,
Patient safety and privacy are protected, and
Professional standards will not be diluted.

It’s imperative that leaders communicate these protections in the early phase of adoption: AI is not about replacing medical professionals but about freeing them from repetitive tasks, allowing them to focus more on patient care and complex clinical decisions.

Proof

Show tangible wins and real use cases with simple, frontline-relevant metrics (for example, “Adopting AI led to 20% more time available for patient interaction during rounds”). Continuous validation and transparent reporting turn proof into confidence in the tool and your vision, accelerating adoption across teams.

Trust in the vision becomes credible when it is translated into role-specific routines. To demonstrate tangible trust in leadership’s vision, let us look at AI scribes as an example. Although still in the early stages of widespread adoption, AI scribes are a successful use case that can replace hours of manual data entry into a few minutes of expert-led review and validation. For clinicians, the value proposition is a dramatic reduction in administrative burden that elevates their role and frees time for top care.

A communication to your clinical team about a recently implemented AI scribe could look like this:

Starting Monday, the AI scribe will capture notes and draft documentation in real time. A routine note that previously might have taken you 15 minutes to write will become a review that only takes a few minutes.

Open the draft, thoroughly review for accuracy, add nuance, and sign. Clinical judgment and required safety checks remain unchanged– the clinician is still in the driver’s seat and decides whether to accept, edit, or reject the draft. If the draft is off or missing essential context, use the override option, select a brief reason (for example, “context missing”), and proceed with manual entry. The clinic monitors edit rates and override reasons, and the weekly governance review adjusts prompts, workflows, and training based on the patterns you report.

One of the nation’s leading medical groups used AI scribes that saved physicians an estimated 15,791 hours of documentation time and improved patient-physician interactions. This tool will help ease the documentation burden and reduce burnout, allowing clinicians more time to focus on patient care.

In this example, trust can be translated using the 3 “P’s”:

Purpose	Protections	Proof
The AI Scribe will reduce documentation time, so a routine note that previously took 15 minutes now becomes a quick review.	The clinician is still in the driver’s seat—they decide whether to accept, edit, or reject the draft and can use the override option and proceed with manual entry.	Point to any data or wins the AI Scribe has provided in the field, such as the American Medical Association’s findings that AI scribes saved physicians over 15,000 hours of documentation time and improved patient-physician interactions.4

When leaders can speak to the applicable user group with this level of clarity by linking new routines to the old, burdensome process, they signal respect for the work required and create a safe pathway for adoption.

Remember that the first phase of AI adoption is about trust.

Trust that the vision is purpose-driven, that people and safety are prioritized, that proof precedes scale, that priorities are honest, and that participation is real. When leaders start here and lead with empathy, they earn trust in the journey.

Trust in the tools comes next, but only after trust in the why. Consider putting the 3 “P’s” into practice in your organization. That is how healthcare organizations turn trust into adoption, and adoption into better care.

Build trust, deliver value: Why KPMG

Trust-forward AI adoption requires a collaborator who can co-design with clinicians and staff, align leadership around a shared vision, and operationalize change without disrupting care. KPMG brings a human-centered operating model that turns trust into scalable value. We blend clinical, operational, and technology expertise to provide sustained outcomes.

Empowering workforces. Shaping business outcomes.

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