Artificial intelligence is quickly becoming part of the healthcare ecosystem, from clinical decision support and documentation to patient education and administrative workflows. But adoption isn’t happening evenly across healthcare professionals. 

One of the most important gaps may be between physicians and nurses. 

According to data highlighted by EMARKETER, 57% of physicians regularly use AI at work, compared with just 41% of nurses. Nurses who use AI are also less likely to use clinician-specific AI support tools: 30% report using them compared with 37% of physicians (source).

That difference deserves attention not simply because nurses represent a large portion of the healthcare workforce, but because they play such an important role in the day-to-day patient experience. 

Nurses Believe in AI. They Just Aren’t Using It at the Same Rate. 

Interestingly, lower adoption doesn’t mean nurses are skeptical about AI’s potential. 

In fact, the opposite may be true. 

The article reports that 61% of nurses believe AI will improve care quality over the next five to 10 years, compared with 55% of physicians. Similarly, 59% believe AI will improve patient outcomes versus 53% of physicians (source).

The disconnect appears when AI moves from the broader promise of better healthcare to the realities of an individual nurse’s workflow. 

Only 55% of nurses believe AI will personally save them time, compared with 70% of physicians (source).

That gap tells an important story: healthcare professionals can believe in the potential of AI without necessarily believing that today’s AI tools solve the problems they encounter every day. 

Trust Is Still the Price of Admission 

Adoption also depends on confidence. 

Accuracy was cited as nurses’ leading AI concern, while reduced human interaction was another concern highlighted in the research.  

That’s especially important in healthcare, where AI isn’t operating in an environment in which a wrong recommendation simply means an irrelevant product or piece of content. Information can influence decisions, conversations and ultimately patient care. 

For healthcare organizations and technology companies, successful AI implementation therefore can’t be measured solely by access to technology. 

Trust, usability and workflow relevance may ultimately be just as important as the technology itself. 

What This Means for Pharma and Healthcare Marketers 

There is another implication that extends beyond clinical technology. 

As AI increasingly influences how healthcare professionals discover and consume information, pharma and healthcare marketers should avoid thinking about “HCP AI adoption” as one uniform behavior. 

Physicians, nurses, nurse practitioners, physician assistants and other healthcare professionals may use AI differently and have different expectations of the information it provides. 

That creates several opportunities for marketers: 

• Think beyond the physician. AI-driven HCP strategies should reflect the broader care team and the role different professionals play throughout the patient journey. 

• Prioritize credibility. As healthcare professionals turn to AI-assisted search and information tools, authoritative, well-structured and evidence-based content becomes increasingly important. 

• Design around workflows. The most valuable information isn’t simply available it appears in a format, channel and moment that fits how an HCP actually works. 

• Consider AI discoverability. Traditional SEO remains important, but healthcare brands should also begin considering how their content is interpreted and surfaced by generative AI platforms. 

• Build trust before driving action. Particularly in healthcare, usefulness and transparency can be more powerful than simply increasing the volume of AI-enabled touchpoints. 

The Next Phase of Omnichannel Healthcare Marketing 

The broader lesson is that AI adoption isn’t just a technology story. It’s an audience story. 

Healthcare organizations may struggle to scale AI if physicians adopt tools that nurses don’t consistently use or trust. Research similarly points to training, workflow integration, and confidence-building as important considerations for healthcare organizations, while health-tech companies need to design around how nurses actually document, communicate, and make decisions.  

The same principle should guide healthcare marketing. 

The future isn’t simply about adding AI to an existing omnichannel strategy. It’s about understanding where AI fits within the behaviors, needs, and workflows of each audience and creating experiences that provide genuine value.  

For marketers, that means moving from a channel-first mindset toward an audience-and-intent-first approach. 

AI may change how healthcare professionals find information, evaluate evidence, and engage with brands. But technology alone won’t determine adoption. 

Relevance and trust will. 

As HCP and APP digital behaviors become more complex, and AI plays a larger role in interpreting them, brand marketers need more than data alone. Human-led, AI-powered insight solutions can bring the context, expertise, and rigor needed to turn digital signals into meaningful, actionable intelligence. By combining human expertise with AI at scale, marketers can better understand the audiences they need to reach and act on AI-driven insights they can trust. Learn more about how LiveInsight AI helps brands uncover deeper, more reliable insights into HCP and APP digital behavior.