When AI comes up in healthcare discussions, nursing perspectives are often missing. The conversation focuses on doctors, particularly specialists in fields like radiology and pathology where AI is most visible.

But nursing is the largest healthcare workforce. How AI affects nurses matters enormously. And the impact is different from what most discussions assume.

What AI Is Doing for Nursing Now

Let me start with what’s actually happening, not what might happen someday.

Clinical decision support in acute care. Early warning systems that flag patients at risk of deterioration are increasingly common in hospitals. These systems analyse vital signs and other data, generating alerts for nursing staff.

In practice, these systems are mixed. When well-implemented, they help nurses prioritise attention. When poorly implemented, they create alert fatigue—so many notifications that important ones get missed.

Medication management. AI systems that check for drug interactions, dosing errors, and allergy conflicts support nursing medication administration. These aren’t new (pharmacy systems have done this for years), but AI capabilities are expanding.

Documentation assistance. As I’ve discussed in previous articles, generative AI can help draft nursing documentation. Early applications are showing promise, though human review remains essential.

Scheduling and workforce management. AI for nursing roster optimisation, patient flow prediction, and resource allocation is increasingly common in larger health services.

What AI Isn’t Doing

Despite headline claims, AI isn’t doing several things people assume:

Replacing nursing judgment. Clinical AI advises; it doesn’t decide. A nurse who delegates their clinical judgment to an algorithm is practicing unsafely. This isn’t changing soon.

Providing hands-on care. Patient care is physical. Turning patients, administering medications, providing emotional support, assessing wounds—these require human presence. No AI addresses this.

Managing complex patient situations. A patient with multiple comorbidities, social challenges, family dynamics, and treatment complexity requires holistic nursing assessment that AI can’t replicate.

Communicating with patients and families. The relational aspects of nursing—building trust, explaining conditions, navigating difficult conversations—remain entirely human.

The Job Impact Question

Nurses often ask me: “Will AI take my job?”

My honest answer: almost certainly not in the next decade, and probably not ever for most nursing roles.

Here’s why:

Nursing is fundamentally about human connection. Patients need human carers. Even if AI could theoretically replace cognitive aspects of nursing (which it can’t, currently), the relational aspects would remain.

Workforce shortages are the reality. Australia faces significant nursing shortages. We don’t have enough nurses for current demand, let alone growing demand from an aging population. AI that increases nursing productivity means better patient care, not fewer nursing jobs.

AI augments, it doesn’t replace. The practical effect of AI in nursing is handling some cognitive tasks (monitoring, documentation, decision support) so nurses have more time for care. That’s augmentation, not replacement.

That said, AI will change nursing practice. Some tasks will shift. Some skills will become more important. Career progression might look different.

Skills That Will Matter More

If I were advising nursing students or early-career nurses:

AI literacy. Understanding what AI can and can’t do. Knowing how to interpret AI recommendations critically. Recognising when AI might be wrong.

Complex care coordination. As AI handles more routine tasks, nursing value concentrates in complex care situations that require judgment, coordination, and holistic assessment.

Technology interface skills. Navigating clinical systems, using digital tools effectively, providing feedback on technology design.

Patient advocacy in digital health. Helping patients understand their digital health information, navigate technology-enabled care, and maintain human connection in increasingly digital systems.

Skills That Might Matter Less

Some nursing tasks are likely to be supported by AI, changing what skills are most valuable:

Routine documentation. If AI helps draft documentation, the skill isn’t writing notes—it’s reviewing AI drafts for accuracy and completeness.

Vital sign monitoring. Automated monitoring and AI alerting shifts nursing attention from checking observations to responding to exceptions.

Information lookup. AI can surface relevant clinical information quickly. Nurses don’t need encyclopedic memory; they need critical evaluation skills.

What Nursing Leaders Should Do

If you’re in nursing leadership, some recommendations:

Engage nurses in AI decisions. Don’t implement AI on nurses—implement it with them. Their workflow knowledge is essential for successful deployment.

Invest in AI literacy education. Basic understanding of AI capabilities and limitations should be part of nursing professional development.

Advocate for nursing perspectives in AI governance. Clinical AI governance committees need nursing representation. Nurses see different aspects of AI performance than doctors or IT staff.

Monitor workload impacts honestly. AI that increases nursing workload (through additional documentation, alert management, or system navigation) isn’t saving time. Track real impacts, not theoretical benefits.

Protect time for human care. If AI frees up time, ensure that time goes to patient care, not additional administrative burden. Efficiency gains should benefit patients and nurses, not just operational metrics.

The Bigger Picture

AI in nursing is part of a larger question about technology in healthcare. How do we capture technology benefits while preserving what matters about human care?

I don’t think we have this figured out yet. There’s a risk that AI implementation focuses on efficiency at the expense of care quality. There’s a risk that technology creates new burdens faster than it removes old ones. There’s a risk that nursing becomes increasingly about managing systems rather than caring for patients.

These risks aren’t inevitable. But avoiding them requires nursing voices in decisions about healthcare technology.

AI will be part of nursing’s future. What that future looks like depends on choices being made now.

---

Dr. Rebecca Liu is a health informatics specialist and former Chief Clinical Information Officer. She advises healthcare organisations on clinical AI strategy and implementation.