How AI powers healthcare innovation

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AI is revolutionising how healthcare is delivered, managed, and experienced. In an industry where decisions affect life and death, AI can help optimise operations, boost worker productivity, and enhance patient experiences.

Already, AI is helping organisations reimagine what's possible in medicine and transform medical systems from reactive to proactive. In fact, new healthcare research by ServiceNow found that 77% of healthcare organisations plan to increase their AI investments in the next fiscal year.

Let’s explore how AI powers healthcare innovation.

Table of contents

• What is AI in healthcare?
• What are AI tools in healthcare?
• Why AI in healthcare is important
• How AI in healthcare works
• Where is AI used in healthcare today?
• Will AI replace healthcare workers?
• What is the future of AI in healthcare?
• The imperative for action

What is AI in healthcare?

AI in the healthcare industry is the application of AI technologies, including machine learning and natural language processing, to improve patient care and operations. Think of it as the seamless fusion of computational power and clinical and nonclinical expertise.

Healthcare AI converts vast collections of complex medical data into actionable intelligence that can drive measurable outcomes: saved lives, reduced costs, and better patient experiences.

Agentic AI is the next degree of healthcare intelligence. Whereas traditional AI observes patterns, agentic AI acts on them. Autonomous AI agents analyse data when prompted, identify opportunities, make decisions, and initiate actions to achieve specified goals. They continuously learn, adapt, and evolve—improving with each interaction.

Nearly half (45%) of the healthcare leaders we surveyed are considering adopting agentic AI in the next year.

What are AI tools in healthcare?

Today's healthcare AI ecosystem offers purpose-built solutions designed to address specific challenges across the care continuum:

• Machine learning platforms analyse complex clinical data to identify disease patterns and predict patient outcomes with remarkable accuracy.
• Natural language processing (NLP) transforms unstructured medical notes into actionable insights, unlocking value from previously inaccessible data.
• Computer vision systems interpret medical imaging with a precision that matches or exceeds what human specialists can do.
• Predictive analytics tools forecast patient deterioration before traditional symptoms appear.
• Virtual health assistants deliver personalised care guidance while optimising resource allocation.

The most powerful AI implementations integrate with existing workflows, amplifying human capabilities rather than replacing them. The organisations achieving breakthrough results aren't deploying these tools in isolation. They're implementing them on unified platforms that seamlessly connect AI capabilities across the enterprise.

Why AI in healthcare is important

Clinician burnout, rising costs, data overload, and increasing patient expectations are taking their toll on the healthcare industry. AI addresses these challenges head-on to improve the caregiver experience, strengthen risk and compliance, and optimise operations for seamless care.

In addition, AI can help streamline research and development, transform compliance from a bottleneck to a competitive advantage, identify and address operational and cybersecurity risks, enhance IT and operational technology connectivity, and increase visibility and control across global operations.

Our research found that 83% of healthcare providers that have implemented AI have improved experiences. And 55% of healthcare companies have seen gains in their gross margins.

Besides solving existing problems, AI is helping to uncover new possibilities for care delivery, scientific discovery, and business model innovation that were previously unimaginable.

How AI in healthcare works

Healthcare AI transforms raw, disjointed medical data into coherent, actionable intelligence through a sophisticated process that mirrors and enhances human cognition:

1. Data integration: Unifying information from disparate sources—electronic health records, imaging, genomics, and real-time monitoring
2. Pattern recognition: Applying advanced algorithms that identify subtle correlations and anomalies across vast data sets that could take human analysts years to discover
3. Predictive modelling: Generating evidence-based recommendations by comparing current patients, medical device usage, drugs, and other treatments against millions of historical cases
4. Decision support: Providing a clear rationale for recommendations that helps build trust with clinical and nonclinical users
5. Continuous learning: Refining accuracy through feedback loops that become more precise with each interaction

The true power emerges when these capabilities integrate directly into both clinical and nonclinical workflows, delivering insights precisely when and where decisions are made.

Where is AI used in healthcare today?

AI has transitioned from innovation labs to frontline implementation across the healthcare ecosystem:

• Radiology departments use computer vision to detect subtle abnormalities in imaging studies and improve early cancer detection rates.
• Pharmaceutical companies accelerate drug discovery timelines from years to months through predictive modelling of molecular interactions.
• Health systems deploy predictive analytics to optimise staffing levels based on anticipated patient volumes, reducing wait times while controlling costs.
• Insurers implement NLP to streamline claims processing, reducing administrative overhead while enhancing member experiences.
• Clinicians employ diagnostic support systems to enhance detection accuracy while reducing time to diagnosis.
• Researchers use AI to accelerate hypothesis testing and literature analysis.

Forward-thinking healthcare organisations are implementing comprehensive platforms that unify these capabilities into cohesive, enterprise wide solutions.

Will AI replace healthcare workers?

AI isn't replacing healthcare professionals, but it is redefining their capabilities. The future of healthcare is humans and machines working in partnership.

The most successful AI implementations augment human expertise by automating routine tasks, surfacing relevant insights, and enabling clinicians and nonclinical employees to practice at the top of their abilities. When administrative burdens decrease, meaningful patient interactions and outcomes increase.

Nearly two-thirds (63%) of the healthcare firms we surveyed are in the process of identifying the skills needed to carry out their AI strategies. That means there are opportunities for workers to move into new roles to help manage AI technologies.

Many organisations are upskilling and training their workers to fill these skills gaps, particularly in the areas of data science, experience development, and machine learning, our research found.

What is the future of AI in healthcare?

Healthcare organisations that thrive in the coming decade will be those that move beyond point solutions to establish comprehensive AI strategies that span the entire care continuum. In the future, we can expect:

• Ambient clinical intelligence that documents patient encounters automatically, allowing clinicians to focus entirely on patients rather than screens
• Digital twins that enable treatment simulations on virtual patient models before implementing them in real life
• Autonomous systems that continuously monitor chronic conditions, adjusting treatments in real time based on patient response
• Federated learning that enables AI models to learn across institutions without compromising patient privacy

These aren't distant possibilities. They're emerging realities that forward-thinking organisations are already implementing.

The imperative for action

The organisations that will lead healthcare's next era aren't necessarily those with the most resources. Rather, they’re those with the clearest vision and most effective implementation strategies. They're the ones integrating AI capabilities across their enterprise and creating seamless experiences for clinicians, researchers, administrators, scientists, and patients alike.

More than half (51%) of the most advanced healthcare organisations in AI maturity in our study—a group we call Pacesetters—are operating with a clear vision, versus 27% of others.

In addition, 74% of Pacesetters take an AI-focused platform approach to connect their data, processes, and workflows. As a result, they’re realising 1.9 times higher productivity and 1.67 times faster innovation than their counterparts.

The future of healthcare belongs to organisations that recognise AI as the defining strategic imperative of our time.

Find out how ServiceNow can help you put AI to work in healthcare.