How Hospitals Use Generative AI to Improve Administration

Hospitals across the United States are increasingly adopting generative AI technologies. The goal is to make administrative work more efficient and to improve communication between healthcare professionals, patients, and support staff. Recent improvements in large language models (LLMs) have fueled this trend. They help hospitals:

One major shift is the integration of generative AI tools into electronic health record (EHR) systems. These AI-powered tools can help draft responses to patient messages, reducing the time doctors and nurses spend on routine communication. 

By August 2023, Epic’s CEO shared that their AI message-drafting tool was active in more than 150 health systems and helped generate over 1 million draft replies to patients each month. According to Epic, about two-thirds of its client organizations now use generative AI features and are seeing real time savings on administrative tasks.

Another key development is the rise of ambient clinical documentation. These AI tools listen to conversations between doctors and patients and then create draft notes in real time. This reduces the burden of note-taking and gives clinicians more time to focus on patient care. At Cleveland Clinic, a pilot program using ambient documentation showed promising results. Clinicians experienced less burnout, reported greater satisfaction, and worked more efficiently across specialties.

To make documentation easier, many hospitals have started using AI-powered voice assistants. These tools allow doctors to speak their notes rather than type them, saving time and improving accuracy. Rush University System for Health expanded its use of these tools after early pilot programs showed that they helped doctors complete their work more quickly and reduced the paperwork that used to spill into their personal time.

Generative AI is also being tested in healthcare revenue cycle management. These tools can help automate difficult administrative tasks, such as writing documents to appeal insurance denials. MultiCare Health System, for example, is testing generative AI for these processes. They expect the tools to reduce manual labor, speed up claim processing, and make the insurance appeals process more accurate.

Hospitals are using AI not only for internal tasks but also to improve how they communicate with patients. Generative AI can help doctors respond faster to simple patient questions, improving both patient satisfaction and clinical efficiency. For instance, Mayo Clinic uses AI to manage millions of patient messages. This allows healthcare providers to focus on more complex needs.

Some health systems, such as UC San Diego Health, are being open about the use of AI in their messages. They notify patients when a message is AI-generated. However, policies on transparency vary across organizations, with some systems still deciding how best to explain AI use to their patients.

A major benefit of using generative AI in hospitals has been reducing clinician burnout. Reid Health, a regional hospital system, reported a 60% drop in the time clinicians spent on documentation after work hours thanks to AI-powered tools. They also saw an 87% improvement in response times to patient calls. Riverside Health observed similar results, including lower mental stress among clinicians, better job satisfaction, and higher-quality patient care.

Hospitals are also using generative AI to support their internal operations. These tools can summarize long documents, write internal communications, and help with clinical research administration. Dana-Farber Cancer Institute, for example, has adopted internal AI systems used widely by both administrative and research staff. The tools help streamline document reviews, simplify tasks, and manage sensitive data while maintaining strict privacy and security standards.

As AI use increases, hospitals and tech companies are working closely to ensure these tools are safe, accurate, and adapted to clinical environments. These collaborations focus on building AI that fits naturally into healthcare workflows, supports clinicians, and protects patient data. Ethical oversight is a top priority, with hospitals setting high standards for transparency, bias prevention, and responsible use.

Many health systems are forming long-term partnerships with AI providers to co-develop tools that meet their specific needs. These partnerships aim to ensure that generative AI is not only effective but also respectful of patients’ rights and the unique challenges of healthcare.

The growing use of generative AI in hospital administration marks a major shift in how healthcare organizations manage their operations. These technologies offer significant potential to: 

As adoption increases, healthcare leaders must remain committed to careful oversight, open communication, and ethical use. Protecting privacy, reducing bias, and ensuring that AI tools support human decision-making, not replace it, will be essential to building trust and delivering long-term value.

In summary, generative AI is becoming a key tool in healthcare administration. It is helping hospitals run more smoothly, supporting overworked staff, and making care more responsive. To fully realize these benefits, hospitals must stay focused on safety, transparency, and putting patients and providers first.