The Accelerating Adoption of Agentic AI in Healthcare: Exploring Its Potential to Automate Routine Tasks and Address Staffing Challenges

Agentic AI is different from traditional AI and robotic process automation because it can work on its own and has goals. It can think, plan, and act without help, and it learns from data and its environment. Unlike simple systems that follow set rules, agentic AI changes based on new information, which is useful in healthcare where things can change quickly.

In healthcare, agentic AI can do many tasks by itself. These include scheduling patients, managing resources, helping with diagnosis, handling medicine, and keeping systems safe. By doing these repeated and time-consuming jobs, it lets healthcare workers spend more time on patient care and important work.

A survey from 2025 showed that 27% of healthcare groups in the U.S. are already using agentic AI for automation, and 39% more plan to use it soon. Most healthcare groups, 94%, say AI is important for how they work, and 86% are already using it now.

Addressing Staffing Challenges Through AI Automation

Healthcare has long had problems with not enough workers, tired staff, and a lot of paperwork. Agentic AI helps by doing the routine jobs that need many people, like booking appointments, registering patients, processing insurance claims, and sending follow-up messages.

Jesse Tutt, a Program Director at Alberta Health Services, said using AI saved the same amount of work as over 238 years in a short time. This large drop in manual work makes things easier for staff and speeds up patient services like check-in and managing medical records.

Also, agentic AI can work all the time without getting tired. That helps hospitals keep services running well even if there are fewer workers or more patients. Staff get to focus on patient care, making decisions, and fixing tough problems instead of paperwork.

Improving Patient Scheduling and Operational Efficiency

One big use for agentic AI today is helping with patient scheduling and managing waitlists. About 55% of healthcare groups in the U.S. are using or finishing setting up AI for booking appointments and lowering no-shows. Agentic AI lets patients schedule themselves, get reminders, and update their health details easily. This helps reduce paperwork and keeps patients involved.

AI can also predict if a patient might miss an appointment and reschedule it ahead of time. This saves money and makes clinics run better. Automation like this helps smooth out clinical work, lowering wait times and using resources well.

Agentic AI does more than scheduling. It can manage hospital resources like beds and staff shifts based on real-time data and expected patient needs. This helps hospital leaders balance workloads and react quickly to changes.

Enhancing Clinical Support and Patient Safety

Agentic AI helps doctors with diagnosis and treatment decisions. AI looks at lots of medical data—like images, lab tests, and patient history—faster and sometimes more accurately than people alone.

For example, AI-assisted diagnosis has cut errors by up to 85% in some areas. Machine learning can spot small problems in images that humans might miss. This helps doctors find diseases like cancer early. About 37% of healthcare groups use or plan to use AI to improve diagnosis and treatment planning in cancer care.

This technology supports clinical decisions by giving recommendations based on evidence. This helps lower differences in care and improve results. Also, AI health assistants watch patients’ vital signs and symptoms from afar, giving alerts and advice any time. This monitoring can lower hospital readmissions and support early care.

Improving Pharmacy and Medication Management

Pharmacies also benefit from agentic AI. AI helps with calculating doses, checking for medication errors, and keeping drug delivery on time. Nearly half (47%) of healthcare groups use AI tools for these pharmacy tasks.

With AI making medicine management smoother and helping patients report symptoms quickly, safety and efficiency improve. Pharmacy staff can focus more on important clinical decisions and talking with patients instead of routine work.

AI and Workflow Automation in Healthcare Practices

Healthcare administrators and IT managers need to understand how agentic AI fits with current workflows to get the most benefits. AI workflow automation breaks big healthcare processes into smaller jobs that the AI can do on its own.

Most (91%) healthcare groups know that a full approach to AI use is needed. This means connecting people, processes, and technology. AI should not work alone but link with electronic health record (EHR) systems, patient platforms, billing software, and other healthcare IT.

This connection lets data flow smoothly between systems. AI can then use real-time information to make decisions and follow up with actions. For example, if a patient misses an appointment, AI can reschedule and send messages automatically, keeping things moving and lowering admin work.

This working together helps with compliance, quality checks, and reporting by managing data in one place. IT managers make sure AI programs are trained well, updated often, and safely connected to healthcare networks.

Addressing Privacy, Bias, and Governance Concerns

Even though agentic AI has benefits, it also brings up worries about patient privacy, bias, and ethical use. Patient privacy is a top concern for 57% of healthcare leaders. About 49% worry that AI medical advice could be biased because of past data inequalities.

Healthcare groups must follow privacy rules like HIPAA and GDPR, and use strong cybersecurity methods like encryption, access controls, constant monitoring, and quick responses to incidents. Transparent AI rules are also needed to check decisions, make sure AI is fair, and keep doctors’ trust.

Organizations also need to train staff to reduce the AI skill gap. This helps workers understand what AI can do and its limits so they use it properly and safely.

Agentic AI Driving Healthcare Cost Savings and Innovation

Agentic AI can save a lot of money. Research by Accenture says AI could save the U.S. healthcare system around $150 billion each year by 2026. Savings come from cutting labor costs, fewer diagnostic mistakes, less unnecessary treatment, and better efficiency.

It also raises productivity. For example, AI automation in software and admin jobs has raised productivity by up to 55%. In customer service, AI chatbots can cut call times by 70% and wait times by 30%. Healthcare call centers are showing this trend too.

Importantly, agentic AI helps staff well-being. About a third of healthcare workers say AI improves their work-life balance and job performance by lowering paperwork.

Real-World Examples and Future Outlook in the U.S.

• Alberta Health Services says AI has saved hundreds of years of manual work and improved patient satisfaction.
• Top healthcare providers use AI for scheduling patients and reading medical images.
• AI chatbots like Vodafone’s TOBi, although not in healthcare, handle over 70% of questions, showing what may be possible in medical offices.

The agentic AI market in healthcare was worth $538.51 million in 2024 and is expected to grow fast by over 45% a year until 2030. This shows how quickly it is being used.

In the future, agentic AI will likely become even more independent, connect better with clinical work, and be used more in robotic surgery, maintenance, and personalized treatment plans. These developments could change how U.S. healthcare providers handle regular operations and worker shortages.

Recommendations for U.S. Medical Practice Leaders

Medical practice leaders should get ready for agentic AI by:

• Figuring out which routine tasks and slow points can be automated.
• Making sure AI works well with EHRs, management systems, and patient portals.
• Training staff to work well with AI, including how to use it fairly and fix problems.
• Setting rules to keep data private, hold AI accountable, and reduce bias.
• Starting small with pilot programs to test results, adjust workflows, and gain trust before using AI widely.

By following these steps, medical practices can use agentic AI to work better, lower costs, and meet patient needs while dealing with staffing problems.

Agentic AI is a practical and growing technology that can change routine healthcare work and staff management in the U.S. Its growing use offers clear benefits in clinical, administrative, and operational areas. Healthcare leaders should consider it to update their practices and improve patient care in a complex environment.