Before a Health System Deploys Agentic AI
What Changes When AI Starts Taking Action
Artificial intelligence in healthcare has largely been used to help people interpret information. It can summarize records, identify patterns, draft communications, and support clinical or administrative decisions.
Agentic AI can go further.
An AI agent may be able to retrieve information from another system, complete a task, submit documentation, schedule an appointment, communicate with a payer, monitor a workflow, or decide that an issue should be escalated to a person.
Once software can take actions inside a healthcare organization, the organization needs clear rules about what it is allowed to do.
That raises practical questions involving authority, patient information, vendor contracts, cybersecurity, regulatory compliance, oversight, and responsibility when something goes wrong.
Where Agentic AI May Show Up First
Administrative operations are an obvious starting point.
An agent could potentially gather information required for prior authorization, complete forms, submit requests, monitor payer responses, and identify when an appeal is needed.
Similar systems could help coordinate referrals, schedule appointments, confirm follow up tasks, or support revenue cycle operations.
These uses may appear lower risk than clinical decision making, but administrative actions can still affect patient care. An incorrect submission can delay treatment. A scheduling mistake can prevent timely follow up. Incorrect information can create reimbursement or compliance problems.
Clinical uses raise the stakes further.
A system could review medical history, laboratory results, medication information, and other records before a visit. It might identify a care gap or monitor information from connected devices and decide when a clinician should be alerted.
At that point, healthcare organizations need to understand where assistance ends and decision making begins.
Start With Authority
Before deployment, organizations should define what the agent is actually allowed to do.
Can it read information? Can it change information? Can it draft a communication? Can it send it? Can it identify a denied claim? Can it submit an appeal? Can it schedule a patient without additional approval?
Each step creates a different level of responsibility.
Some actions may be appropriate for automation. Others may require human approval. Certain activities may need to remain outside the system’s authority entirely.
Those boundaries should be deliberate and documented.
Human Oversight Has to Be Real
Keeping a human involved does not automatically create meaningful oversight.
Organizations should determine when a person enters the process, what information the person receives, whether the reviewer has the necessary expertise, and whether there is enough time for meaningful review.
A person who approves hundreds of automated decisions may eventually treat approval as routine.
Healthcare organizations should decide which actions require review, who is qualified to perform that review, and what happens when the person disagrees with the system.
Where the Legal Issues Show Up
Agentic AI may require broader access to patient data and operational systems than traditional software.
Organizations should know what information the agent can retrieve, which systems it can enter, what credentials it uses, and whether its access changes depending on the task.
HIPAA and other privacy obligations remain relevant. Vendor contracts should also address what can be done with information obtained through the relationship, including whether data can be used to improve models or support services provided to other customers.
Cybersecurity becomes more important when software can act across multiple systems. Organizations should consider permissions, credentials, incident response, and how access can be suspended quickly if something goes wrong.
Contracts should address what actions the agent is permitted to perform, how system changes are communicated, what records are retained, and who is responsible for incorrect or unauthorized actions.
Responsibility Continues After Deployment
Healthcare software operates in an environment that changes constantly. Vendors update products. Electronic health records change. Interfaces are modified. New data sources are added. Security vulnerabilities emerge.
An agent that worked properly when first deployed may behave differently later.
Organizations should determine who is responsible for monitoring those changes.
The vendor may control the software. The health system may control the workflow. A third party may provide an interface. Another company may supply a connected device.
Responsibilities should be clear before an incident occurs.
The agreement should address who monitors updates, who validates significant changes, who investigates problems, and who is responsible for correcting them.
Organizations Need to Be Able to Reconstruct What Happened
If an automated action is challenged, the organization may need to determine what information the agent accessed, what instructions it received, which systems it interacted with, what actions it performed, and whether anyone approved those actions.
That makes auditability important.
Detailed records may be needed for patient safety reviews, compliance investigations, payer disputes, cybersecurity incidents, litigation, and vendor management.
If an organization cannot determine what its own system did, responding to a problem becomes much more difficult.
What Executives Should Review Before Deployment
Before giving an AI agent authority to act, healthcare organizations should be able to answer a few basic questions:
What actions can the system perform?
Which actions require human approval?
What information can it access?
Which systems can it enter or change?
Who reviews information submitted outside the organization?
Who is responsible when an automated action is wrong?
Can the organization reconstruct what the system did?
Who monitors the technology after deployment?
How are software updates and changes evaluated?
Do existing contracts address the responsibilities created by automated action?
Agentic AI may remove significant amounts of administrative work from healthcare and improve coordination across fragmented systems.
Those benefits depend in part on whether organizations put appropriate controls around the technology before relying on it.
Software that can act requires more than an accuracy review.
Healthcare organizations need to know what it can do, who is watching it, and who is responsible for the result.
How Lanton, Lanton & Sosa Law Can Help
Lanton, Lanton & Sosa Law advises healthcare and life sciences organizations on regulatory compliance, technology contracting, data governance, healthcare operations, cybersecurity, and emerging issues involving artificial intelligence.
Organizations evaluating agentic AI may need to review vendor agreements, data rights, privacy obligations, cybersecurity responsibilities, approval procedures, audit requirements, liability provisions, and the regulatory requirements associated with particular uses of the technology.
Reviewing those issues before deployment can help an organization determine whether its legal and operational controls are keeping pace with the authority it is giving the software.