Key points: AI agents in healthcare are autonomous software programs that use artificial intelligence (AI). They are autonomous in their decision-making processes, but humans are required to define goals and predefined rules. As AI agents are beginning to take on more autonomous roles governance structures are needed to manage AI systems
It seems like AI agents are the new buzzword in healthcare, what even is an AI agent?
According to IBM, an AI agent is an autonomous software program that uses artificial intelligence (AI). The system autonomously performs tasks by designing workflows with available tools, connecting to electronic health records (EHRs), and using external tools to handle complex tasks with minimal human supervision. AI agents in healthcare move beyond basic conversational chat. They are autonomous in their decision-making processes, but humans are required to define goals and predefined rules. 1
How do AI agents differ from ChatGPT?
AI agents in healthcare move beyond basic conversational chat. ChatGPT is a passive knowledge engine. Models like ChatGPT wait for human prompts and output text, forcing physicians to manage every input and output: what data goes in, how it’s framed, and whether the output is accurate.
Unlike ChatGPT, AI agents can independently break down complex tasks into intermediate steps and execute them autonomously, running in a continuous loop to solve complex tasks.
AI agents are not here to replace clinical judgment. There are clear limitations where it must never operate independently, like high-risk medications or final diagnosis.
The integration of AI agents with business processes and customer management systems can also raise some serious security concerns. Sensitive employee and patient data must be stored securely . 2
What Does HIM Need?
As AI agents are beginning to take on more autonomous roles, interacting with business systems and influencing decisions, governance structures are needed to manage AI systems that are becoming increasingly embedded in business operations.
“Traditional application governance has focused primarily on access: who can use a system, what information they can access and what actions they are permitted to take. AI agents change that model. Governance must expand beyond access controls. Organizations need practical capabilities for managing AI operations, including maintaining an inventory of AI systems, assigning ownership, monitoring performance and creating processes for evaluating changes before deployment.” 3
AI technology will continue to evolve, as will the role of HIM professionals who are in a unique position to take on emerging roles with their depth of knowledge on the sources and origins of healthcare data. The challenge for HIM professionals is to identify leading practices for the management of healthcare data and information in an AI-enabled world.
HIM professionals are in a unique position to step in with their depth of knowledge on the sources and origins of healthcare data. The task for HIM professionals is to identify leading practices for the management of healthcare data and information in AI healthcare. 4
Increasing the use of AI agents will require changes and defined liability frameworks.
The advantages of AI agents are all about delegation. This needs skilled leadership. Human oversight is not an option. It is essential.
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Resources:
1; https://www.ibm.com/think/topics/ai-agents
2; https://kevinmd.com/2026/01/agentic-ai-in-medicine-moving-beyond-chatgpt.html
