AI agents are computer programs that work on their own. They use large language models (LLMs) and other technology to do tasks without needing step-by-step instructions every time. Instead of waiting for people to tell them what to do next, AI agents set goals, plan how to finish them, and complete tasks on their own. This shows a change to what some call agentic AI, where AI systems act ahead and adjust to new situations.
A survey by IBM and Morning Consult in 2025 found that 99% of developers working on business AI focus on AI agents. Right now, AI agents can plan and call functions, which lets them use tools and data well. They are not yet fully independent in making hard decisions, but they can manage routine and repeating jobs that happen a lot in healthcare administration.
Healthcare administration covers many jobs like patient intake, scheduling appointments, billing, and compliance tasks. Many of these tasks repeat often and take up a lot of staff time. AI agents can help by handling phone calls from patients, checking insurance information, sorting out administrative questions, and giving updates to patients and doctors.
Healthcare administrators in the U.S. can use AI agents to make their offices work more smoothly. Clinics and medical offices usually get many phone calls, and staff must answer them all. Doing this by hand can cause long wait times, missed appointments, and unhappy patients. AI agents like those from Simbo AI can answer calls, schedule appointments, and respond to common questions without needing a person.
This kind of automation frees staff to focus on harder tasks like handling insurance claims or coordinating patient care. AI agents improve workflow, lower clerical mistakes, and reduce administrative costs. Over time, this helps make patients happier and offices run better.
Healthcare in the U.S. must follow strict rules like HIPAA to protect patient privacy. AI agents working in healthcare need to follow privacy, transparency, and accountability rules. IBM researchers such as Vyoma Gajjar and Maryam Ashoori say it is important to have ways to undo errors, keep audit logs, and include humans in the decision process to avoid mistakes and keep trust in AI.
IT managers in medical offices face challenges to get their workplaces ready for AI agents. They must organize data, protect access with APIs, and make sure systems work well with AI workflows. Chris Hay from IBM explains that success with AI agents depends more on how well healthcare groups prepare their computer systems than just on how smart the AI is.
Open source AI models are also important because they let healthcare providers change and improve AI agents to fit their specific needs. This is very useful in front-office automation where AI must connect with systems like electronic health records (EHRs), appointment schedulers, and communication tools.
Workflow automation means using technology to do repetitive tasks without much human help. AI agents help with this by being able to work independently, adjust when needed, and solve problems. For healthcare administrators, many processes like confirming appointments, reminding patients, checking insurance eligibility, and directing calls can be done faster and easier.
Agentic AI systems do more than just simple tasks. They use different kinds of data—like voices, text, and patient files—to understand what is going on and make decisions like a person would. These agents organize many AI parts to handle different sides of a workflow.
For example, in a typical medical office day, an AI agent might:
This kind of AI automation speeds up work, makes fewer mistakes, and lets staff focus on more important activities like patient care.
A review by Soodeh Hosseini and Hossein Seilani expects AI agents in healthcare to grow from helping staff to running complex workflows on their own. Tools like LangChain, CrewAI, AutoGen, and AutoGPT help build many AI agents that work together in healthcare settings.
Even with benefits, there are challenges in using AI in healthcare administration. One big challenge is keeping patient data private and secure. Since healthcare information is very sensitive, AI must follow strict laws and rules. Ethical rules are needed to watch AI actions and make sure they are fair and safe.
Another problem is that many healthcare organizations are not ready. They may not have the right technology or trained workers to handle AI efficiently. As Chris Hay from IBM says, many medical centers find it hard to connect current systems with AI technology. They must spend on new IT systems and staff training as well as AI tech.
Currently, AI agents mostly plan and call functions at basic levels. They are not fully independent when making complex medical decisions. Humans still need to supervise and make final choices.
Cost and doubts about financial benefits also slow use. Marina Danilevsky from IBM notes that although people are excited about AI, the money saved is not always clear right away. Healthcare providers must study AI plans well to make sure their spending brings real improvements.
Simbo AI creates phone automation for front-office work in healthcare. Their AI agents focus on talking with patients, automating processes, and helping reduce stress on office staff. Phone communication is very important in U.S. medical offices for managing appointments and follow-ups. Simbo AI’s technology meets these needs.
Simbo AI offers:
By automating these front-office tasks, Simbo AI shows how AI agents can improve healthcare administration. This is important for small to medium practices that often have limited resources and busy staff.
By 2025, AI agents are expected to take on more workflow automation in U.S. healthcare. They may manage tasks like insurance pre-authorization, verifying patient data, and giving support for difficult decisions as they get better. This will help healthcare groups lower costs, reduce errors, and improve patient services.
Ongoing research in agentic AI is working on making AI agents more independent and able to make decisions while keeping ethics and safety in mind. Healthcare providers, tech companies, and regulators must work together to create clear rules that balance progress with privacy and security.
Medical practice administrators and IT managers should prepare early by organizing data systems, training workers, and setting up clear ways to monitor AI.
AI agents like those from Simbo AI are already changing front-office work. With more improvements and use, AI agents will become important tools in healthcare administration. This will let healthcare workers focus more on patient care and less on paperwork.
In conclusion, AI agents are an important new technology for healthcare administration in the U.S. They can automate difficult workflows, especially front-office phone tasks. This means less work for staff on repeating jobs and faster service for patients. There are challenges with rules, ethics, and readiness, but more attention from developers and healthcare workers shows their growing role by 2025. For those managing healthcare groups, learning about and using AI agents will be key to staying effective in a more digital healthcare world.
An AI agent is a software program capable of autonomous action to understand, plan, and execute tasks using large language models (LLMs) and integrating tools and other systems. Unlike traditional AI assistants that require prompts for each response, AI agents can receive high-level tasks and independently determine how to complete them, breaking down complex tasks into actionable steps autonomously.
AI agents in 2025 can analyze data, predict trends, automate workflows, and perform tasks with planning and reasoning, but full autonomy in complex decision-making is still developing. Current agents use function calling and rudimentary planning, with advancements like chain-of-thought training and expanded context windows improving their abilities.
According to an IBM and Morning Consult survey, 99% of 1,000 developers building AI applications for enterprises are exploring or developing AI agents, indicating widespread experimentation and belief that 2025 marks the significant growth year for agentic AI.
AI orchestrators are overarching models that govern networks of multiple AI agents, coordinating workflows, optimizing AI tasks, and integrating diverse data types, thus managing complex projects by leveraging specialized agents working in tandem within enterprises.
Challenges include immature technology for complex decision-making, risk management needing rollback mechanisms and audit trails, lack of agent-ready organizational infrastructure, and ensuring strong AI governance and compliance frameworks to prevent errors and maintain accountability.
AI agents will augment rather than replace human workers in many cases, automating repetitive, low-value tasks and freeing humans for strategic and creative work, with humans remaining in the decision loop. Responsible use involves empowering employees to leverage AI agents selectively.
Governance ensures accountability, transparency, and traceability of AI agent actions to prevent risks like data leakage or unauthorized changes. It mandates robust frameworks and human responsibility to maintain trustworthy and auditable AI systems essential for safety and compliance.
Key improvements include better, faster, smaller AI models; chain-of-thought training; increased context windows for extended memory; and function calling abilities that let agents interact with multiple tools and systems autonomously and efficiently.
Enterprises must align AI agent adoption with clear business value and ROI, avoid using AI just for hype, organize proprietary data for agent workflows, build governance and compliance frameworks, and gradually scale from experimentation to impactful, sustainable implementation.
Open source AI models enable widespread creation and customization of AI agents, fostering innovation and competitive marketplaces. In healthcare, this can lead to tailored AI solutions that operate in low-bandwidth environments and support accessibility, particularly benefiting regions with limited internet infrastructure.
Simbo is using AI agents to automate all phone related workflows. Connect now to know more.
Schedule AI Agents Demo Now© Since 2019, Simbo AI.
