Enhancing Stakeholder Theory in the Context of AI: A Systematic Approach to Identifying and Engaging Diverse Roles

Artificial Intelligence (AI) is becoming a key part of healthcare management in the United States. It is now used in tasks like front-office phone operations, changing how healthcare organizations connect with patients. For companies like Simbo AI, which focus on AI-powered phone automation and answering services, it is important to understand and manage the different people involved in AI projects for ethical and lasting success.

This article talks about how the roles of people involved in AI projects in healthcare are changing. It points out the need to recognize different types of people affected by AI, including those without direct control over the systems. It also explains how AI can improve work processes in medical offices while keeping in mind the ethical duties that come with using this technology.

Understanding Stakeholder Roles in AI Healthcare Projects

AI projects are different because they might cause harm or problems for people, communities, and even the environment. Healthcare managers, owners, and IT staff in the U.S. must know that AI systems affect more than just the people who make or use them; many others are also affected indirectly.

A study by Gloria J. Miller, published in Project Leadership and Society, says that project owners, managers, teams, and organizations act as “moral agents.” This means they have ethical duties throughout the AI project’s life. AI decisions can impact important health services like patient communication, privacy, and access to care. So, knowing who is involved and talking with them properly is very important.

The study sorts stakeholders into six roles based on how likely they are to be harmed and how urgent their needs are. One group is “passive stakeholders.” These are people or groups affected by AI but usually can’t change or influence the project. In healthcare, passive stakeholders often include patients, caregivers, or non-technical staff who feel the effects of automated phone systems but don’t have much say in how they are made or used.

Using a method that combines stakeholder theory helps healthcare leaders find all relevant groups early on. This allows teams to create AI systems that reduce risks, avoid harm, and follow ethical rules. For example, practices using AI phone systems like Simbo AI’s need to listen to concerns from staff about reliability and from patients about ease of use. This helps make adoption smoother and keeps patients happier.

The Moral and Ethical Responsibilities of AI Project Managers in Healthcare

AI project managers and owners in U.S. healthcare must understand that their work directly affects people’s health and well-being. This responsibility goes beyond technology and includes thinking about how AI decisions affect vulnerable groups.

Miller’s research points out that project managers must involve both active and passive stakeholders early in planning. Ignoring passive stakeholders can lead to ethical problems and harm the trust in AI systems. For example, if an AI answering system can’t spot urgent patient needs well, it might cause delays that hurt patients.

The idea of harm in the stakeholder model helps managers decide which groups need the most attention because of the possible impact. When combined with urgency, it creates a way to make ethical choices that consider risks and stakeholder needs.

In U.S. healthcare, following rules and ethical duties is essential. Laws like the Health Insurance Portability and Accountability Act (HIPAA) require patient data to be protected. AI systems for phone answering and scheduling must follow these privacy rules. Project managers need to make sure these rules are built into the system from the beginning.

Categorizing Stakeholders in AI Healthcare Projects

• Project Owners and Sponsors: Healthcare managers, practice owners, or IT directors who control the budget and goals.
• Project Managers and Teams: IT staff, clinical experts, and developers who design and use AI systems like Simbo AI’s phone automation.
• Operators: Administrative workers who use AI systems every day for patient calls and scheduling.
• Passive Stakeholders: Patients, caregivers, and some staff affected by AI but without control over it.
• Regulatory Bodies: Compliance officers, health departments, and government agencies making sure laws are followed.
• Technology Vendors: Companies providing AI tools and support, like Simbo AI.

Including people from all these groups early in projects helps U.S. medical practices build AI tools that fit their needs and protect patients.

AI and Workflow Automation in Healthcare Administration

One immediate effect of AI in medical offices is workflow automation. Simbo AI’s phone automation shows how AI can handle tasks like answering patient calls, booking appointments, managing questions, and offering support 24/7 without full human help.

This reduces work for office staff, letting them focus on harder tasks that need human contact. For instance, instead of answering common questions about hours or directions, staff can help coordinate care or manage urgent cases.

AI systems also improve patient access by giving quick answers and easy booking. This is very helpful in busy offices or ones with many patients. In the U.S., where wait times and paperwork are big issues, AI phone services offer a practical fix.

Still, using AI for workflow automation needs careful control. Healthcare leaders must make sure AI can recognize urgent calls and pass them to humans when needed. Systems should avoid errors that slow care or make patients unhappy.

Listening to stakeholders remains important. By getting feedback from staff and patients on AI phone system performance, organizations can adjust AI responses to better meet needs and keep safety high.

Also, proper training for staff helps them understand what AI can and cannot do. This lowers resistance to new tools and builds trust among users working with AI.

The Role of Stakeholder Theory in Sustaining AI Development

Healthcare AI projects in the U.S. increasingly see that success depends on being accountable to many groups, especially those indirectly affected by AI use. The clear method for finding and involving stakeholders gives healthcare leaders a good plan to manage AI projects the right way.

Including passive stakeholders through their representatives makes sure AI systems consider needs that may otherwise be missed. For example, patients with limited English or older people might have trouble with automated phone systems. By listening to them, healthcare offices can create AI that is easier to use and fairer.

Healthcare IT staff must work closely with AI developers and users to keep ethical standards that protect patient data and trust. This cooperation makes sure AI development matches the reality of busy medical offices.

The stakeholder model, adapted for healthcare AI projects, helps prioritize ethics along with technical goals. It supports the responsibility of project leaders to involve all stakeholders, even those with little power, to avoid harm and promote social care.

Application of AI Stakeholder Theory to Medical Practice Phone Automation

Simbo AI’s technology shows many ideas from stakeholder research. By automating front-office phone services, it affects many people—from IT managers setting up the system, to office staff using it daily, to patients getting faster and clearer communication.

Medical office managers and owners in the U.S. who use stakeholder methods include both technical and non-technical users in feedback sessions. IT managers should regularly check how administrative staff experiences the system to find problems or spots for improvement.

Patient feedback from surveys or talking directly can reveal issues like confusion or delays in urgent care calls caused by AI. Including this passive stakeholder input during updates helps healthcare providers keep their ethical duties in today’s digital world.

Following healthcare laws such as HIPAA is also an important part of stakeholder focus. Developers and managers must work with compliance officers to build data privacy and security into AI workflows.

This teamwork reflects the moral agent role that project owners and managers have—making sure technology benefits healthcare while lowering risks.

Using a clear and organized way of identifying and involving stakeholders helps U.S. healthcare groups use AI systems like Simbo AI’s front-office automation more carefully. This protects patient safety and ethical standards while improving work processes, supporting better healthcare in a digital world.