Healthcare organizations in the U.S. are using AI more often. According to the Global Enterprise AI Survey 2025, 94% of these groups see AI as important, and 86% already use it a lot. About 27% use agentic AI—AI that can work on its own with little human help—and 39% plan to start using it soon.
Agentic AI can do routine tasks like scheduling patients, managing pharmacies, and helping with medical decisions. By doing these tasks automatically, AI can cut down patient wait times, reduce staff stress, and help with staff shortages. For example, Alberta Health Services says AI saved over 238 years of staff work time, which helped patients get better care.
Still, using AI widely means more than just adding new technology. Leaders agree success comes from fitting AI tools well into current workflows and how their organizations are set up.
Strategic planning is a key step for using AI well. It means linking AI projects to the goals of the organization and healthcare priorities. In the U.S., where health rules are strict and data privacy is important, planning must also address following laws and using AI fairly.
Rob Stone, Senior Vice President at SS&C Technologies, says good governance makes sure AI is used safely. This means protecting patient data from leaks, making AI decisions clear, and setting rules to prevent bias. About 57% of healthcare leaders worry about patient data privacy, and 49% are concerned about bias in medical advice.
AI cannot succeed without handling these risks first. Good governance also helps patients and staff trust that AI will not harm care quality or privacy. This is very important in the U.S., where legal problems from privacy issues can be serious, and trust is needed for patients to stay involved in their care.
Research shows that technology alone does not guarantee good results with AI in healthcare. About 31% of healthcare organizations say human factors like staff readiness and acceptance matter more than technology. Successfully using AI needs connecting people, processes, and technology well.
AI changes how workers do their jobs. A survey by SS&C found 40% of healthcare workers are learning new AI skills, and many expect new jobs because of AI. Around 31% of employees say they now focus more on strategic and creative work because AI handles routine tasks.
Health leaders and IT managers must lead training programs that:
Continuous training reduces resistance and helps staff work well with AI. This is important for daily work and future changes as AI gets better.
More than 90% of healthcare groups say it is important to organize all workflows and technologies to work smoothly together.
For administrators, this means:
For example, AI can help schedule patients with real-time booking, automatic reminders, waitlist management, and self-service portals. This lowers no-shows and makes patients happier.
Also, AI automations in pharmacy management and decision support reduce errors, speed up medication delivery, and give doctors data-backed treatment help. AI agents made just for healthcare fit well with areas like cancer, radiology, or chronic diseases.
While adopting AI means new technology, there are problems mixing it with old hospital or clinic systems. About 35% say integration is a big challenge.
Data quality is also a problem—wrong, mixed-up, or hard-to-get data hurt AI performance. Almost 44% report trouble moving big data sets fast, and 41% say their data can be inaccurate. AI needs good data, so fixing these problems is part of the plan.
Process orchestration software helps here. It makes data move smoothly between systems and lets people control AI tools centrally. This helps keep checking and improving operations.
In clinics and small medical offices, front-office work needs to be quick and patient-friendly. Simbo AI focuses on automating phone calls using AI. This helps healthcare places improve important but time-consuming tasks.
By using AI for phone calls, offices can:
This reduces manual call work for staff, who often do repetitive jobs with little need for clinical judgment. Receptionists and assistants then get more time for harder patient needs.
Also, AI phone services work 24/7, so patients get faster answers outside office hours. This improves access and satisfaction while lowering missed appointments.
When these AI systems link with electronic health records and practice software, data stays consistent and patient experience improves. Over time, AI reports can show common patient concerns, helping to improve processes.
Measuring AI’s value is important but not easy. Most healthcare groups (88%) watch AI results, but only 36% see clear benefits often. Knowing where AI helps—like in patient satisfaction, workflow, or costs—lets leaders change plans fast.
Key measures include:
Using AI is not a one-time thing. As rules change and patients or technology change, continuous review and workflow updates are needed.
This fits the idea of Digital Twin Organizations that can model workforce and process changes in real time. These models find skills gaps and problems early, allowing quick fixes. For U.S. healthcare, this approach helps manage AI integration well.
Using AI in healthcare brings workforce and security issues that need focus. About 35% of healthcare leaders say they lack enough skilled staff to manage AI. This skill gap can slow progress and waste investments.
Healthcare groups should:
Security is another concern. Around 37% of leaders see rules compliance and data protection as major challenges. Healthcare data is sensitive, and breaches can cause legal trouble and loss of patient trust.
Strong cybersecurity is key. This includes encrypting data, doing regular safety checks, and limiting access. AI itself can help improve security by finding threats faster and keeping data safe.
Healthcare in the U.S. is starting a digital change where AI will be a big part of care and operations. Nearly 67% of business leaders believe AI will change healthcare practices and create more efficient workplaces.
AI will likely grow in areas like diagnostics, remote patient monitoring, and clinical decision support. About 42% of healthcare groups have or plan to use AI in diagnosis within two years. Also, 33% focus on remote monitoring.
Success means seeing AI not just as technology but as part of a plan. By organizing processes, preparing workers, setting rules, and watching results, healthcare groups can use AI to improve care quality, patient experience, and efficiency.
For administrators, practice owners, and IT managers in the U.S., using AI needs a balanced plan. Technology is important, but it is just as important to invest in people and processes that support that technology.
Front-office AI tools, like those from Simbo AI, show how AI can help quickly improve patient communication. Strategic planning, fair governance, workforce training, and data handling are needed to grow and keep these gains.
Continuous learning and changing workflows will help U.S. healthcare organizations meet the changing needs of patients and staff as AI becomes more common. Those who use all parts of integration well are more likely to see steady benefits and success over time.
27% of healthcare organizations report using agentic AI for automation, with an additional 39% planning to adopt it within the next year, indicating rapid adoption in the healthcare sector.
Agentic AI refers to autonomous AI agents that perform complex tasks independently. In healthcare, it aims to reduce burnout and patient wait times by handling routine work and addressing staffing shortages, although currently still requiring some human oversight.
Vertical AI agents are specialized AI systems designed for specific industries or tasks. In healthcare, they use process-specific data to deliver precise and targeted automations tailored to medical workflows.
Key concerns include patient data privacy (57%) and potential biases in medical advice (49%). Governance focuses on ensuring security, transparency, auditability, and appropriate training of AI models to mitigate these risks.
Many believe AI adoption will improve work-life balance (37%), help staff do their jobs better (33%), and offer new career opportunities (33%), positioning AI as a supportive tool rather than a replacement for healthcare workers.
Currently, AI is embedded in patient scheduling (55%), pharmacy (47%), and cancer services (37%). Within two years, it is expected to expand to diagnostics (42%), remote monitoring (33%), and clinical decision support (32%).
AI automates scheduling by providing real-time self-service booking, personalized reminders, and allowing patients to access and update medical records, thus reducing no-shows and administrative burden.
AI supports medication management through dosage calculations, error checking, timely medication delivery, and enabling patients to report symptom changes, enhancing medication safety and efficiency.
AI reduces wait times, assists in diagnosis through machine learning, and offers treatment recommendations, helping clinicians make faster and more accurate decisions for personalized patient care.
91% of healthcare organizations recognize that successful AI implementation requires holistic planning, integrating automation tools to connect processes, people, and systems with centralized management for continuous improvement.
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