Future trends in healthcare AI: agentic automation, addressing the talent shortage, and prioritizing domain-specific customization over cost in AI tool selection

Agentic automation means AI systems can do complex tasks mostly on their own. Simple AI tools mostly help people by giving suggestions or answering easy questions. Agentic AI works more independently. It can manage workflows, make decisions, and handle tasks that people usually did manually.

In 2024, agentic automation became more common in healthcare AI. Menlo Ventures says it powers about 12% of AI uses in businesses, with healthcare being one of the top fields. This kind of AI can handle jobs like automating clinical notes, managing administrative work, coding, triage, and handling billing cycles.

Eleos Health is one example of agentic AI in healthcare. Their AI summarizes meetings and creates clinical notes automatically, sending them right to electronic health records (EHRs). This helps clinicians spend less time on paperwork and more time with patients. Agentic automation can also follow up on unfinished tasks, send reminders, or route work to specialists without needing a person to step in.

Agentic AI’s ability to manage complicated tasks could be very useful in medical offices. Front office tasks like phone calls, scheduling, patient check-in, and billing often need constant attention. AI phone answering services, like Simbo AI, might change from simple call answering to handling all parts of a patient’s first contact, such as booking appointments and answering payment questions, before a human gets involved.

Using these AI tools fits with U.S. healthcare goals to improve patient satisfaction and run operations more smoothly. Providers want to cut wait times and reduce administrative work, and AI automation can help. But moving to agentic automation needs careful planning. Healthcare places need to prepare for changes in workflows and staff roles. They must also make sure the AI systems meet quality standards and privacy rules.

Addressing the Growing AI Talent Shortage in Healthcare

As AI becomes more important in healthcare, there is a bigger need for workers who know both AI technology and medical work. Menlo Ventures says there is a big shortage of people with both skills. This shortage has made salaries much higher—sometimes two or three times normal pay. This makes hiring and keeping good workers harder.

Many medical practices in the U.S. find it tough to hire people who can use, manage, and improve AI tools well. These workers need to understand clinical workflows, laws like HIPAA, and AI features such as natural language processing and ambient scribing.

The shortage could slow down how fast healthcare uses AI or make organizations depend more on outside vendors. Still, many providers do not want to fully outsource AI tools since they need careful adjustments to fit their special workflows and meet rules.

To handle this talent gap, healthcare managers are trying several ideas:

• Training Current Staff: Teaching existing employees AI basics and how to fit AI into workflows builds internal skills. For example, H&M’s “Amplified Intelligence” program helps workers and AI work better together.
• Working with Vendors Offering Support: Choosing AI providers who offer customization and ongoing help can make up for missing talent.
• Partnering with Schools and Training Centers: Some healthcare groups team up with universities to create programs that teach both healthcare and AI skills.
• Investing in AI Governance: Strong rules and management of AI use ensure it is ethical, legal, and works well. This helps less specialized staff manage AI safely.

Until more AI experts are available, healthcare providers need to carefully balance buying AI tools with having enough support to keep them working well.

Prioritizing Domain-Specific Customization Over Cost

When picking AI tools, healthcare groups often have tight budgets and many needs. But new data shows that price is not the main factor in choosing generative AI in healthcare. Only about 1% of decision makers say cost is their top concern.

Instead, the key factors are a clear return on investment (ROI) and how well the AI fits healthcare workflows and rules. Customization for specific healthcare areas is important—it makes up about 26% of what matters in choosing AI. ROI is the biggest factor at 30%.

This focus on customization makes sense because healthcare is complex. Generic AI tools might be cheaper upfront but often don’t work well or give full benefits. They might not connect easily with EHR systems or handle detailed tasks in patient care.

For example, ambient scribes like Eleos Health or Abridge automate clinical notes. Their tools understand medical terms better and follow healthcare laws. AI tools for front-office phone tasks, like Simbo AI, focus on patient calls, handling healthcare questions, and routing calls correctly.

Medical practice managers in the U.S. should look for AI tools that offer:

• Integration with Existing Systems: AI needs to work well with EHRs, practice software, and billing.
• Adaptability to Local Rules: Compliance with HIPAA and specific state laws is a must.
• Customized Workflows: AI should support tasks like appointment setting, insurance checks, and patient intake without causing problems.
• Support and Training: Vendors who provide ongoing help and training can make AI adoption easier and more lasting.

Choosing AI designed for healthcare workflows helps more people use it successfully and leads to better ROI by making work faster and reducing mistakes or rework.

AI and Workflow Automation in Healthcare

Automation is key for the big AI changes planned for healthcare offices. The best AI tools make workflows simpler, cut down on manual tasks, and let staff focus more on caring for patients.

In the front office, AI phone systems can handle many calls well. These systems can check patient identity, share appointment times, answer insurance questions, and gather basic patient info before visits. Simbo AI is one company that shows how AI can manage front-office phone work. Their technology provides personal call handling, shortens wait times, and fixes errors in routing calls.

Apart from phone work, AI helps other medical office tasks:

• Clinical Documentation: AI scribes write and summarize patient visit details. This speeds documentation and makes it more accurate. These systems connect with EHRs to keep patient records updated for billing and care.
• Coding and Billing Automation: AI tools read clinical notes to assign billing codes or find missing info. This cuts down on claim denials and helps money come in faster.
• Patient Triage and Intake: AI chatbots or voice assistants ask patients about symptoms and history before appointments, making care smoother and patients happier.
• Task Management: Agentic AI can track work progress, send reminders, and raise issues on its own, freeing staff from constant follow-up.

Automation also helps with following rules. AI can spot privacy risks, track consent forms, and enforce documentation standards.

Adding AI workflow automation saves money by lowering admin work, cutting mistakes, and helping patients stay engaged. Healthcare managers should invest in automation plus domain-specific AI to keep up with more patients and new rules.

Closing Thoughts on the Future of Healthcare AI in U.S. Medical Practices

The trends of agentic automation, more AI talent shortages, and focusing on AI customized for healthcare have big effects on medical providers in the U.S. Practice managers and IT leaders should plan well for these trends.

Agentic AI can automate tough tasks with less human oversight but also changes workflows and jobs. The lack of AI experts means investments in training staff and working with vendors are needed to implement AI responsibly. Most importantly, picking AI tools that fit healthcare workflows and show clear benefits is key, rather than choosing based on cost alone.

As more healthcare providers use AI automation and manage the challenges, they will improve efficiency, reduce paperwork for clinicians, and make patient care better. For those focusing on front-office improvements, companies like Simbo AI offer helpful solutions for telephone interactions with AI—systems designed for the needs of U.S. healthcare.

Healthcare AI in the United States is growing fast and will keep doing so in 2024 and beyond. Recognizing and preparing for these changes will help providers use AI well while keeping patient care and privacy at the center.