The top priority of healthcare organizations is clear: Deliver the best care to the most people. However, the industry is struggling to maintain levels of care — both in quantity and quality — because the ratio of those needing care and those willing to deliver it is widening. Providers can’t keep up with the growing demand.
Between an aging patient population and a growing workforce shortage, there are often more jobs to be done than people to do them. This forces healthcare professionals to further allocate their time to a growing list of administrative tasks. Combine this with fragmented data, disparate applications, paper forms, and manual tasks, and it quickly leads to mounting inefficiencies and staff burnout.
Who pays the price? Patients, members, and customers — who must endure longer wait times, inaccessible or more expensive care protocols, disconnected experiences, conflicting information, and slower time to therapy. And providers struggle, too, as they’re constantly being pulled away from their most important job of providing care and answering questions.
Healthcare Companies Need AI
Healthcare organizations must find ways to boost efficiency, and they’re turning to AI to do it. A 2024 Forrester Study indicated that more than 80% of healthcare leaders believe organizations that effectively adopt AI will be more efficient and agile. And according to Menlo Ventures’ research, 22% of healthcare organizations have already implemented domain-specific AI tools. This is a 7X increase over 2024 and 10X over 2023 — and twice the rate of the broader economy.
Until now, however, AI has taken a reactionary role, responding to rules and human prompts to complete tasks. But what if AI could act as a digital labor force, filling in the jobs that don’t have enough human workers? To ease the burden on healthcare workers and free up time for actual caregiving, AI agents would have to take autonomous actions, with human oversight, but far less human intervention than we’re accustomed to.
The Next Wave of AI is Here
Chatbots opened the door to conversational AI, simplifying common tasks and personalizing patient interactions based on predefined rules. Then, copilots upped the ante with assistant-like automation that could answer questions and generate content using natural language grounded in customer data. But none of these solutions could reason or take action independently in digital workflows across systems.
AI’s third era? Agentic AI, joining the versatility and flexibility of large language models (LLMs) with the precision of traditional programming. AI agents achieve specific goals and even consider the consequences of their actions to make smarter decisions. This means AI can now be fully autonomous, working beside humans as a digital workforce to relieve administrative burdens without compromising trust.
From jumpstarting patient recruitment to scheduling appointments, agentic AI plays a pivotal role in enhancing efficiency, reducing errors, and personalizing patient care.
Agentic AI Supports Important Healthcare Use Cases
With AI agents working alongside human teams, organizations can:
- Bring relief to a strapped workforce with intelligent assistance that works alongside humans. They can perform jobs in patient and member services, provider education, care coordination, sales and market engagement, and public health data management.
- Make smarter, faster decisions using natural language with AI agents. These agents can anticipate, plan, and reason, as well as adapt to new information, operating within predefined guardrails.
- Automate entire workflows and ensure seamless coordination and hand-off between AI agents and human employees, facilitating trusted collaboration across every department.
The Future of Agentic AI is Built on Trusted Data
The data conversation has shifted from cleaning, breaking down silos, and storage to activation and interoperability, allowing different parts of the business and AI agents to collaborate with one another. A good agentic AI solution comes with prebuilt integration to connect structured data with unstructured data, which now accounts for 90% of an enterprise’s information, according to IDC.
This shift in focus has paved the way for everyday use of AI, with healthcare leading the charge. Healthcare companies are expecting significant impact on productivity, efficiency, and outcomes. Specifically, Advocate Health, a North Carolina-based healthcare system, is expecting a 50% reduction in documentation time after implementing 40 AI use cases. And SimonMed, a large radiology group, is piloting solutions from more than 50 vendors, up from co-building only 10. It’s testing systems for intake, ambient scribing, and revenue cycle management, among others.
Healthcare leaders across all sectors are seeking opportunities to integrate AI into their daily operations. While initiating this transition can be challenging, delaying it puts competitive advantage at risk. The industry players that transform into agentic enterprises today are the trailblazers that will shape the future of healthcare.
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