Artificial intelligence is rapidly transforming hospital operating rooms and administrative processes, becoming essential for both clinical and financial success. As hospitals increasingly integrate automation and generative AI into their operations, many forward-thinking leaders are looking ahead to the next frontier: AI agents.
"AI agents hold transformative potential to accelerate the evolution of healthcare by augmenting decision-making, personalizing care and automating repetitive tasks," said Biju Samkutty, COO of international and enterprise automation at Mayo Clinic in Rochester, Minn. "These agents can analyze vast amounts of patient data, including medical histories, imaging and genetic profiles, to provide clinicians with real-time, evidence-based insights. This allows healthcare providers to make faster, more accurate diagnoses and tailor treatments to the unique needs of each patient."
By integrating AI agents within EHRs, health systems can detect early disease warnings, recommend treatments, enhance precision medicine, and predict patient outcomes.
"By enhancing the speed and precision of medical decisions, AI agents empower clinicians to focus more on delivering compassionate, human-centered care," said Mr. Samkutty. "Beyond clinical settings, AI agents can optimize healthcare operations, improving efficiency and accessibility."
AI agents can streamline administrative tasks such as scheduling, billing, and resource allocation. They can also serve as virtual assistants, guiding patients through appointment scheduling and engagement. Additionally, AI agents can strengthen public health initiatives by analyzing population health data to identify trends, predict outbreaks, and inform policy decisions.
"As healthcare systems strive to balance quality, cost and access, AI agents serve as powerful tools to drive innovation, foster equity and reimagine what's possible in delivering care," Mr. Samkutty added.
Shekar Ramanathan, executive director of digital transformation at Atlantic Health System in Morristown, N.J., views both generative AI and agentic AI as game-changers in shifting healthcare from reactive to proactive care.
"For some years now, we've collected mountains of data in EHRs and data lakes but struggled to translate those insights into meaningful impact. Too often, it's added more burden to clinicians instead of relieving it," he said. "These newer forms of AI go beyond basic automation. Generative AI can interpret and synthesize unstructured clinical notes in real time, streamlining documentation and surfacing critical insights, while agentic AI can automate entire processes, such as prior authorizations or remote patient monitoring, so clinicians can focus on direct patient care."
To successfully implement AI agents, Mr. Ramanathan recommends starting with small projects and focusing on the right problems. This approach not only helps hospitals integrate advanced AI smoothly but also supports clinicians and alleviates burnout.
"Organizations that embrace these technologies, foster AI literacy and implement robust governance frameworks will not only gain a competitive advantage but also elevate their ability to serve communities effectively in an increasingly AI-driven landscape," said Sunil Dadlani, executive vice president and chief information and digital transformation officer and chief cybersecurity officer at Atlantic Health System.
Several health systems have already begun piloting AI agents with promising results. AtlantiCare in Atlantic City, N.J., became the inaugural partner for Oracle’s AI agent, Oracle Clinical Digital Assistant, which was designed to reduce administrative burdens through ambient note generation. Among the 50 providers given access to the technology, AtlantiCare reported an 80% adoption rate.
Those who used the AI agent saw a 42% reduction in documentation time, saving approximately 66 minutes per day. AtlantiCare CIO Jordan Rauch told Becker’s assistant editor Naomi Diaz in December that the health system had planned a six-wave rollout for its 800 providers.
Dennis Chornesky, chief AI advisor at UC Davis Health, is also closely monitoring the potential of AI agents in healthcare. While they have the potential to drive efficiency, he noted, they also pose risks, including AI-to-AI interactions and workforce displacement.
"It raises questions about how future workers will gain experience and how we prepare them to work effectively with AI," he said in an interview with Becker’s assistant editor Giles Bruce.
The introduction of large language models into AI agents has given them more autonomy and decision-making capabilities, but many healthcare leaders remain cautious about widespread adoption.
"Early opportunities may lie in coding, summarization, and patient-provider communication," Mr. Chornesky said. "For instance, AI agents could facilitate patient interactions, automate coding, and improve care coordination. Multimodal capabilities will likely drive adoption, but industry discussions on practical applications are still evolving."