The 2025 State of AI in Healthcare report by Menlo Ventures highlights that the sector now allocates more than $1 billion yearly toward AI implementation—a significant uptick for an industry historically slow to adopt technological change. Driving this acceleration is the emergence of Agentic AI, systems designed to independently reason, plan, and execute tasks without human intervention.
Agentic AI fundamentally changes what is possible, even in an industry as highly regulated as healthcare. It introduces capabilities that go well beyond prior generations of tools. Instead of prompting users to do something, agentic AI actually does it — and not just in a siloed application but across entire workflows.
Transforming Healthcare Workflows
This matters because healthcare processes aren’t linear. A single patient encounter spans intake, documentation, diagnostics, billing, and follow-up, each requiring distinct systems. Agentic AI streamlines these fragmented steps into a cohesive patient journey.
This creates a more cohesive, less error-prone experience. In short, impact becomes meaningful. Agentic AI connects these previously disparate pieces, in part, because it understands context. Based on its contextual understanding of each function, agentic AI can determine whether it should act, moving users through the workflow, or pause to defer to human judgment.
Importantly, the agentic AI opportunity does not lie with a single vendor or solution. It lies in the infrastructure, the orchestration of all of the individual pieces in concert with one another. Open, interoperable standards can enable this type of innovation to flourish across the entire healthcare ecosystem.
That’s where emerging open frameworks such as the model context protocol (MCP) and similar interoperability standards come into play. MCP provides a method for AI systems to connect external tools and data sources. McKinsey’s healthcare AI analysis notes, “Open architectures, such as MCP, are allowing new AI agents to directly access functional data across care organizations.”
MCP and Emerging Standards
Frameworks like MCP are helping change the historical barriers to innovation. In practice, approaches like MCP can help simplify the highly complex integration challenge of healthcare workflows.
Rather than custom integrations, developers use MCP to let AI systems access records, check drug interactions, schedule appointments, or process claims. In just a year, MCP evolved from an open-source project to an industry-standard framework.
MCP grew from roughly 100,000 server downloads when it launched in November 2024 to over 8 million by mid-2025, with more than 5,800 MCP servers now available. Then last December, MCP was donated to the newly formed Agentic AI Foundation under the Linux Foundation, co-founded by Anthropic, OpenAI, and Block, ensuring vendor-neutral governance and long-term stability.
With the foundation in place, it is now possible to completely reimagine the patient journey, starting with the very first patient touchpoint through post-visit actions like insurance claims and follow-up. The introduction of standardized approaches for running interactive user interfaces through MCP has enabled AI systems to present structured data, dashboards and decision workflows within the context of care delivery.
Through these advances, AI agents are becoming a routine part of daily practice, and clinicians and administrators are no longer forced to deal with multiple layers of applications. The human element remains central, as the role of human judgment remains vital in the patient care process, with agentic AI supporting healthcare providers by alleviating their cognitive and administrative burdens.
Healthcare systems, EHR vendors, and care delivery organizations must consider whether they have the faith to invest in another technology for a shot at real transformation. Industry analysts predict that agentic AI in healthcare will grow 40-45% annually, and the potential to exceed $5 billion within the next five years is possible, as healthcare providers continue to spend over $1 billion annually on AI adoption, according to the 2025 State of AI in Healthcare report.
This includes visualization of patient trends or guided forms for documentation.
No amount of data analysis can replace human expertise, accountability, and empathy.
