Insights from the healthcare sector highlight notable advancements in medical technology, particularly in relation to artificial intelligence.
Jaimon Jose, the senior director of engineering and compliance at CharmHealth, has crafted a career with over 18 years dedicated to product development in identity and security technologies, distributed systems, cloud security, and data center virtualization.
While technology has long been touted as a game changer for healthcare, its impact has often fallen short of expectations. Instead of achieving streamlined processes, the industry has seen an increase in clicks and administrative tasks. However, the landscape appears to be shifting.
The "2025 State of AI in Healthcare" report from Menlo Ventures finds that healthcare organizations are now investing more than $1 billion each year in AI technology. This figure is especially striking considering the typically cautious adoption rates of new technologies in this field. Recently, healthcare systems have transitioned from experimental projects to rapid, large-scale implementations, highlighting a new sense of urgency. A key driver behind this change is the emergence of Agentic AI, which includes autonomous systems capable of reasoning, planning, and executing tasks.
Agentic AI represents a significant leap forward, offering functionalities that extend far beyond traditional tools. Unlike older systems that merely prompt users, agentic AI actively executes tasks, streamlining workflows rather than complicating them. In healthcare, where patient interactions often involve multiple steps—such as intake, documentation, diagnostics, billing, and follow-up—agentic AI can create a more integrated experience across the entire patient journey. This integration not only enhances efficiency but also reduces errors.
One of the standout features of agentic AI is its contextual awareness. By understanding the nuances of different workflows, it can intelligently decide when to act autonomously and when to defer human input. This capability addresses a major challenge in healthcare: the often convoluted nature of patient interactions.
The potential of agentic AI does not reside within a single vendor's offering; it lies in the architecture that unifies various systems. Open and interoperable standards are essential for fostering innovation throughout the healthcare ecosystem. Emerging frameworks, such as the Model Context Protocol (MCP), play a critical role in this trend.
Historically, fragmentation within healthcare—where data is trapped in separate electronic health records, billing systems, and other databases—has been a significant barrier to progress. Frameworks like MCP facilitate connections between different data sources and tools. According to McKinsey, open architectures like MCP empower new AI agents to access functional information across various healthcare organizations. MCP acts as a catalyst, enabling streamlined integrations that improve tasks such as accessing patient data, checking for drug interactions, scheduling appointments, and managing claims.
The response from developers has been enthusiastic. The adoption of MCP has rapidly escalated, growing from approximately 100,000 downloads at its November 2024 launch to over 8 million by mid-2025, along with more than 5,800 available servers. In a notable development, MCP was donated to the newly established Agentic AI Foundation, part of the Linux Foundation, which was co-founded by notable entities like Anthropic, OpenAI, and Block. This ensures that MCP maintains vendor-neutral governance and sustainable growth.
With this robust foundation, healthcare can be reimagined, starting from the initial patient interaction through to post-visit elements like claims processing and follow-up actions. Standardized methodologies facilitated by MCP enable AI systems to present structured data, visualizations of patient trends, and dynamic forms that enhance the delivery of care.
As these technologies integrate into daily practice, they are not just additional layers of complexity but rather integral components that enhance the workflow for clinicians and administrators alike.
However, amidst these advancements, the importance of human judgment continues to be paramount. Human expertise, accountability, and empathy cannot be substituted by data processing or algorithms.
The objective of agentic AI is not to replace healthcare professionals but to support them by alleviating some of the cognitive and administrative pressures they face. This collaboration fosters a shared responsibility among technology providers, healthcare organizations, and patients. Developers are called upon to create systems that prioritize safety, transparency, and accountability, while healthcare organizations must ensure that technology augments their workflows appropriately. Ultimately, the final decisions on patient care must remain in human hands, requiring that healthcare providers assess and approve each diagnosis and treatment plan. Furthermore, patients need to actively engage by providing detailed health information, which allows AI systems to deliver more tailored and effective care.
The future of healthcare appears promising, with the convergence of agentic AI, open interoperability standards, and a strong demand for greater efficiency offering substantial opportunities for transformation. Analysts anticipate that the use of agentic AI in healthcare will experience annual growth rates of 40-45%, potentially surpassing $5 billion within five years.
If this positive trajectory continues, we may witness a reconciliation between technology and healthcare delivery, as agentic AI fulfills its promise to enhance outcomes for both clinicians and patients. The critical question for healthcare systems, EHR vendors, and care delivery organizations remains: Are they ready to embrace this transformative technology with the confidence needed to drive meaningful change?
