Healthcare has never lacked innovation.
The industry has embraced electronic health records, connected medical devices, robotic surgery, advanced imaging, and now artificial intelligence. But unlike many industries, healthcare doesn’t adopt technology simply when it’s possible. It adopts technology when it can be trusted.
That’s why the conversation around AI is changing.
The question is no longer, “Can AI effectively enable clinicians?” Increasingly, the question is, “Can we trust AI enough to make it part of clinical workflows?”
That trust isn’t built through a single model or application. It’s earned across every layer of the technology stack, from the data clinicians rely on to the infrastructure protecting sensitive information and the workflows that ultimately impact patients. That’s the thinking behind Cisco Compatible Solutions for AI. By bringing together Cisco infrastructure with an expanding ecosystem of validated software partners, we’re helping healthcare organizations deploy AI with greater confidence while building trust into every layer of the solution.
Trust Begins With Better Clinical Insight
Every second, hospitals generate an enormous volume of physiological data from monitors, ventilators, infusion pumps, and other bedside devices. The challenge is bringing that data together in a way that helps clinicians access data to inform their assessment of patient status.
That’s what makes Sickbay so compelling.
Running on Cisco Unified Edge, Sickbay brings high-frequency patient monitoring data from a wide range of bedside devices into a single view. Instead of clinicians jumping between multiple systems, they get one dashboard that helps them see the full picture, with proactive alerts that can streamline data visibility for care teams.
By bringing together continuous waveform data with clinical and electronic health record (EHR) information, AI can assist in identifying patterns for clinical review. That helps reduce alarm fatigue, supports timely access to information, and gives clinicians greater confidence in the decisions they make.
Trust Depends on Protecting Sensitive Data
As AI becomes part of clinical workflows, healthcare organizations face another challenge: protecting some of the world’s most sensitive information while enabling innovation.
Healthcare has always required strong security, but AI introduces new considerations. It’s no longer just patient records that need protection. Models, prompts, inference data, and intellectual property all become part of the attack surface.
That’s where our work with Fortanix represents an important step forward.
Together, Cisco and Fortanix are helping organizations run AI workloads inside confidential computing environments, where models and sensitive data remain protected even while they’re actively processing information. Hardware-based isolation, attestation, and zero-trust principles provide organizations with greater confidence that AI can operate on sensitive data without exposing it to unnecessary risk.
For healthcare, trust isn’t simply about keeping data encrypted. It’s about providing infrastructure designed to support the secure operation of AI where sensitive information exists. Trust Extends to Everyday Care
Some of the most meaningful aspects of clinical care and recovery can happen outside the clinical and operational environments.
Consider something as simple and important as meal delivery. A key portion of patient management and support can be ensuring that the proper dietary regimen is followed.
**Proppos **uses computer vision and AI to verify that a patient’s meal matches their dietary restrictions before it leaves the kitchen.
It’s a straightforward application, but it reflects something much bigger.
Healthcare AI isn’t only about supporting complex clinical assessments. It’s also about reducing preventable errors, improving consistency, and helping clinical teams focus on clinical tasks instead of manual verification.
Confidence is the Real Foundation for Healthcare AI
These examples may solve very different problems, but they all point to the same conclusion.
Healthcare organizations won’t measure the success of AI by the number of models they deploy. They’ll measure it by the confidence those solutions create for clinicians, IT leaders, and ultimately, patients.
That confidence depends on an ecosystem where trusted infrastructure, secure AI, and validated applications work together.
That’s why we’ve been investing in Cisco Compatible Solutions for AI. By combining a full stack of Cisco infrastructure, including compute solutions powered by Intel and others, with an expanding ecosystem of independent software vendors, we’re helping healthcare organizations deploy AI solutions that have been tested to work together; building great confidence, trust, and simplicity into every deployment.
The future of healthcare AI will be defined by thousands of trusted decisions made every day, supported by technology designed to assist clinicians, healthcare organizations, and patients.
To learn more about how Cisco Compatible Solutions for AI brings together validated partner solutions with Cisco infrastructure to accelerate AI deployment, visit the Cisco Compatible Solutions for AI page.