AI in healthcare: Why your network is the missing piece

Healthcare organizations are among the most enthusiastic adopters of digital transformation. They are embracing everything from electronic records, high-definition imaging and robotic surgery to Internet of Medical Technology (IoMT) devices — interconnected medical devices and systems that collect, transmit and analyze health data through internet connectivity.

And, more recently, GenAI and agentic AI are rapidly changing how organizations operate in healthcare and just about every other industry.

But beneath the surface of these advances lies a growing tension: the network. CEOs across the sector are waking up to a hard truth: Without a secure, high-performing network, there is no AI.

In a recent IDC webinar, Modernizing healthcare network infrastructure with AI-ready networks, I spoke alongside Kartika Prihadi, Vice President of Partner Sales at Cisco. We discussed the urgent need for healthcare organizations to modernize their network infrastructure as a prerequisite for successful AI adoption, emphasizing that reliability, performance and security are nonnegotiable in clinical environments.

We also explored how agentic AI and automation are transforming network operations from reactive to adaptive and unlocking strategic benefits such as predictive uptime, intelligent optimization and real-time threat detection.

Let’s take a closer look at these and other key topics from the webinar.

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Healthcare’s infrastructure reckoning

According to IDC research*, three-quarters of healthcare organizations now view their networks as their most critical infrastructure element, and rightly so. Years of piecemeal buildouts have led to sprawl, complexity and fragility — precisely what AI-driven operations can’t tolerate. The challenge isn’t just scale; it’s also reliability, performance and security in a 24x7 clinical environment where latency can literally mean life or death.

The message to healthcare leaders is clear: Consolidate, simplify and modernize. But this goes well beyond simply upgrading routers and switches. It’s about reimagining the very fabric of healthcare delivery by:

• Modernizing infrastructure to support AI for networking and security
• Building lossless, low-latency environments that support real-time decision-making
• Streamlining provisioning, troubleshooting and performance optimization
• Embedding observability and automation into every layer
• Making networks easier to run, scale and secure — without manual overhead

Networking for AI, and AI for networking: A reciprocal evolution

Only when healthcare organizations have laid the technological foundation for AI-ready networks can they start capitalizing on AI’s potential to deliver speed, security, resilience and reliability. But the rewards warrant the effort. With a solid network foundation, AI offers:

Reliability: Predictive uptime

AI-powered telemetry and analytics make real-time visibility into network health a reality. By identifying patterns and predicting device failures before they happen, AI enables healthcare networks to cultivate self-healing capabilities that support the continuous operation of business-critical systems.

Performance: Intelligent optimization

AI dynamically prioritizes traffic for high-impact applications — think remote robotic surgery, high-definition imaging and real-time diagnostics. Services are delivered seamlessly through optimized bandwidth and routing based on application context and urgency.

Data explosion at the edge: Managing IoMT at scale

With the surge of IoT and IoMT devices in hospitals, clinics and even patients’ homes, AI helps to route massive volumes of data to the right endpoints without delay. Timely insights and fewer bottlenecks are essential for precision care.

Security: AI as a network sensor

While AI enables predictive care and operational efficiency, it also expands the attack surface. By embedding security into AI platforms from the ground up, healthcare organizations can keep data encrypted at rest and in transit. The network sees everything — and with AI, it becomes a proactive security layer. By detecting anomalies, identifying threats like ransomware and automating remediation and containment at machine speed, AI transforms the network into a real-time defense system.

Strategic impact: Better experiences for all stakeholders

AI-enhanced networks don’t just make the IT team’s job easier. They empower clinicians, reduce operational friction and improve patient outcomes. From automated provisioning to intelligent troubleshooting, they free up technical teams to focus on innovation, not firefighting.

AI that acts: The agentic revolution begins

The next frontier of digital transformation in healthcare is agentic AI — autonomous agents that act on telemetry, context and deep domain expertise to support IT teams and elevate operational control. NTT DATA’s “AI fabric” is a prime example of agentic AI in action:

• AI client success manager: A 24x7 personal digital advisor offering instant insights, SLA updates and board-ready data
• AI licensing specialist: Navigates complex licensing data to track and optimize spending and usage
• Luna, the network AI engineer: Assists technical teams with configuration, troubleshooting and solution design

Operationalizing AI in healthcare: Steps to success

Kartika and I concluded the webinar by sharing the best practices that NTT DATA and Cisco recommend to healthcare clients as they embark on this journey.

Start with data quality: AI is only as good as the data it ingests. High-quality, representative and timely data is essential for accurate insights — whether it’s network telemetry or patient diagnostics. Poor data leads to poor decisions.

Build in automation: Modern infrastructure must be automated by design. From provisioning to troubleshooting, automation reduces friction, speeds up resolution and frees up your people for strategic tasks. But don’t go fully hands-off. Human-in-the-loop remains essential for validation and governance. Tools like Cisco’s AI Canvas enable real-time, cross-team collaboration on network decisions, blending GenAI with human oversight for smarter, faster outcomes.

Unify networking and security: In the AI era, separating network and security management is no longer viable. A converged platform delivers visibility, performance and protection across every layer — from the edge to the core. The network itself becomes a security sensor, detecting anomalies and containing threats in real time.

Partner strategically: Transformation is complex. Success depends on working with partners who bring both technical depth and expertise in the healthcare domain. Organizations like NTT DATA and Cisco help you navigate this shift with AI-native platforms, agentic AI assistants and consulting services built for Day 2 operations.

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