ViVE 2026 in Los Angeles brought together healthcare IT leaders from across the country — and what stood out most wasn’t hype, it was reality. Conversations on the showroom floor revealed that healthcare organizations are wrestling with several core infrastructure, performance, and data challenges that threaten clinical outcomes, cost efficiency, and innovation velocity.

  1. Data Volume Is Exploding — and It’s Creating Real Workload Headaches

One theme came up in nearly every conversation: healthcare data isn’t just growing — it’s accelerating faster than most systems can handle.

Industry research suggests that healthcare organizations generate a significant share of the world’s data, and the rate of growth is staggering. For example:

  • Healthcare systems produce roughly 30% of the world’s data volume, driven by EHRs, imaging, genomics, and medical devices.
  • Estimates show that overall medical and health data may double every ~73 days, reflecting how rapidly information accumulates in modern care delivery environments.
  • According to recent data projections, global healthcare data volumes are expected to grow into the hundreds of exabytes in the coming years.

This explosion isn’t academic. When performance can’t keep up with volume — especially for live clinical workloads — clinicians experience lag, frustration, and interruptions in care delivery.

  1. Predictable Clinical Performance Is Harder Than It Should Be

On the floor, IT leaders repeatedly described battles to keep core systems responsive.

EHRs and clinical systems are mission-critical — delays directly impact patient care. But as data volumes and concurrent workloads grow, performance variability creeps in, especially in cloud environments not originally designed for mixed, high-concurrency healthcare workloads.

For many teams, this leads to tactical performance compromises and short-term workarounds that ultimately slow innovation.

  1. Cloud Costs Spiral When Teams Overprovision for Safety

Another frequent topic at ViVE 2026 was cloud economics.

To protect performance, many healthcare organizations overprovision infrastructure — paying for capacity they hope they’ll never need — simply because unpredictable performance could jeopardize SLAs or clinical responsiveness.

This pattern is reflected in industry research: healthcare data growth and analytics demand are key drivers of expanding big data infrastructure investments, yet without optimized architectures, cost control remains elusive.

The result? Many organizations are left choosing between cost control or predictable performance — when what they really need is both.

  1. Analytics and ETL Can’t Keep Up With Real-Time Expectations

Analytics and data pipelines were a recurring pain point on the showroom floor.

Leaders described reporting jobs that take hours, ETL windows that interfere with production workflows, and data stacks that struggle to surface insights fast enough to support clinical and operational decision-making.

In an era where leaders expect data now, slow pipelines are increasingly untenable — especially when they impede quality improvement, operational efficiency, and AI readiness.

  1. Healthcare AI Adoption Is Real — But It Demands Safe Access to Live Data

AI was everywhere at ViVE — but the conversations were grounded in practicality, not hype.

Healthcare teams aren’t asking whether they should deploy AI; they’re asking how to do it responsibly without sacrificing performance or patient safety.

Across sessions and hallway conversations, a consistent concern emerged:

Can we safely enable AI models to consume live, production-grade clinical data without disrupting primary systems?

This challenge is central to gauging AI readiness in real environments, and it keeps coming back to infrastructure fundamentals: predictable performance, safe data access, and cost-efficient architectures.

The Common Thread

What ViVE made clear is that today’s top IT challenges in healthcare aren’t isolated problems — they’re interconnected.

Healthcare data is exploding. Cloud environments weren’t built for these mixed, concurrent workloads. Analytics expectations are rising. AI is becoming a strategic imperative. And performance and cost pressures are tightening everywhere.

But there is a missing layer.

A Better Way Forward: Meet the Cloud Acceleration Layer Healthcare Needs

At Silk, we heard these exact themes echoed by healthcare IT leaders — and we built a solution designed to address them directly.

Silk provides a cloud acceleration layer for mission-critical healthcare workloads, giving organizations the ability to:

  • Maintain predictable EHR and clinical system performance during peak demand
  • Reduce cloud overprovisioning and control infrastructure spend
  • Accelerate reporting, analytics, and ETL from hours to minutes
  • Enable AI models to safely access live production data

This isn’t theoretical — it’s built for the realities health systems are facing today.

If You Attended ViVE — Let’s Keep Talking

Whether you stopped by Silk’s booth or didn’t make it to our corner of the showroom floor, the challenges discussed at ViVE aren’t going away.

If you’re exploring how to:

  • Keep clinical systems responsive and predictable
  • Control cloud costs without compromising performance
  • Support faster analytics and data-driven decision-making
  • Enable real-time AI adoption safely and efficiently

We’d love to show you how Silk can help.

Request a demo and see how Silk becomes the cloud acceleration layer your healthcare environment has been missing.

Let's Keep Talking!

See how Silk becomes the cloud acceleration layer your healthcare environment has been missing.

Request a Demo