Arrow Intelligent Solutions Blog

Healthcare is entering a decade of unprecedented transformation. Costs are expected to rise at roughly 8.5% annually, according to PwC¹. At the same time, care is shifting out of hospitals and into distributed environments supported by virtual delivery, automation, AI, and continuous data flows. Healthcare leaders are no longer asking how technology fits into their ecosystem; they are asking how quickly they can modernize and how deeply compute needs to move closer to where care happens.

"By 2035, healthcare will be proactive, automated, robot-enabled, and accessible wherever life happens" – PwC

Companies developing imaging solutions, care-coordination platforms, analytics tools, and diagnostic devices face new pressures. They must support richer data workloads, higher image fidelity, and AI-powered insights while reducing operational complexity. They need compute that is powerful, long-lasting, secure, and flexible enough to support the rapidly growing range of care settings from traditional radiology suites to mobile carts to in-home monitoring.

This is where HP Z Workstations, supported by Arrow’s intelligent solutions business’s engineering and lifecycle services, provide value.

The New Compute Reality in Healthcare

By 2035, PwC projects that more than $1T1 of annual spending will shift from infrastructure-heavy environments to virtual, intelligent, and distributed care models. This shift requires high-performing, reliable, and easy-to-integrate compute at the edge.

Three trends are reshaping what healthcare enterprises expect from their hardware partners:

1. Care is moving closer to the patient
From hospital-at-home programs to connected diagnostics, compute must support real-time decision-making at the point of care. This includes low-latency inferencing, 3D imaging, data acquisition, and analytics where bandwidth or uptime cannot be compromised.

2. AI workloads are expanding
AI algorithms support early risk detection, triage, image enhancement, and operational automation. AI will become a core driver of diagnosis, navigation, and workflow efficiency. This requires dependable GPU-accelerated systems and scalable architecture.

3. Infrastructure must shrink
Facilities are evolving into high-speed care nodes. In many environments, equipment must fit into carts, cabinets, mini-data-closets, or small clinical rooms. In these space-constrained environments, compute density is just as critical as performance. HP and Arrow directly address these needs with a combined foundation of long-lifecycle hardware and specialized engineering support.

Why HP Z Workstations Fit the Needs of Healthcare

HP Z Workstations have become the trusted backbone for imaging, diagnostics, clinical informatics, life sciences, and emerging AI-enabled healthcare devices. Their value is clear:

Proven platform stability
Z platforms support long, predictable lifecycles that reduce redesign and validation. This is critical for imaging systems, analytics platforms, and medical device OEMs that require consistent configurations across years of production.

Flexible deployments from cart to data closet
The Z portfolio spans small-form-factor systems, mini workstations, full-tower compute, and the Z4R 1U rack workstation. At the same time, healthcare enterprises can standardize workflows while deploying purpose-built form factors to support:

• Mobile carts
• Ultrasound and point-of-care systems
• Distributed radiology and visualization workflows
• Hybrid on-prem and cloud-connected AI systems

Enterprise-grade performance for clinical workloads
HP Z systems deliver the compute needed for 3D imaging, multimodal diagnostics, real-time rendering, and advanced analytics. With support for NVIDIA, AMD, and Intel GPUs, organizations can match the right accelerator to each workload from visualization to generative AI.

Optimized for edge inferencing
Z platforms support containerized AI workloads, local inferencing, and low-latency processing. They excel in:

• Imaging reconstruction
• Segmentation and detection models
• Real-time triage
• Video analytics in clinical settings
• Clinical decision-support applications

Security is built into every layer
Healthcare IT teams benefit from features such as HP self-healing BIOS and HP Wolf Security, which provides hardware-enforced security. These protections help safeguard sensitive clinical data and maintain endpoint trust in distributed environments.

The Role of Arrow Intelligent Solutions

Building on HP’s compute foundation, Arrow engineers, integrates, and delivers platforms designed to remove deployment friction for OEMs, ISVs, and system integrators. Arrow’s teams support the full lifecycle of healthcare solutions:

Engineering and validation
Arrow provides engineering support to help ensure each workstation performs consistently across healthcare applications. This includes optimization, testing, and configuration services that reduce variability and improve workload stability.

• Thermal and mechanical testing
• BIOS configuration and tuning
• GPU and workload optimization
• Application validation and stress testing

Integration and manufacturing
With Arrow, we deliver complete system integration so healthcare solutions arrive deployment-ready. Systems are built, tested, and packaged consistently across global facilities.

• Custom imaging and assembly
• Branding and labeling
• Cabling, racking, and full system integration
• Global manufacturing and logistics at scale

Supply chain stability
Predictable component availability is essential as care models expand beyond traditional facilities. Arrow manages long-term planning and coordination to keep healthcare platforms consistent year after year.

• Multi-year forecasting
• Inventory management
• Global fulfillment
• Lifecycle continuity

Arrow and HP: Supporting the Demands of Modern Healthcare

Healthcare is becoming more distributed, data-intensive, and AI-enabled. Rising costs, workforce challenges, and the shift toward virtual and connected care models are pushing organizations to rely on technology that can operate reliably across many clinical environments.

HP Z Workstations and Arrow’s intelligent solutions business provide the computing foundation required for this evolution. HP delivers long-life, high-performance platforms that support imaging, diagnostics, analytics, and AI at the point of care.

Arrow contributes engineering expertise, global integration, and lifecycle support that help healthcare organizations deploy and maintain these platforms consistently at scale.

Together, HP and Arrow give healthcare enterprises confidence that their compute infrastructure will remain stable, responsive, and ready to grow with emerging demands.

Healthcare organizations face pressure to modernize, secure data, and meet compliance, all while managing tight budgets and high patient volumes. Fast-approaching end-of-life (EOL) on infrastructure disrupts systems, requires requalification of workflows, and leads to unexpected costs.

Executives are left asking: How do we invest in technology that keeps pace with innovation, compliance, and cost?

The Problem

Most commercial technology refreshes every 18 to 24 months. Frequent technology refresh creates chaos in healthcare. New devices or drivers mean revalidation, regulatory review, and retraining. For hospitals using imaging, lab, or monitoring devices, these disruptions impact operational efficiency and continuity, and patient care.

It’s not just an IT inconvenience; it’s a business risk. When suppliers unexpectedly change components or firmware, healthcare teams must rebuild compliance documentation, recertify interfaces, and retest software that previously worked.

The financial impact of short lifecycle infrastructure is hidden in operational friction:

• Costly recertification and revalidation
• Procurement delays caused by supply gaps
• Extended downtime in critical clinical systems
• Compromised compliance reporting

The Insight

Long-life infrastructure gives organizations control. Hardware consistency for 5 to 10 years means stable validation cycles, budgets, and innovation plans. With long-lifecycle systems like HP Z platforms, executives can:

• Maintain validated hardware configurations over time
• Simplify compliance management with consistent documentation
• Plan technology refreshes around strategic needs instead of vendor timelines
• Extend depreciation across 5 to 10 years to reduce total cost of ownership

A predictable platform isn’t just reliable; it’s also predictable. It’s financially responsible and operationally resilient.

What Stability Looks Like in Practice

Imagine a hospital that deploys HP OEM compute systems across its imaging network. Each workstation maintains the same validated configuration for years, supported by HP’s proactive end-of-life reporting and long-term parts availability.

When new applications are added, IT teams integrate them confidently, knowing the platform stays compliant and stable. Consistency across sites and departments boosts efficiency, reduces risk, and supports patient care.

The Business Outcome Executives who prioritize lifecycle stability achieve measurable results:

• Lower operational risk through predictable technology behavior
• Stronger financial planning with fewer surprise refresh costs
• Faster adoption of innovation because systems stay validated longer
• Greater confidence with regulators and auditors through continuity of compliance

This is the foundation of sustainable digital transformation in healthcare.

The Decision

Choosing long-lifecycle infrastructure is a strategic investment in reliability, compliance, and agility. It protects capital, preserves certifications, and keeps focus on better outcomes for patients and providers. When healthcare builds on platforms designed to last, organizations stop reacting to hardware change and start driving strategic progress. Learn why over 70% of the world's largest medical device OEMs work with Arrow to advance their medical innovations*

*Based on the MedTech Big 100

The memory market has moved into a tighter, more managed environment. This is not a typical cycle in which pricing falls during excess supply and rises when demand returns. The current phase is being shaped by two durable forces: suppliers are actively steering capacity toward higher-value products, and demand is being reallocated toward AI infrastructure that is more memory-intensive than prior compute generations.

This dynamic was underscored at CES, where NVIDIA CEO Jensen Huang¹ emphasized that the limiting factor for AI systems is no longer raw compute but memory. As models scale, he highlighted that memory bandwidth, memory capacity, and data movement are becoming fundamental constraints on performance and efficiency.

[caption id="attachment_13247" align="alignnone" width="1430"] Figure: AI data interacts with a variety of storage and memory devices (source: Seagate)[/caption]

In practical terms, more memory is required to be closer to compute, and it must move faster and at scale. That reality places sustained pressure on the memory ecosystem well beyond accelerators alone. When those resources become critical to uptime and schedule, purchasing behavior changes. Customers commit earlier, hold more buffer inventory for hard-to-replace parts, and prioritize continuity over spot optimization. 

Why is capacity constrained?

Capacity constraints today are less about a single chokepoint and more about product mix and transition timing.

For DRAM, suppliers are concentrating investment and output on products tied to long-term growth and profitability.

Two areas stand out: DDR5 for modern platforms and HBM for accelerators.

As capacity and engineering focus shift toward these segments, legacy DRAM receives less support, especially in DDR4. Even where DDR4 demand remains meaningful due to the installed base and longer qualification cycles, memory suppliers have clear incentives to reduce exposure to low-margin legacy parts and move the market forward. As a result, DDR4 is increasingly characterized by constrained availability, less pricing elasticity, and a higher risk of allocation.

For NAND, the conversation is more nuanced.

NAND wafer supply matters, but finished product availability often depends on additional components and manufacturing steps. Enterprise SSDs, for example, rely on controllers, substrates, PCBs, power loss protection components, and, in many cases, drive DRAM. If any of these elements become constrained, finished drive output tightens even if NAND supply is improving. Buyers sometimes underestimate this, assuming that a better NAND supply picture automatically translates to abundant SSD availability. Constraints can migrate across the bill of materials.

What memory makers are doing

Rather than expanding output aggressively at the first sign of recovery, memory suppliers are focusing on profitability, product mix, and long-term positioning. In practical terms, that means:

• Prioritizing higher value DRAM segments, particularly DDR5 and HBM.
• Exiting or de-emphasizing lower margin businesses to focus on higher value, AI-driven memory products.
• Using allocation frameworks that favor customers with credible forecasts and committed demand.
• Managing capital spending to avoid creating the kind of oversupply that would rapidly reset pricing.

For customers, this matters because it changes the rules of engagement. In a more managed market, availability can depend as much on planning and commitments as it does on willingness to pay in the moment.

Inventory and why it is not a reliable shock absorber

Inventory conditions across the ecosystem have shifted. In recent years, many channels built inventory buffers during periods of uncertainty. As the market tightened and product transitions accelerated, those buffers have been drawn down. What remains is often unevenly distributed.

Some inventory is held by large OEMs, hyperscalers, or major module houses. Some are committed to specific platforms or customers. Some do not match current qualification requirements. The implication is that inventory can exist in the system while buyers still experience scarcity for the parts that matter to their builds.

[caption id="attachment_13248" align="alignnone" width="914"] Figure: DRAM Inventory Levels (source: Morgan Stanley Research and TrendForce, Jan 2026)[/caption]

This is particularly relevant for DDR4-dependent programs and for qualified enterprise storage configurations. Where substitution is difficult, buyers tend to secure coverage earlier and hold it longer. That behavior reduces the availability of flexible supply and amplifies short-term disruptions.

Implications for pricing and availability

The market implication is straightforward: the greatest pricing pressure and availability risk sit at the intersection of two factors, constrained supply and limited alternative options.

For DRAM, legacy products are exposed because supply is being deprioritized while demand persists. DDR4 is the clearest example. As production attention shifts to DDR5 and HBM, DDR4 tightness can emerge quickly, and pricing can move sharply because buyers have fewer near-term alternatives. In contrast, DDR5 continues to benefit from strong platform momentum, but pricing is still influenced by capacity being pulled toward HBM and by the pace of server buildouts.

For NAND and SSDs, availability and pricing are increasingly shaped by enterprise demand and by the full component stack behind finished drives. When enterprise storage demand is strong, upstream NAND pricing can firm, but the more immediate pain points for many buyers are finished drive allocation, extended lead times, and the need to secure the right configuration rather than any SSD at any price.

Overall, the market is signaling a period when volatility is more likely to show up as allocation events and step changes in quotes, not just gradual movement. Buyers should expect continued tightness in parts tied to AI infrastructure and in legacy products that suppliers are intentionally steering away from.

[caption id="attachment_13249" align="alignnone" width="960"] Figure: Memory and Storage Pricing Trends and Forecast for Q1’26 and Q2’26. Source: Morgan Stanley Research and TrendForce)[/caption]

Where to go from here: Arrow’s recommendations

The most effective response is to treat memory and storage as schedule-critical inputs, not as late-stage commodities. The following actions consistently reduce risk:

Build a DDR4 continuity plan.
If you have platforms that require DDR4, define the coverage horizon now. Identify last-time-buy requirements, validate alternate sources where feasible, and avoid waiting until pricing dislocates or allocations tighten further. Where possible, align future designs and refresh cycles to DDR5 adoption so you are not anchored to a shrinking supply base.

Use forecasting as a supply tool.
In a managed market, credible demand visibility improves allocation outcomes. Share forecasts early, refresh them routinely, and align them to production schedules. Buyers who provide clean visibility tend to see better continuity than those who rely on ad hoc ordering.

Consider longer-term commitments for constrained items.
For parts that are hard to substitute or that sit in the most constrained segments, longer term agreements can stabilize supply and reduce surprises in price. The right structure depends on your risk tolerance and demand certainty, but the broader principle holds: committed demand is prioritized.

De-risk enterprise SSD programs by validating the full stack.
Treat SSD availability as a system outcome, not a NAND outcome. Validate controller availability, substrates, power loss protection components, and on-drive DRAM assumptions. Confirm that alternates are qualified or qualify them proactively. This is often where programs slip when teams focus only on NAND supply.

Segment your purchasing strategy by criticality.
Not every part deserves the same approach. For highly constrained or hard-to-replace parts, prioritize continuity and security of allocation. For more flexible items, staged buying tied to confirmed demand can manage working capital while reducing exposure to sudden price moves.

Budget with scenarios and triggers.
Instead of a single price assumption, build a range and define triggers for action. Pre-approve alternates and escalation paths so that procurement does not stall when quotes change quickly.

Closing perspective

This market is being reshaped by structural demand and disciplined supply behavior. The organizations that navigate it best will be those that plan earlier, qualify intelligently, and align procurement strategy to technology transitions.

Connect with our team today to learn how Arrow’s Intelligent Solutions can support your organization by translating market signals into practical allocation plans, qualification strategies, and sourcing structures that help protect schedules while managing cost and risk.