Corporate Memory Loss: How the Global Memory Shortage Is Reshaping Device Planning 

What’s driving the memory shortage

To navigate this shortage, it helps to understand what’s changed. The issue isn’t just higher demand, but a structural shift in how memory is produced and consumed.

1. AI is absorbing memory capacity
   The AI boom has led to a shortage of PC memory, as AI servers are huge consumers of memory, requiring significantly more DRAM and NAND per system than typical endpoints or even traditional servers.
   
   Consequently, global capacity is increasingly pulled into AI data centers. Manufacturers are shifting their limited production lines toward High Bandwidth Memory (HBM), which is essential for AI accelerators. The critical issue here is yield: HBM consumes much more wafer capacity than standard DDR5 to produce the same gigabyte volume. Every wafer dedicated to HBM is a wafer not producing standard PC or server memory, directly increasing scarcity for general IT hardware.
   
   AI companies are investing billions of dollars to rapidly build data centers around the world, pulling enormous amounts of memory capacity into AI infrastructure. This scale and speed of investment signal that demand for memory is not a temporary spike, but a long-term reallocation of supply.
   
   The reason is structural. AI has changed the nature of memory demand itself: training and inference workloads require large, persistent memory footprints, extremely high bandwidth, and tight proximity to compute. These requirements can’t be dialed back without breaking performance, ensuring sustained pressure on the global memory supply chain.
2. Supply can’t scale fast enough
   While demand skyrockets, supply remains relatively inelastic. Current supply growth projections for DRAM and NAND are tracking below historical norms. Building new fabrication plants takes years and billions of dollars; manufacturers cannot simply “turn up the dial” on production overnight.
   
   We are seeing tight inventories combined with a limited ability to scale quickly. There is also significant concentration risk, as a very small number of manufacturers control the vast majority of global DRAM output. When these few players pivot to AI, the entire downstream market feels the squeeze.

The ripple effects across the business

When memory availability tightens, its impact is felt across devices, procurement workflows, and budgets.

Employee devices

The most immediate impact will show up across the device fleet. As memory availability tightens, organizations may be forced to compromise on standard configurations—either delaying refreshes or stepping down performance tiers to stay within budget.

That disruption compounds over time. When new devices are too expensive or hard to source, teams rely more heavily on break/fix support, extended warranties, and redeploying older assets. Maintaining consistent memory tiers across the fleet becomes harder, which can increase support complexity and create uneven user experiences.

Procurement

For procurement teams, the challenge isn’t just higher prices—it’s reduced predictability. Lead times can shift quickly, preferred SKUs may disappear, and approved configurations may require last-minute substitutions.

The mindset has to shift from “buy now or wait for a better price” to “what’s essential, and how do we secure it before it’s unavailable?” In a constrained market, strong procurement strategy means building flexibility into sourcing plans, standardizing where possible, and aligning early with suppliers to reduce surprises.

Budgets and forecasting

For finance leaders, volatility becomes the headline. Significant price swings can occur between the time hardware is quoted and when it actually ships, making budgeting and forecasting far less reliable.

This forces organizations to rethink how they plan refresh cycles and allocate funds—especially when memory-heavy configurations are no longer priced (or available) the way they were in prior years. The result is more frequent budget adjustments, tighter governance, and increased pressure to prioritize only the most business-critical upgrades.

How to navigate ongoing memory constraints

While business leaders can’t fix the global supply chain, they can take steps to protect their organizations from its most disruptive effects.

1. Build Resilience into Device Planning:
   Regularly assess device-level memory and storage inventory and forecast demand for memory-intensive workloads. Plan ahead for refresh cycles, OS upgrades, and AI-ready devices to reduce exposure to supply disruptions that can delay deployments or degrade performance.
   
   Shift procurement earlier for critical roles and projects. Segment users by workload so higher-memory configurations are reserved for business-critical functions, even if standard users must temporarily operate with constrained specs.
   
   Maintain a targeted buffer stock for high-failure, high-urgency components. Concentrate this investment on essential services and peak deployment periods rather than overstocking broadly, which can unnecessarily tie up capital.
   
   Create a shared operational view between IT and Finance that aligns refresh timelines, supply risks, and budget triggers. Formalize this alignment with a decision runbook that defines what to accelerate, delay, or standardize when memory supply falls below agreed thresholds.
2. Plan Ahead Using Data-Driven Forecasting:
   Use device-level monitoring and AI-driven analytics to anticipate memory demand and hardware risk before they impact productivity. By analyzing utilization trends, performance degradation, failure rates, and upcoming workload changes, organizations can forecast when higher-memory configurations will be required and adjust refresh and procurement timelines accordingly.
   
   Extend these insights beyond the endpoint by factoring in supplier lead times, historical shortages, and pricing volatility to identify supply-risk windows early. Share predictive signals across IT, Procurement, and Finance, and tie them to predefined decision thresholds—enabling faster, more disciplined decisions on when to buy early, reallocate inventory, or defer non-critical initiatives.
3. Simplify to Reduce Supply Risk
   Complexity is the enemy of supply chain resilience. Every additional device model, memory tier, or configuration multiplies exposure when supply tightens. Reducing the number of approved memory configurations across the device estate lowers the risk of disruption and makes shortages easier to absorb.
   
   Standardize wherever possible and pre-approve acceptable alternatives in advance. When memory constraints emerge, procurement teams should be empowered to substitute compatible configurations without triggering lengthy revalidation cycles. This balance of standardization and flexibility allows organizations to maintain deployment velocity and protect critical operations—even when preferred components are unavailable.

How MCPC Can Help

Navigating a constrained market requires more than ordering hardware earlier—it requires a unified approach to device lifecycle management. MCPC® helps organizations plan, reserve, store, deploy, and retire devices through a single, coordinated lifecycle, reducing exposure to sudden price spikes and unpredictable lead times.

Across the device estate, MCPC helps optimize refresh and lifecycle governance to reduce reliance on scarce high-memory configurations and safely extend device life across mixed-OEM environments. Integrated IT asset management and recovery services further free up budget, reduce waste, and reinvest value from end-of-life devices—helping organizations remain resilient even during prolonged supply constraints.