Blog Will AI Spend Break IT Procurement? Mar 26, 2026AI, Audit Defense, Contract Negotiation, Price Benchmarking, SaaS Management Share This Article Subscribe For Updates Uncover negotiation leverage and unlock savings across your IT spend. Most enterprise technology categories eventually get tamed. IT procurement teams learn the pricing models, build the benchmarks, and negotiate contracts that protect the business. AI is proving stubbornly resistant to that process, and the reason goes deeper than market immaturity. IT Procurement Was Built for a Different Kind of Cost Enterprise IT has always involved a mix of spending types. Per-seat SaaS licenses are predictable by design. Infrastructure contracts are negotiated upfront. Usage-based services like cloud compute can spike, but they scale in response to workloads that procurement teams can model and monitor. In every case, there is a mechanism (contractual or operational) that connects cost to something finance can plan around. That mechanism breaks down with AI. The spend is consumption-driven, but unlike cloud infrastructure, it is not tied to a workload that procurement can define or forecast in advance. It is tied to user behavior: how often people invoke AI tools, how complex their queries are, and so on. None of that is visible before it happens, and very little of it is controllable after a contract is signed. The Contract Gives You a Price, Not a Ceiling When IT procurement negotiates an AI agreement, the deliverable is typically a rate: cost per token or credit, API call, action, interaction, data volume, or a committed spend tier with overage terms. Spend caps are not clearly defined compared to a SaaS agreement, where the number of seats sets a practical ceiling on cost. In an AI consumption agreement, the accountability for managing consumption lives entirely on the buyer’s side. For IT procurement teams accustomed to using contract structure as a cost control mechanism, this is a significant shift in operating model. Negotiating favorable unit pricing is still valuable, but it addresses only one dimension of the problem. Why the Standard ROI Model Doesn’t Hold AI investments are commonly justified through headcount reduction or productivity gains. Both are real possibilities, but the total cost picture is rarely modeled with enough precision to hold up under scrutiny. The productivity case tends to be measured at the point of AI output: tasks completed faster, content generated at scale, queries resolved without human involvement. What gets undercounted is the human layer that sits downstream of that output. AI-generated work typically requires review, validation, and correction before it can be used, and that labor cost does not disappear when AI is deployed. It shifts. Organizations that model ROI by netting AI licensing costs against eliminated roles frequently find that the math changes when oversight labor is added back in. IT procurement’s role here is to push for more rigorous TCO modeling before contracts are signed, not after. That means requiring business units to account for human oversight costs alongside platform costs in any AI business case that comes through for approval. The Benchmarking Problem One of IT procurement’s most powerful tools is price benchmarking – although it’s not the only one. Knowing what peers are paying for similar technology creates negotiating leverage and establishes whether a vendor’s pricing is defensible. AI is difficult to benchmark in the traditional sense for several reasons. Pricing models vary significantly across vendors, and consumption-based pricing makes apples-to-apples comparisons difficult. Also, AI contracts are relatively new. Organizations that are used to benchmarking pricing based on the firsthand experience of their procurement teams don’t have a lot of historical data to draw from. That does not mean price benchmarking is impossible. But it does mean procurement teams need to invest in acquiring both internal and external AI-specific pricing intelligence rather than assuming existing SaaS benchmarks will translate. The organizations that are furthest ahead on this have started tracking consumption patterns across their own deployments and are using outside intelligence to determine peer-based benchmarks. What Procurement Needs to Get Right in AI Contracts The good news is that procurement has more leverage than it thinks, particularly at initial contracting and at renewal. A few areas where contract terms can provide meaningful protection: Spend guardrails and commitment structures. Committed spend tiers can offer unit cost savings, but the terms around overages and ramp schedules should be negotiated carefully. Soft caps and escalation clauses that trigger review rather than automatic billing are achievable with the right vendors. Usage reporting and audit rights. Contracts should require vendors to provide granular consumption data at a cadence that enables real-time monitoring, not just monthly invoicing summaries. Audit rights matter for validating billing accuracy as pricing models evolve. Model change and repricing protections. AI vendors update underlying models regularly, and those updates can affect both performance and cost. Procurement should negotiate protections against unilateral repricing when a vendor migrates customers to a new model version. Exit provisions. Data portability and exit terms are especially important in AI agreements because switching costs can be high if proprietary data or fine-tuning work is involved. Getting these terms locked in at signature is far easier than negotiating them at renewal. None of these terms eliminate the fundamental unpredictability of AI consumption costs. But they shift more of the risk back toward the vendor and give procurement teams more visibility and control. The Broader Shift in IT Procurement’s Role AI is not the first technology category to arrive with immature pricing and governance structures. Cloud computing went through a similar period, and IT procurement teams that built cloud cost management capabilities early ended up with a durable advantage in managing one of their largest and fastest growing spend categories. The organizations that treat AI procurement as a specialized discipline now, rather than an extension of existing software management practices, are building the same kind of advantage. That means developing AI-specific benchmarks, building consumption monitoring into deployment requirements, pushing for TCO rigor in business cases, and using contract terms to establish the controls that the technology itself does not provide. Share This Article Subscribe For Updates Uncover negotiation leverage and unlock savings across your IT spend.
Blog What IBM’s Acquisition History May Tell Us About the Future of Confluent Mar 18, 2026IBM Share This Article Subscribe For Updates Uncover negotiation leverage and unlock savings across your IT spend. When a major software vendor acquires a company, most of the early conversation focuses on technology. But for enterprise buyers, the more important question often comes later: What will happen to pricing, licensing, and contracts once the new owner takes control? With IBM’s acquisition of Confluent now complete, many organizations that rely on Confluent’s streaming platform are starting to think about that question. IBM has been highly active on the acquisition front in recent years, and its integration strategy tends to follow recognizable patterns. For procurement and IT sourcing teams, those patterns can offer useful signals about what may happen after the Confluent deal closes. A Growing Software Portfolio IBM has completed roughly 25 acquisitions over the past six years as it expands its software portfolio across automation, infrastructure, and data platforms. Recent acquisitions include companies such as Apptio, HashiCorp, Instana, DataStax, and multiple products acquired from Software AG. Each acquisition broadens IBM’s ability to position itself as a full-stack enterprise software provider. Over time, those acquired products rarely remain standalone businesses. They are gradually pulled into IBM’s commercial framework and product portfolio. For customers, that transition often comes with meaningful changes. The Typical Post-Acquisition Integration Playbook Across multiple IBM proposals we’ve reviewed over the years, a consistent pattern tends to emerge once an acquisition moves from announcement to integration. In many cases, IBM begins aligning the acquired products with its existing commercial structures and product catalog. That process often includes several steps. Contract migration into IBM Passport Advantage. Legacy agreements are often moved into IBM’s centralized licensing framework, particularly when existing contracts are not aligned with IBM’s standard commercial model. Product rebranding and new part numbers. Acquired products are typically incorporated into the IBM catalog with new names and IBM part numbers. Licensing model changes. Licensing metrics frequently shift toward IBM’s preferred licensing structures, replacing the original model used by the acquired vendor. New product versions. IBM often releases a new version of the software under the IBM brand while gradually phasing out older versions. Upgrade incentives. Customers may be encouraged to migrate to the new version as part of contract modernization or renewal discussions. Deployment restrictions. Some deployments may be limited to environments owned and operated by the licensee, which can affect hybrid or hosted environments. Pricing resets. As products move into IBM’s commercial framework, pricing structures are often recalibrated. A Recent Example: webMethods A recent client scenario involving webMethods illustrates how these dynamics can play out in practice. IBM acquired webMethods in 2024 as part of its purchase of integration technologies from Software AG. After the acquisition, the platform was reintroduced as IBM WebMethods Hybrid Integration. IBM positioned the transition as an opportunity to modernize contracts and align pricing with the current value of the platform. Customers were told the move to IBM contracts would not necessarily require an immediate reimplementation and could be handled as a regular upgrade. However, the commercial impact was substantial. Under the client’s original Software AG agreement, annual maintenance for webMethods was about $1 million, resulting in a three-year cost of nearly $3 million with unlimited core deployment. When IBM introduced its modernization proposal tied to a new platform version, the economics shifted significantly. The new version of IBM WebMethods Hybrid Integration carried a list price of $100+ million, and IBM offered two paths forward: Option 1: A perpetual licensing option that would bring the three-year cost to over 175% higher than the previous agreement Option 2: A subscription model that resulted in nearly a 100% cost percent increase IBM framed these options as part of a modernization path. For the customer, however, the proposal set a very different pricing starting point going forward. How Acquired Software Shows Up in Enterprise Agreements Another pattern frequently appears during IBM Enterprise License Agreement (ELA) renewals: Acquired software often becomes integrated into broader IBM proposals. Sometimes the products are added to existing enterprise agreements. In other cases, they appear inside expanded product catalogs bundled with other IBM technologies. From IBM’s perspective, this approach helps drive adoption of newly acquired platforms while increasing the strategic footprint of the overall software portfolio. For enterprise buyers, however, it can also increase the scale and complexity of renewal negotiations. What This Could Mean for Confluent Customers None of this guarantees exactly how IBM will integrate Confluent. But if historical patterns hold, Confluent customers may eventually see several familiar dynamics: product rebranding under the IBM portfolio, migration toward IBM commercial frameworks, licensing model adjustments, and the potential for broader bundling within IBM enterprise agreements. Most importantly, customers should expect that pricing structures could evolve as the technology becomes part of IBM’s broader software strategy. Preparing for the Transition Acquisitions often create a transition window before new commercial models fully take shape. Organizations that use Confluent may benefit from preparing early, particularly if renewals fall within a 12 to 24-month post-acquisition window. Steps procurement teams may want to consider include: Reviewing current contracts and renewal timelines to understand when IBM integration changes could affect negotiations Benchmarking pricing against recent IBM proposals involving acquired software Understanding potential licensing metric changes that could alter future cost structures Evaluating deployment models and architecture that may be affected by IBM licensing policies Planning negotiation strategy early, before new commercial frameworks are fully established By the time vendor integration strategies are fully implemented, the commercial structure is often much harder to influence. Organizations that prepare early typically enter those discussions with far more leverage. Share This Article Subscribe For Updates Uncover negotiation leverage and unlock savings across your IT spend.
Blog Microsoft 365 E7: What It Is, What’s Inside, and What Enterprise Buyers Need to Know Mar 10, 2026Microsoft Share This Article Subscribe For Updates Uncover negotiation leverage and unlock savings across your IT spend. On March 9, 2026, Microsoft officially announced Microsoft 365 E7 — its first new enterprise licensing tier since E5 launched in 2015. Hitting general availability on May 1, 2026 at $99 per user per month, E7 reflects Microsoft’s bet on how enterprise work will be organized in the age of AI agents. For IT and sourcing leaders navigating upcoming EA renewals, the timing and implications are hard to ignore. What Exactly Is Microsoft 365 E7? Think of E7 as Microsoft’s answer to a question that’s been building for three years: How do you price an enterprise suite when the “worker” might not be human? Microsoft is calling it the Frontier Worker Suite and the name is intentional. E7 is designed to serve both human employees and the AI agents that increasingly work alongside them. It bundles together components that many large organizations have been purchasing piecemeal, or not purchasing at all, into one stack. Here’s what’s included: Microsoft 365 E5 — the full enterprise productivity and security suite Microsoft 365 Copilot — the AI assistant layer across Word, Excel, PowerPoint, Outlook, and Teams Agent 365 — Microsoft’s new control plane for managing, governing, and securing AI agents across the enterprise Microsoft Entra Suite — identity governance and access management, including capabilities beyond what E5 previously covered Advanced Defender, Intune, and Purview capabilities — enhanced security, device management, and compliance tooling Priced at $99/user/month (or $90.45 without Teams), Microsoft positions E7 as less expensive than buying all of these components individually. The math largely checks out. M365 E5 alone is $57/user/month today (rising to $60 on July 1), Copilot adds $30, and Entra Suite adds $12. That’s $99 before you even count Agent 365 at $15/user/month. The New Thing Everyone Should Pay Attention To: Agent 365 The biggest net-new component in E7 is Agent 365, which goes generally available on May 1 alongside E7. This is Microsoft’s enterprise control plane for AI agents: a single, centralized location where IT and security teams can observe, govern, manage, and secure every agent operating across the organization. Why does this matter? Because agents are proliferating faster than most IT teams realize. In just two months of preview, tens of millions of agents have been registered in the Agent 365 Registry by preview customers alone. Microsoft itself runs over 500,000 internal agents and logs more than 65,000 agent-generated responses per day for its own employees. The result is enterprises are facing a real governance gap: agents being spun up by business units, running on third-party frameworks, operating with access to sensitive data — all with no centralized visibility. Agent 365 intends to close that loop. It covers agents built in Microsoft tools, ecosystem partners, and those registered via API, and it assigns each agent a unique Entra identity with conditional access policies and risk evaluation built in. Copilot Gets a Major Upgrade: Meet Copilot Cowork E7 also arrives alongside Wave 3 of Microsoft 365 Copilot, which Microsoft aims to shift from a “chat assistant” to an “action-taker.” The flagship feature is Copilot Cowork, built in partnership with Anthropic and powered by Claude. Cowork is designed for long-running, multi-step workflows. Microsoft’s example: “Prepare me for a customer meeting” prompts Cowork to build the presentation, pull financial data, email the relevant team members, and schedule prep time. All without requiring manual integration, connectors, or data movement outside the enterprise boundary. Cowork enters research preview through Microsoft’s Frontier program in March and is grounded by Work IQ — Microsoft’s intelligence layer that ingests signals from Outlook, Teams, SharePoint, and OneDrive to construct a semantic graph of how you work, who you work with, and what projects are active. The idea is that context is what separates a genuinely useful AI system from a fancy autocomplete engine. Wave 3 also brings agentic features into Word, Excel, PowerPoint, and Outlook natively. Why This Is a Big Deal for Enterprise Buyers There are a few reasons E7 represents more than a normal licensing announcement: 1. It’s the first new enterprise tier in a decade.Microsoft hasn’t introduced a new top-tier M365 plan since E5 in 2015. This alone signals strategic intent that’s noteworthy for enterprise customers. 2. It reframes what “enterprise seat licensing” means.Microsoft has been signaling for months that AI agents will need to be licensed like employees with Entra IDs, access controls, compliance scopes, and audit trails. E7 is the first commercial packaging of that vision. Organizations that wait too long to engage with this shift will face a steeper governance ramp later. 3. The timing intersects with price increases.Microsoft is raising prices across the board on July 1. E3 goes from $36 to $39/user/month (an 8% increase), and E5 from $57 to $60. For enterprises already on E5 plus standalone Copilot licenses, the E7 bundle math becomes more compelling with those increases priced in. 4. Copilot adoption has been lagging and Microsoft knows it.Just over 3% of Microsoft’s 450 million M365 business subscribers had purchased Copilot seats as of early 2026. Similarly, E5 penetration sat at roughly 12% of the installed base as recently as 2022. E7 is, in part, Microsoft’s strategy for accelerating adoption by lowering the per-component friction. Considerations and Pitfalls for Enterprise Customers E7 is compelling on the surface, but enterprise buyers should approach the renewal conversation with clear eyes. Don’t assume the bundle math works for your entire user base.E7 is priced for the fully-loaded knowledge worker. For large organizations with significant populations of frontline, task-based, or limited-use workers, paying $99/user for capabilities they’ll never touch is wasteful. Segment your population carefully before committing. Test and build a business case for E7.Most large enterprises are mid-contract on E5 agreements. Wondering if E7 should be included in your next renewal? Use your remaining E5 term to pilot Agent 365 through the Frontier program, evaluate actual Copilot utilization, and build an internal business case. Agent 365 governance isn’t fully GA on Day 1.Several Defender and Purview capabilities within Agent 365 will still be in public preview on May 1. Runtime threat protection and investigation for agents won’t reach GA until April or May depending on the capability. Enterprises with strict risk thresholds should map exactly which features are production-ready before incorporating them into security baselines. Consumption-based pricing may be coming.It’s been reported that Microsoft is exploring a hybrid user- and consumption-based pricing model for future E7 iterations. This is more akin to Azure economics than flat per-seat licensing. This is not in the initial E7 offer, but enterprises should monitor whether this surfaces in EA renewal negotiations, particularly for large agent-heavy deployments. Copilot Cowork is still in preview.Cowork (possibly the most compelling capability in the E7 story) enters only a research preview in March through the Frontier program. It is not a Day 1 GA feature. Organizations evaluating E7 primarily on Cowork’s promise should treat that capability as directional, not deliverable, at launch. A Familiar Playbook – Microsoft’s Bundling Strategy in Context Microsoft’s announcement of Microsoft 365 E7 reflects a strategy the company has used many times before: bundling newer or less-proven technologies with widely adopted platforms in order to accelerate adoption. In this case, Microsoft is combining the already popular Microsoft 365 E5 suite with emerging capabilities such as Microsoft 365 Copilot and AI agent management tools. By packaging these technologies together, Microsoft lowers the barrier for customers to begin using AI features and positions them as a natural extension of the existing productivity platform rather than optional add-ons. Historically, Microsoft has used similar bundling strategies to drive adoption of new products and expand the reach of its ecosystem. From a business standpoint, the bundle also allows Microsoft to establish a new top tier for its enterprise offerings while increasing the overall value of the platform. Rather than relying on customers to purchase AI capabilities separately, the company can incorporate them into a higher-priced enterprise tier and gradually normalize AI as part of the core workplace software stack. One implication is that many organizations may end up purchasing AI capabilities for far more users than will meaningfully use them, as enterprises often standardize on a single license tier to simplify procurement and compliance. This “all-users” licensing pattern (common in large enterprise agreements) can lead to significant overbuying in the early stages of adoption, particularly when the productivity benefits of AI tools are still uneven across roles and departments. While bundling can accelerate deployment, it also increases the likelihood that customers pay for capabilities that only a subset of users will actively utilize in the near term. The Bottom Line Microsoft 365 E7 is one of the most significant enterprise licensing events from Microsoft in a decade. It aligns Microsoft’s AI vision with licensing reality. The enterprise seat is no longer just about a human with an inbox. It’s about the human, their AI assistant, and the fleet of agents working on their behalf – all governed, secured, and observable from a single control plane. For enterprise technology leaders, a move to E7 may sound compelling. But like all things Microsoft, proceed with caution. Start by understanding exactly what you have, what it would cost to assemble E7’s components under your current agreements, and where your organization sits on AI agent adoption. That analysis will reveal a game plan that makes functional and economical sense. 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Blog Why Memory Costs Are Now Your Biggest IT Budget Problem — And What to Do About It Mar 5, 2026Hardware, Price Benchmarking Share This Article Subscribe For Updates Uncover negotiation leverage and unlock savings across your IT spend. If you built your 2026 IT hardware budget on historical pricing assumptions, there’s a good chance you’re already behind. The global memory market has undergone a structural shift that most enterprise IT and procurement teams are still absorbing. DRAM and NAND prices didn’t just tick up. They surged at levels not seen in over two decades. And unlike the cyclical corrections the industry is accustomed to, the conditions driving this increase aren’t a blip. The pressure is structural, and it’s going to be with us for a while. Here’s what’s happening, why it matters across your entire IT stack, and what organizations that are managing through it well are actually doing differently. The Numbers Are Hard to Ignore To understand the scope of this problem, start with what’s really happened to pricing over the past year: DDR5 is up 100–200% year over year — with certain configurations climbing as much as 240–300% DDR4, still widely deployed in enterprise environments, has increased 140–170% NAND wafer pricing is up approximately 250% in key segments DRAM inventory levels have contracted from 31 weeks of supply to fewer than 8 weeks entering 2026 The downstream effect is already showing up in enterprise purchasing. PC configurations are reflecting 15–20% cost increases. For organizations running large refresh programs planned on last year’s pricing models, that gap can translate into seven-figure budget variances — not because something went wrong operationally, but simply because the market moved. This Isn’t a Temporary Memory Cost Spike – Here’s Why The instinct to wait it out is understandable. Memory markets have historically been cyclical. But the structural dynamics this cycle are different from previous ones, and that distinction matters a great deal for planning purposes. AI is consuming memory at a pace the industry wasn’t built to accommodate. Hyperscalers and AI infrastructure projects are pre-committing supply years in advance. Data centers are projected to absorb up to 70% of global memory output in 2026. To put a finer point on it: OpenAI’s Stargate initiative alone is estimated to consume roughly 40% of global monthly DRAM output. That leaves considerably less elasticity for everyone else. At the same time, major manufacturers (Samsung, SK Hynix, and others) have reallocated wafer capacity toward higher-margin high-bandwidth memory (HBM) products serving AI workloads. New fabrication capacity takes years to build, and manufacturers aren’t rushing to overbuild into a demand environment this concentrated. The realistic outlook: pricing pressure continues through H1 2026, the earliest possible relief is H2 2026, and elevated pricing baselines are likely to persist well into 2027. Planning assumptions that ignore this timeline are setting organizations up for compounding variance. The Impact Goes Well Beyond Hardware Refresh This is where a lot of IT leaders are underestimating their exposure. Memory cost inflation isn’t just a hardware purchasing problem — it’s flowing through the entire technology stack. Cloud infrastructure is getting squeezed as providers compete with hyperscalers for the same memory supply. Memory-intensive workloads like databases, analytics platforms, and AI services may see 10–20% effective cost increases as providers adjust their pricing models. Enterprise servers are particularly exposed. DDR5 64GB RDIMMs widely deployed in enterprise data centers could approach double their early-2025 pricing by late 2026. Enterprise SSD pricing is up 25–40% depending on the segment, and lead times are extending to 26–40+ weeks in certain categories. SaaS renewals aren’t immune either. Vendors facing higher infrastructure costs are adapting their pricing models accordingly. Annual increases of 8–25% are showing up across segments, with AI-related features commanding 30–110% premiums. Renewal negotiations increasingly reflect these infrastructure cost pass-throughs, whether the contract mentions memory or not. The bottom line: if you’re managing an IT budget, memory pricing is influencing your costs whether you’re buying hardware or not. What This Looks Like in Practice: The Cisco Example Abstract market dynamics are easy to dismiss. A policy change from a vendor you’re actively negotiating with is harder to ignore. Earlier this year, Cisco made a significant change to its commercial terms for compute orders. The vendor revised its pricing policy to reserve the right to adjust pricing between order placement and shipment — citing component costs, manufacturing changes, tariffs, and exchange rates as justification. The company also added a provision allowing it to cancel compute orders up to 45 days before shipment. This is a direct consequence of the memory supply dynamics described above. Vendors are absorbing acute component volatility and, increasingly, they’re passing that risk back to buyers through contract terms rather than price. What does this mean practically? Pricing certainty between order and shipment can no longer be assumed through at least Q3–Q4 2026. A purchase order that felt locked in is now subject to adjustment. For organizations with large Cisco compute programs underway, that’s a contract risk shift, not just a pricing inconvenience. For procurement teams, this type of change demands an immediate response. NPI’s guidance is to audit all open quotes and purchase orders for hardware and execute high-priority items as quickly as possible. Waiting is no longer a neutral decision. We also recommend briefing finance on the need for 15–25% budget contingency for hardware through 2026, and engaging Cisco account teams directly to understand the scope of quote price protection changes. Cisco isn’t alone in this. It’s a leading indicator of where vendor commercial terms are heading across the industry. When suppliers are managing this much input cost volatility, the risk gets allocated somewhere. Right now, that somewhere is increasingly the enterprise buyer. The Real Differentiator Is Procurement Discipline Here’s something consistent in what we observe across enterprise IT buying: memory cost inflation doesn’t affect all organizations equally. The difference is almost always operational discipline, not budget size. The behaviors that increase exposure are surprisingly common: Long internal approval cycles that push orders into higher pricing bands Accepting short quote validity windows without negotiating extensions Using OEM default configurations without validating against actual workload requirements No independent benchmarking against current fair market value Refresh schedules still anchored to pricing assumptions from 12–18 months ago In a market where pricing resets quarter over quarter, a delayed approval or a missed pricing window isn’t just an inconvenience. It can mean absorbing the next pricing increase on a program that might represent millions in spend. What to Do Right Now The strategic response isn’t overly complicated, but it does require moving sooner than may feel necessary. Pull forward refresh activity where budgets allow. The longer you defer, the more likely you are to absorb the next pricing reset. Align IT, finance, and procurement earlier in budget cycles so that internal approvals don’t create the costly delays that passive processes typically do. Negotiate structural protections. Extended quote validity windows, allocation commitments for large programs, and pricing protections for multi-quarter rollouts aren’t unusual asks in the current climate. Push for them. Recalibrate your standard configurations. Memory-heavy defaults that made sense 18 months ago may be adding cost without adding value. Aligning RAM tiers to validated workload requirements (rather than OEM defaults) can generate meaningful savings at scale without a performance tradeoff. Update your multi-year cost models. Planning assumptions that don’t account for sustained elevated pricing through 2027 will produce budget variance. That’s not a matter of if, but when. The Bottom Line Memory has moved from a background component cost to a primary driver of IT budget variance. It’s showing up in hardware quotes, cloud bills, and SaaS renewals — and the enterprises managing through it most effectively aren’t necessarily the ones with the biggest budgets. They’re the ones with the most disciplined procurement processes. Cost escalation in this environment is manageable. But only when it’s anticipated, not deferred. Want the full picture? NPI’s white paper, Containing Memory Cost Inflation, provides a detailed breakdown of market dynamics, enterprise exposure points, and strategic planning guidance. Download it here. Share This Article Subscribe For Updates Uncover negotiation leverage and unlock savings across your IT spend.