The channel doesn’t make headlines. It makes sales happen.
Managed service providers, value-added resellers, and system integrators are the infrastructure through which most enterprise technology, including most enterprise AI, actually reaches customers. When that layer gets squeezed, the consequences don’t stay in the channel. They ripple into how AI products are scoped, sold, supported, and ultimately adopted. The Omdia survey published this week puts a precise number on a problem that’s been building for several quarters: nearly 60% of channel partners worldwide expect double-digit profit declines in Q1 2026 compared to a year earlier.
That’s not a bad quarter. That’s structural pressure.
What the Data Says
The Omdia survey, as reported by ChannelBuzz, identifies two primary drivers: costs outpacing the ability to pass through to customers, and hardware vendor pricing pressure alongside order cancellations. Less than a third of partners anticipated any profit growth at all. These are global figures representing partners across technology segments, traditional IT, cybersecurity, cloud infrastructure, and, increasingly, AI products and services.
A few important caveats before drawing conclusions. This is survey data, not actuals. Omdia’s methodology, sample size, geographic distribution, fielding dates, isn’t detailed in the available reporting. Survey respondents are describing expectations, not reporting confirmed results. Q1 actuals, when partners report them, may land better or worse than these estimates suggest. The figures deserve weight given Omdia’s standing as a global technology analyst firm, but they’re the beginning of the analysis, not its conclusion.
The Hardware Cost Pattern
The hardware pricing pressure cited in the survey isn’t isolated to this data point. The 2026 market has seen persistent component and infrastructure pricing tension as AI-driven demand for GPUs, networking hardware, and data center buildouts has collided with constrained supply chains that haven’t fully caught up to scale. Partners who built margin assumptions around 2024 hardware pricing have been repricing downward throughout the cycle.
Order cancellations add a separate dimension. When enterprise buyers cancel or defer hardware orders, a pattern associated with AI project uncertainty and budget cycle pressures – partners absorb the carrying cost of inventory commitments they can’t unwind cleanly. That drag doesn’t appear in vendor revenue lines. It shows up in partner margin compression exactly like what the Omdia survey is measuring.
The pattern running underneath these figures: AI infrastructure investment created hardware demand faster than the channel built the margin structures to service it profitably.
Where AI Products Fit
This section requires a clear distinction: the Omdia survey addresses channel economics broadly, not AI-specific channel segments. What follows is analytical inference from the verified data, not Omdia’s findings.
Partners carrying AI products face a specific version of the margin problem. AI software licensing, whether GPU-accelerated SaaS, AI agent platforms, or enterprise LLM deployments – typically involves higher upfront scoping costs than traditional software. Implementation complexity is real. Training requirements are real. Partners who take on AI engagements absorb those costs against margin structures that were designed for simpler product categories.
The GPU and AI hardware segment is acutely exposed to the pricing pressures the survey identifies. Partners who resell AI compute infrastructure, NVIDIA-adjacent hardware, AI-optimized servers, edge inference hardware, have watched component pricing move in ways that compress their resale margin even as enterprise demand nominally holds. Add order cancellation risk as AI projects face internal justification cycles, and the margin picture gets tighter.
Services margin, the historically higher-margin component of partner revenue, should theoretically provide buffer. AI implementation and managed services carry better margins than pure hardware resale. But those services require specialized skills that take time and money to build. Partners in the middle of that capability transition carry costs on both sides: the old hardware margin compression and the new services build-out investment.
What This Means for AI Vendors
Enterprise AI vendors who depend on channel partners to reach mid-market and distributed enterprise customers need to take the margin pressure seriously as a distribution strategy variable, not just a partner welfare concern.
Partners under severe margin pressure reprioritize. Products and vendors that offer better deal economics, higher margins, faster sales cycles, cleaner implementation scopes, get preference. AI products that require substantial partner investment to sell, implement, and support are at a disadvantage in a channel that’s tightening its portfolio.
Vendor response options include deal registration programs that protect partner margin, increased investment in partner enablement to reduce implementation costs, and co-selling models that reduce the partner’s exposure on complex deals. None of these are new playbooks. What’s new is the urgency: if Q1 actuals confirm the Omdia survey’s directional findings, vendors who haven’t already adjusted partner economics will face pushback in H2 planning cycles.
What to Watch
Three signals matter from here. First, Q1 partner earnings reports from publicly traded MSPs and resellers, companies like Insight Direct, CDW, or regional IT services firms – will confirm or qualify the Omdia survey’s directional picture with actual numbers. Second, GPU and AI hardware pricing data for Q2 will indicate whether the cost pressure is easing or persisting. Third, vendor pricing announcements, particularly from AI software players with significant channel presence, will signal whether the vendor layer is willing to absorb any of the margin pressure or pass it downstream.
The channel’s Q1 profit warning is a leading indicator. It’s worth watching before it becomes a lagging one.