AI-enabled personal computers are on track to become the majority of the global PC market by 2026, according to new projections from Gartner, underscoring a structural shift in client computing even as supply chains and tariffs continue to cause friction.
AI PCs set for rapid share gains
Gartner now expects AI PCs to account for 54.7% of worldwide PC shipments in 2026, or about 143.1 million units. That is almost double the 77.8 million units forecast for 2025, when AI PCs are projected to reach a 31% share.
The upgraded outlook follows earlier revisions tied to tariffs and procurement disruptions, but the trend still points to steady mass adoption over the next two years.
User demand, not hardware, seen as main hurdle
Analysts warn that the pace of adoption will depend less on chip performance and more on whether users find compelling reasons to upgrade.
Current AI features such as meeting transcription or simple assistants may not be enough to trigger large replacement cycles. Demand is expected to turn only if more advanced local functions gain traction, including enterprise-grade privacy computing, on-device model inference and domain-specific copilots that reduce reliance on cloud services.
Should these capabilities become commonplace, enterprises could accelerate refresh cycles across their PC fleets and related IT systems.
Chipmakers race to define the AI PC stack
Competition among chip designers is intensifying as the Windows-based AI ecosystem shifts from early trials to a multi-vendor market.
NVIDIA and MediaTek have joined established players in AI PCs, adding pressure on incumbents. NVIDIA is concentrating on GPU-centric designs and tight software integration. AMD is leaning on its combination of x86 CPUs and GPUs. Qualcomm is pitching energy efficiency and always-connected capabilities, particularly around Windows-on-Arm devices. Intel is using its entrenched enterprise channels and large client base to defend share and push new AI-accelerated platforms.
The entry of more suppliers is widening hardware options, but also increasing platform risk as traders weigh which architectures and software stacks will dominate.
Advanced nodes keep TSMC at center of supply
Regardless of whether x86 or Arm gains more ground in AI PCs, manufacturers remain heavily dependent on advanced semiconductor processes.
TrendForce estimates global wafer foundry revenue at about $41.7 billion in the second quarter of 2025, with TSMC capturing 70.2%. By the fourth quarter, revenue is projected to rise to $46.3 billion, and TSMC’s share to 70.4%. This cements the foundry’s position as the key supplier of high-performance chips spanning AI PCs, data center servers and premium smartphones.
This concentration reinforces an existing industry structure where a small number of manufacturers hold the most advanced production nodes and, in turn, much of the sector’s pricing power.
Market performance and trading themes
Market data from Yahoo Finance show shares of AMD, Intel, Arm and TSMC have all displayed strong elasticity over the past year, but with differing risk profiles.
Analysts often frame TSMC as a relatively stable core holding for exposure to manufacturing, AMD as a primary performance growth driver tied to GPUs and data center wins, and Arm and Intel as higher-risk turnaround or re-rating stories linked to new platforms and execution on roadmaps.
Structural strains from memory and component demand
The AI build-out is amplifying stress across the component stack. The global high-bandwidth memory market is forecast to expand from $6.96 billion in 2025 to $8.67 billion in 2026, according to industry projections. Rising demand for HBM and other advanced components is already feeding into shortages and price inflation, complicating sourcing and margin management for PC makers.
Gartner now expects global semiconductor revenue to jump 64% in 2026, helped by what analysts label “memflation” — a surge in memory prices. DRAM prices alone are projected to climb 125% over the year. While this supports profitability for memory suppliers, it risks delaying PC and server upgrades, particularly among cost-sensitive enterprise buyers.
NVIDIA’s Arm push challenges x86 dominance
Platform risk is rising as well. Reports from early June 2026 confirm that NVIDIA’s new RTX Spark platform, built on Arm architecture, will directly challenge the long-standing dominance of x86 processors in the Windows ecosystem.
The move creates the possibility of a genuine architectural split inside the world’s most widely used desktop operating system, heightening uncertainty for OEM roadmaps and for chipmakers most exposed to traditional x86 Windows deployments, notably Intel and its closest rival.
Software compatibility emerges as key bottleneck
The software layer remains the main friction point, especially for Windows-on-Arm.
Microsoft used its recent Build conference to showcase AI agents designed to speed up porting of legacy x86 applications, an acknowledgment that hardware capabilities have outpaced the readiness of the app ecosystem. Success in this area will be critical for Arm-based platforms to move beyond niche status into mainstream enterprise use.
Macro and policy risks cloud the outlook
Sector risks remain significant. If AI PC applications fail to deliver clear productivity gains, users may hold onto older devices longer, weakening shipment forecasts. Slower progress in Windows-on-Arm compatibility would limit upside for Qualcomm and other Arm-based entrants.
Trade policies, export controls and changes in enterprise IT budgets could all weigh on demand. At the same time, tight supply at advanced nodes, or any deterioration in macroeconomic sentiment, could pressure valuations across the semiconductor value chain.
Traders should watch for:
- The pace of AI feature roll-out on devices versus actual usage in enterprises and among consumers
Long-term shift rather than short-term trade
Despite near-term volatility, observers broadly describe the AI PC story as a multi-year industry transition rather than a brief cyclical upturn.
As headlines rotate between product launches, supply bottlenecks and policy risks, attention is increasingly centered on companies that control critical manufacturing capacity, platform-level software and robust cash generation. Those segments are seen as the more durable revenue engines in an environment where both demand for compute and constraints on affordability are tightening simultaneously.
In the near term, the trajectory of the market will depend less on benchmark scores or shipment guidance and more on whether corporate and household budgets can absorb higher device prices driven by expensive components and memory. The core tension for the sector is clear: strong long-term demand for AI computation, set against immediate constraints in supply, pricing and real-world willingness to upgrade.
Want deeper insight into AI’s role in finance and trading? Explore our guide on Web3, AI, and crypto next.
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