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What the market forecasts say—and what they do not
Gartner’s August 28, 2025 forecast put AI PCs at 31.0% of worldwide PC market share in 2025, or 77.792 million units, and projected 54.7%, or 143.113 million units, for 2026. Gartner also forecast AI laptops at 35.7% of the total laptop market in 2025 and 58.7% in 2026. These figures indicate expected growth; they are not observed shipment totals. Gartner’s forecast and methodology context.
Gartner analyst Ranjit Atwal said adoption in 2025 was slowing because of tariffs and pauses in PC buying amid market uncertainty. That qualification matters for refresh plans: a fast-rising forecast does not mean every organization should accelerate replacement or that the forecast will be realized on schedule.
What IT decision-makers report about AI PCs
The available surveys show growing awareness and activity, but the findings come from different populations, dates, and sponsors. They should not be read as a single continuous measure of enterprise adoption.
| Finding | What it measures | Source and qualification |
|---|---|---|
| 58% were very or extremely interested in AI PCs | Interest among surveyed IT decision-makers | IDC, 2024, Intel-sponsored infographic; n=410 for this question |
| 84% supported employee use of generative AI services | Support for GenAI services, not AI PC ownership | IDC, 2024, Intel-sponsored survey; n=514 |
| 80% had heard of “AI PC”; 63% had heard of “neural processing unit” | Term awareness among surveyed IT decision-makers | IDC, 2024, Intel-sponsored survey; n=514 |
| 81% were deploying, piloting, or planning AI PCs within 12 months | Reported deployment stage: 27% deployed, 33% piloting, 21% planning | IDC, 2026, AMD-sponsored research summary; more than 500 IT and business decision-makers in the United States, Japan, France, the United Kingdom, and Germany |
| 70% expected agentic AI systems to influence employee workflows within two years | Expectation about future workflow influence, not observed deployment or impact | IDC, 2026, AMD-sponsored research summary; same five-country study context |
The 2024 IDC infographic was produced by IDC Custom Solutions and sponsored by Intel; the later figures were reported in AMD summaries of AMD-sponsored IDC research. Those sponsorships and differing survey bases limit direct comparisons. In particular, stated plans and expectations are not evidence that organizations completed deployments or achieved measurable benefits. IDC Custom Solutions’ 2024 Intel-sponsored infographic; AMD’s summary of the 2026 IDC study.
What executives expect AI PCs to deliver
In AMD’s September 2026 summary of AMD-sponsored IDC research, respondents named productivity improvement as an AI PC investment driver (59%), innovation or competitive differentiation (39%), and security benefits (35%). These are reasons respondents gave for investing, not independently measured causal effects. The evidence does not establish that buying an AI PC by itself improves productivity or security. AMD’s summary of the September 2026 IDC research.
Gartner also forecast that 40% of software vendors would prioritize on-PC AI capabilities by the end of 2026, up from 2% in 2024. This is a vendor-prioritization forecast, not proof that the applications an organization uses will support useful NPU features by a particular refresh date. Gartner’s forecast.
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Which AI PC platform fits a business?
There is no evidence here that one processor architecture is right for every company. Gartner forecast that x86 Windows devices would represent 71% of the AI business laptop market in 2025, compared with 24% for Arm. Gartner notes that business and consumer platform preferences differ and that application compatibility is one consideration. These are forecasts of market preference, not a recommendation for a particular enterprise fleet.
Atwal described the future of AI PCs as “customization.” For IT teams, that means evaluating devices against role-specific software and peripherals rather than selecting on an AI label or NPU specification alone. Check architecture-specific application constraints, compatibility with essential peripherals, management integration, endpoint controls, lifecycle support, and how each candidate fits the existing estate.
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How to decide whether an NPU matters in your refresh
An NPU is relevant only when software uses it for workloads the organization actually cares about. Before adding an AI PC requirement to a procurement standard, work through these decision points:
- Inventory real workloads. Identify current or committed applications that use NPU-enabled features, the roles that need them, and expected availability dates. Ask key independent software vendors for their feature roadmaps; do not treat general AI capability claims as application support.
- Compare local and cloud processing needs. Assess response time, privacy, and data-handling requirements for each workload. Local processing may change where computation occurs, but it does not automatically satisfy security, data governance, or regulatory obligations.
- Model the economics against refresh timing. Review current cloud AI service costs, any hardware premium, the expected replacement schedule, and a workload-based estimate of potential savings. A future on-device feature may matter when devices will remain in service for years, but the available survey evidence does not show that AI PCs save money for every buyer.
- Validate operational fit. Confirm that the candidate device works with existing endpoint management, security controls, deployment processes, and support arrangements. Include user understanding and training needs in rollout planning.
- Segment by role and configuration. Different users may need different applications, performance, battery, or form-factor trade-offs. Gartner and the Intel-sponsored IDC infographic both point toward customization rather than a single configuration for everyone.
The Intel-sponsored IDC infographic specifically recommends examining cloud AI service costs, consulting hardware partners about suitable systems, and asking important software vendors about NPU-feature roadmaps. These are sensible evaluation steps, not proof of a guaranteed return. IDC Custom Solutions’ planning recommendations.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Security, governance, and rollout are separate workstreams
AMD’s summary of its sponsored IDC research identifies security, integration with management tools, limited employee understanding, and uncertainty around regulatory or data compliance as planning considerations. Because this is AMD’s summary of AMD-sponsored research, it should be treated as a set of reported considerations, not a neutral census of all IT departments. AMD’s September 2026 summary.
Evaluate security controls and governance requirements directly for each proposed workload and device configuration. Decide what data may be processed locally, what may be sent to cloud services, how endpoint policies apply, and how employees will understand the approved uses. Purchasing hardware does not resolve these policy and compliance questions.
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What to take to the next refresh review
- Use shipment forecasts to understand market direction, not as evidence of final adoption or a mandate to replace devices early.
- Separate interest, deployment plans, and expectations from completed deployments and measured outcomes.
- Require application-level evidence that planned software features will use the NPU and arrive on a useful timeline.
- Compare platforms for compatibility and operational fit in the organization’s own environment.
- Base any business case on role-specific workloads, refresh timing, cloud costs, device premiums, governance needs, and measured pilot results.
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