Windows Copilot+ Semantic Search: The Future of Desktop Search is Here

For many Windows users, desktop search remains a perennial frustration—a clunky, often literal tool that doesn’t 'understand' context, intent, or meaning and rarely finds what you’re looking for unless you remember the exact filename or its location. With the introduction of Copilot+ PCs, Microsoft is seeking to redefine this core experience by leveraging local AI for semantic search—an ambitious marriage of language modeling and edge-device processing, promising to make your searches more natural, more accurate, and ultimately more productive. But does it deliver on this vision, or is it yet another AI-enabled feature that sparkles in demos but submits to inconsistency in real-world use? Let’s examine the reality behind the promise, verify the technical claims, and analyze what Windows’ next-generation semantic search brings to the table—warts and all.

What Is Semantic Search on Copilot+ PCs?​

Semantic search, in the simplest terms, is search that understands meaning. Rather than matching raw strings or keywords, it seeks to comprehend the intent and context of your query, thus fetching results that are relevant even if their filenames—or even textual content—don’t exactly match the search terms.
The semantic search feature in Copilot+ PCs goes well beyond the humble search bar at the bottom of your Windows taskbar. According to Microsoft documentation and hands-on reports, it applies to:

• The main Windows Search box in the taskbar
• File Explorer
• The Settings app

It uses on-device language AI models—specifically running on the Neural Processing Unit (NPU) present in Copilot+ hardware—to perform local semantic indexing and retrieval, functioning entirely offline. This is a deliberate privacy move by Microsoft: “All data gathered from semantic indexing is stored locally on your PC. None of it is ever sent to Microsoft or used to train AI models”. That’s a crucial point for anyone concerned about cloud privacy or data sovereignty.

How To Get Semantic Search: Hardware, Software, and Set-Up​

Semantic search is a Copilot+ exclusive. That means it’s not just about running the latest version of Windows 11; your PC needs to be part of a new hardware class—Copilot+—which as of mid-2024 includes devices running:

• Snapdragon X Series Arm processors (Qualcomm)
• AMD Ryzen AI 300 Series
• Intel Core Ultra 200V Series

If you own a Copilot+ PC, activating semantic search is straightforward: Navigate to Settings > Windows Update and check for updates. Accept and install any new builds, then restart your PC. If the feature still doesn’t appear, ensure “Get the latest updates as soon as they’re available” is toggled on for early access to new waves of Copilot+ features. Once active, you'll spot the telltale “star sparks” overlaying your search magnifying glass—the new AI insignia per Microsoft’s visual language update.

Wave 1 vs. Wave 2 Features​

Microsoft distinguishes between feature “waves.” Wave 1 Copilot+ exclusives launched with Paint Cocreator, Live Captions, Recall, and Studio Effects. The improved Windows Search—semantic search—is classed as a Wave 2 feature, alongside other generative AI enhancements such as Super Resolution in Photos and Click to Do. This staged rollout strategy is consistent with how Microsoft is gating certain AI features behind Copilot+ hardware, which has triggered both excitement and controversy among Windows enthusiasts.

Indexing: The Necessary Precursor​

Semantic search demands that your PC index all its searchable files—a compute-intensive, largely automatic process that can take hours, especially on large volumes of files. According to Microsoft's support documentation and reflected in PCMag’s testing, initial indexing is not controlled via the Settings UI but through the Microsoft Management Console:

• Hit Win + R to launch Run, and type services.msc.
• Locate the Windows Search service. Here, you can start or stop indexing—a helpful trick if you want to minimize resource usage at inopportune times.

Microsoft recommends plugging in your Copilot+ PC during this process to avoid performance bottlenecks and ensure indexing completes without interruption. The Enhanced search option (in Settings > Privacy and Security > Searching Windows) broadens the search scope to cover your entire PC but at the cost of longer, heavier indexing. Classic mode limits searching to user folders—Documents, Pictures, Music, etc.—and is much quicker.
Frustratingly, you cannot directly prioritize or view per-folder indexing status except via that main Settings pane. In practice, even after hours of indexing, some users report that only a portion of their files have been indexed—a limitation that clearly undermines the promise of universal searchability, at least in the short-term.

Real-World Experience: Where Semantic Search Shines​

For Files and Documents​

True to promise, semantic search can return files by meaning rather than literal phrase matching. For example, searching for “web benchmarks” may successfully identify a document called “browser benchmarks”; entering “internet testing”—with no filename overlap—can also surface that file. This capability finally brings desktop search behavior in line with the semantic logic we’ve come to expect from modern web search engines.
Supported document formats, according to Microsoft and corroborated by field testing, currently include:

• DOCX (Word documents)
• PDF files
• PPTX (PowerPoint)
• TXT
• XLSX (Excel)

For Images​

Windows Search now treats all images as “Photos,” regardless of extension. It supports a variety of common image formats:

• BMP, GIF, ICO, JPEG, JPG, PNG

A striking demonstration involves searching for “flamingo”—which, even absent any textual hints, produces images of that long-necked pink bird if present on your PC. Likewise, a query for “warbler” returned an image of a yellow bird, specifically a Lesser Goldfinch, noted for its resemblance. This suggests that the underlying AI is not just keyword-matching metadata but processing image contents with an image model, likely using on-device vision transformers optimized for the NPU. However, the lack of official documentation describing exactly which vision models are employed warrants some skepticism; reported results may vary depending on both the build and the hardware.

Limitations​

This capability, while impressive, has notable blind spots. For example, common raw camera file formats (.ARW from Sony, .CR3 from Canon) are not indexed or processed by semantic search. Queries like “raw camera” fail to retrieve such files, even if present in commonly indexed photo folders. And semantic image recognition is clearly better for common, easily-identifiable subjects (like “flamingo”) than for more complex or less-represented queries (“mountain” failed to yield appropriate images in testing).

Within the Settings App​

The semantic engine is now built into the Settings search as well. Typing common troubleshooting queries (“reboot”, “update OS”) often returns related settings, even where the exact phrase doesn’t appear verbatim in menu titles or descriptions—a clear improvement over the literal, almost comically rigid matching systems of previous builds.
It’s worth noting, though, that the feature is inconsistent. In PCMag’s real-world trials, typing “update OS” failed to lead to Windows Update settings, though “update” alone produced appropriate results. Other queries, like “reboot,” found related Recovery settings due to inferred semantic similarity. This highlights both the promise and the pitfalls: semantic search can intelligently match context, but is still brittle with phrasing and sometimes fails completely.

Where Semantic Search Falls Short​

Despite its sophistication, the feature’s current implementation is far from foolproof.

• Indexing Gaps: Critically, full-search fidelity hinges on complete, error-free indexing. Yet many users find that—at least initially—the index is incomplete, leading to missed results or the “Results from this PC may be incomplete” warning.
• Limited File-Type Support: As mentioned, raw file formats for cameras are ignored, as are countless other non-standard or professional file types.
• No Integration With File-Picker Dialogs: Despite the new search working in File Explorer, it does not extend to file-picker windows (those seen when selecting files to attach or insert within applications like Word). This curtails the reach of the AI-enhanced experience in numerous workflow contexts.
• Unexpected Result Gaps: Even with text-based content, semantic search can occasionally miss highly relevant matches if phrasing diverges from what the AI recognizes. This unpredictability makes it unreliable for some power users and professionals.
• Configuration and Transparency: The ability to understand, configure, or prioritize how semantic search works remains limited. Most options are buried or absent altogether, and power users may want more transparency or control.

Privacy: Microsoft’s Local Processing Pledge​

One of the most important claims, and among the most verifiable, is that semantic search happens entirely on-device and is never sent to Microsoft’s cloud for analysis. According to the latest Microsoft whitepapers and official documentation:

• All semantic indexing is processed and stored locally, leveraging the Neural Processing Unit for acceleration.
• No data is transmitted to Microsoft, nor is private user content used to train future iterations of Microsoft’s AI models.

This stands in marked contrast to several previous Microsoft search features (such as Cortana’s cloud-based history indexing) and should alleviate most privacy concerns for those worried about sensitive corporate or personal data leakage. Independent audits or reviews, however, would provide further reassurance—Microsoft’s claims, though detailed, remain self-attested.

How To Fine-Tune or Report Issues​

Recognizing that semantic search is a work in progress, Microsoft has incorporated subtle feedback mechanisms within Copilot+. When the search yields errors or fails to meet expectations, a pop-up in the lower-right corner offers a quick avenue for reporting issues. This crowdsourced feedback is expected to drive ongoing improvements, and Microsoft has historically been responsive to such input in the context of new Windows 11 features.

Strengths and Notable Advances​

• Truly Context-Aware Search: Files and images are often findable via intent, rather than strict keywords. This is an enormous quality-of-life advance over prior Windows Search implementations.
• Offline, On-Device Security: All semantic intelligence remains local, protecting privacy and sidestepping enterprise compliance risks.
• File-Type Breadth: For mainstream documents and images, semantic search supports most common extensions, broadening its appeal for general users.
• Convergence Across Search Domains: Having similar smart search capabilities in the taskbar, File Explorer, and Settings minimizes confusion and eases adoption.
• Visibly Marked AI Features: The “star sparks” visual cue makes it clear (at least to power users) when the new model is engaged.

Key Weaknesses and Areas for Concern​

• Incomplete Indexes Undermine Results: If your PC isn’t fully indexed—or if distinction between what is and isn’t indexed is unclear—search confidence is undermined.
• Spotty Support For Advanced File Types: Advocates for creative or technical workflows will find little solace until formats like RAW images, specialty design files, or code repositories are fully supported.
• Unpredictable Phrasing Sensitivity: Despite its AI-driven fluidity, the search engine can fail outright if queries don’t match expected paraphrases, which may frustrate end-users.
• Missing From File-Picker Popups: The lack of semantic search within common app dialog windows limits its practical benefit.
• Low Transparency For Advanced Users: There’s little insight into how results are ranked, indexed, or why certain things appear or don’t appear.

Comparative Assessment: How Does It Stack Up?​

When set against competing desktop environments and their evolving search capabilities, Windows’ semantic search is a major leap. MacOS’s Spotlight and third-party tools like Alfred have long provided strong text-based indexing, but don’t currently match Copilot+ for semantic context-awareness or on-device AI-powered content analysis. That said, competitors often offer more transparency and customization—something power users may miss with Microsoft’s more opaque model.
Linux distributions with Tracker or Baloo offer some semantic tagging but usually require substantial manual input to achieve results that Copilot+ handles (when working) automatically. Still, Windows’ approach is currently unique in its local, NPU-accelerated, privacy-preserving model.

The Road Ahead: Incremental Perfection​

Despite its present rough edges, Copilot+ semantic search is a foundational shift in how we interact with digital content. As more users adopt Copilot+ PCs and provide feedback, Microsoft will be under pressure to rapidly iterate, fix quirks, and broaden support for additional file types, applications, and complex user workflows.
The fact that the feature’s scope is defined as a “Wave 2” capability—rolling out as part of a deliberate, hardware-gated strategy—suggests a dedicated investment on Microsoft’s part. If uptake is strong, expect further developments in companion APIs, business integrations, and (potentially) a loosening of restrictions on which hardware can participate, especially as NPUs become common across all new PC classes.
Until then, early adopters gain a powerful new tool whose strengths far outstrip previous generations—at least when it works. Occasional disappointment is inevitable, but so is the promise of steady, unmistakable improvement. For now, semantic search on Copilot+ PCs clearly points the way toward a smarter, more intuitive, and—critically—local-first future for Windows. If Microsoft’s track record holds, this may mark the beginning of a new era for desktop productivity; just be ready for a few missteps on the journey.

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Source: PCMag UK Semantic Search Makes Your Copilot+ PC Smarter, But Only Sometimes