In the rapidly evolving landscape of personal computing, semantic search is emerging as one of the key differentiators for Microsoft's Copilot+ PCs. Unlike traditional Windows 11 machines, Copilot+ devices leverage updated Windows Search with semantic indexing to deliver a substantially smarter search experience. But while the promise is alluring—context-aware, AI-powered searching that works locally and preserves user privacy—the practical results today are, as many early users and reviewers report, a mixed bag. Examining both the strengths and the holes in the current implementation provides an enlightening window into how Copilot+ is raising the bar, as well as the hurdles Microsoft must clear before semantic search becomes an unqualified win.
Semantic search on Copilot+ PCs is a sharp departure from the classic Windows Search experience. Instead of relying on literal phrase matching or Boolean logic, semantic search employs a small, local language AI model running on the system’s Neural Processing Unit (NPU). The advantage? Users can type in natural, descriptive queries, and the search engine will attempt to understand your intent, surfacing results even if there are no obvious keyword matches in file names or metadata.
What makes this approach particularly notable—and in some respects, more privacy-friendly than its competitors—is that all data gathered from semantic indexing stays local. As confirmed by Microsoft’s own documentation and corroborated by coverage from trusted tech publications, “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.” This local-first processing sharply contrasts with the cloud-centric semantic search strategies deployed by Google or Apple, underscoring Microsoft’s push for on-device intelligence as a selling point for Copilot+ hardware.
Compatibility, however, is restricted to Copilot+ hardware. This category spans devices using Snapdragon X Series Arm processors as well as newer AMD Ryzen AI 300 and Intel Core Ultra 200V Series chips—systems all equipped with NPUs capable of running these advanced AI models locally. Standard Windows 11 PCs are currently left out, and there’s no sign, as of now, that Microsoft will backport semantic search to non-Copilot+ hardware.
Fine-tuning what gets indexed is handled in Settings under
It is worth noting that, despite these user-accessible settings, some reviewers have observed that even full overnight indexing occasionally leaves some files unindexed. This is a point that may frustrate users with large libraries or uncommon file organization schemes.
However, semantic understanding isn’t perfect or omniscient. For more abstract or indirect associations—such as searching for a folder associated with “music software” in hopes of surfacing the Ableton Live directory—the results fell short, even after extended indexing. The current generation model does not yet appear capable of establishing some forms of contextual relationships, particularly with app-based associations or more specialized terms.
Yet this capability is uneven. In several tests, searching for specific content (such as “warbler,” a small bird) surfaced images that were tangentially relevant (a Lesser Goldfinch, a similar-looking creature) rather than precise matches. Other times, a simple search for “mountain” yielded no results, even among a folder filled with relevant photos. Image content analysis’s reliability still appears to be highly query dependent.
Additionally, image format support is selective. JPG, PNG, GIF and other common filetypes are supported, but RAW image files such as Sony’s .ARW or Canon’s .CR3 did not appear in results for terms like “raw camera.” Advanced photographers, therefore, will find the current search experience lacking for their needs.
Within the Settings app, semantic search offers an upgraded experience, albeit one that is not bulletproof. While searching “update” brings up the correct section, combining terms as in “update OS” sometimes yields no results. Simple synonyms, such as “reboot,” more reliably surface relevant settings (like Recovery), showcasing the improved flexibility over keyword matching but demonstrating persistent gaps in semantic understanding.
This architecture means that even when searching sensitive or private files, the risk profile is significantly reduced compared to cloud-reliant competitors. It also means that semantic search remains fully operational when the PC is offline, a boon for users with patchy internet or those working in restrictive environments.
Additionally, users must temper expectations. This first-generation AI search provides glimpses of brilliance but can just as often disappoint—either through incomplete indexing, semantic misses, or missing support for specialized files. There is also the potential risk that local AI models, if vulnerable, could one day become an attack surface (though at present, there is no indication or reporting of exploits in Microsoft’s implementation).
Finally, while local processing is a substantial privacy win, Microsoft’s opaque communication around machine learning pipelines means some users may still worry about unexpected data exposure—especially as Copilot+ features continue to roll out and integrate more deeply across the OS.
Within a year or two, as AI models mature and Microsoft iterates on user feedback, it is likely semantic search will become a staple of the Windows experience—seamlessly integrated, more accurate, and accessible across hardware lines. For now, Copilot+ owners get an early taste of that future. While it’s not flawless, its strengths already outweigh its inconsistencies, and it serves as a glimpse of the way we’ll soon all expect to interact with our devices.
The key takeaway for Windows power users and newcomers alike: semantic search is worth trying now, but don’t expect perfection. Give it time, provide feedback, and watch as your Copilot+ PC becomes not just smarter, but more attuned to what you actually mean when you search. With each update, that vision will only become clearer.
Source: PCMag Australia Semantic Search Makes Your Copilot+ PC Smarter, But Only Sometimes
The Anatomy of Semantic Search on Copilot+
Semantic search on Copilot+ PCs is a sharp departure from the classic Windows Search experience. Instead of relying on literal phrase matching or Boolean logic, semantic search employs a small, local language AI model running on the system’s Neural Processing Unit (NPU). The advantage? Users can type in natural, descriptive queries, and the search engine will attempt to understand your intent, surfacing results even if there are no obvious keyword matches in file names or metadata.What makes this approach particularly notable—and in some respects, more privacy-friendly than its competitors—is that all data gathered from semantic indexing stays local. As confirmed by Microsoft’s own documentation and corroborated by coverage from trusted tech publications, “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.” This local-first processing sharply contrasts with the cloud-centric semantic search strategies deployed by Google or Apple, underscoring Microsoft’s push for on-device intelligence as a selling point for Copilot+ hardware.
Rolling Out Semantic Search: Compatibility and Installation
Getting access to semantic search is a straightforward affair for Copilot+ PC owners. An updated version of Windows 11, installed via the usual Windows Update process, activates the feature. While some Copilot+ enhancements arrive under a “Preview” label, semantic search in Windows Search has been afforded full, non-preview status for eligible devices. Microsoft distinguishes its new Copilot+ exclusives into two “waves.” Wave 1 includes features like Cocreator for Paint, Live Captions, Recall, and Windows Studio Effects; Wave 2, where semantic search sits, encompasses the updated Windows Search, “Click to Do,” and super-resolution in Microsoft Photos.Compatibility, however, is restricted to Copilot+ hardware. This category spans devices using Snapdragon X Series Arm processors as well as newer AMD Ryzen AI 300 and Intel Core Ultra 200V Series chips—systems all equipped with NPUs capable of running these advanced AI models locally. Standard Windows 11 PCs are currently left out, and there’s no sign, as of now, that Microsoft will backport semantic search to non-Copilot+ hardware.
Under the Hood: How Semantic Search Works
Semantic search depends on the thorough indexing of your files—a process that is more resource-intensive than traditional Windows Search setups. Microsoft openly acknowledges that the first round of semantic indexing can take substantial time, recommending that users leave their Copilot+ PC plugged in during this process to ensure uninterrupted completion. According to Microsoft's documentation and echoed by hands-on testers, users may encounter a note above the search box reading, “Results from this PC may be incomplete,” accompanied by a progress spinner until indexing ends.Fine-tuning what gets indexed is handled in Settings under
Privacy and Security > Searching Windows. Users can restrict or expand the coverage (say, from Documents and Pictures only, to the entire drive using the “Enhanced” mode). Indexing status and progress are also visible on this settings page. For those wanting more granular control, the indexing service can be started or stopped via the Microsoft Management Console—helpful for advanced users, but something novices likely won’t need to touch.It is worth noting that, despite these user-accessible settings, some reviewers have observed that even full overnight indexing occasionally leaves some files unindexed. This is a point that may frustrate users with large libraries or uncommon file organization schemes.
How Semantic Search Performs: Everyday Usage
Searching for Documents: Natural Language Triumphs and Limitations
Where Copilot+ semantic search shines brightest is in document retrieval. The system is adept at handling varied semantic queries, surfacing relevant files—even in cases where your search term doesn’t appear verbatim in the file name or content. In one test, searching for “web benchmarks” surfaced a spreadsheet titled “browser benchmarks”; a query for “internet testing” also produced the desired file. This marks a distinct improvement over traditional keyword-based indexing, particularly for users who don't name their documents methodically.However, semantic understanding isn’t perfect or omniscient. For more abstract or indirect associations—such as searching for a folder associated with “music software” in hopes of surfacing the Ableton Live directory—the results fell short, even after extended indexing. The current generation model does not yet appear capable of establishing some forms of contextual relationships, particularly with app-based associations or more specialized terms.
Searching for Images: Smart, Yet Still Learning
Image search introduces another compelling vector for Copilot+’s semantic model. The system can, in some surprising instances, visually recognize content within your images, regardless of original file naming. Searches for “flamingo” delivered photos of bright pink birds, even when filenames contained no useful keywords—a result indicating that the AI is applying content analysis reminiscent of photo apps like Google Photos, but notably, all on-device.Yet this capability is uneven. In several tests, searching for specific content (such as “warbler,” a small bird) surfaced images that were tangentially relevant (a Lesser Goldfinch, a similar-looking creature) rather than precise matches. Other times, a simple search for “mountain” yielded no results, even among a folder filled with relevant photos. Image content analysis’s reliability still appears to be highly query dependent.
Additionally, image format support is selective. JPG, PNG, GIF and other common filetypes are supported, but RAW image files such as Sony’s .ARW or Canon’s .CR3 did not appear in results for terms like “raw camera.” Advanced photographers, therefore, will find the current search experience lacking for their needs.
File Explorer and Settings Searches: Mixed Bag
The semantic search functionality extends into File Explorer, with similar performance characteristics as the main search bar. Users will notice the telltale AI “star” icons, now a recurring visual metaphor for Copilot+’s generative powers. However, the semantic search enhancement does not operate in file-picker dialogs (such as when inserting images into Word), which can come as an unfortunate surprise to users expecting system-wide consistency.Within the Settings app, semantic search offers an upgraded experience, albeit one that is not bulletproof. While searching “update” brings up the correct section, combining terms as in “update OS” sometimes yields no results. Simple synonyms, such as “reboot,” more reliably surface relevant settings (like Recovery), showcasing the improved flexibility over keyword matching but demonstrating persistent gaps in semantic understanding.
Caveats and User Feedback Loops
Because semantic search is both new and evolving, Microsoft has equipped the system with direct user feedback options. Contextual pop-ups allow users to flag successes and failures, providing actionable intelligence for Microsoft to refine the underlying AI model. While some might view this as a tacit admission that the system is incomplete, it's a proactive move: feedback mechanisms are invaluable in iterating AI features towards greater accuracy and inclusivity.Security and Privacy: Local-Only Advantage
One of the standout strengths of semantic search on Copilot+ is its approach to privacy. Whereas other AI-powered search tools may rely on processing user data in the cloud—creating potential vectors for privacy breach or misuse—Microsoft’s feature remains resolutely local. Both official documentation and respected security researchers confirm that semantic indexes are kept strictly on-device. No files are transmitted to Microsoft, nor are queries used to train AI models globally.This architecture means that even when searching sensitive or private files, the risk profile is significantly reduced compared to cloud-reliant competitors. It also means that semantic search remains fully operational when the PC is offline, a boon for users with patchy internet or those working in restrictive environments.
Areas Where Semantic Search Falls Short
Despite the innovation, several clear limitations persist:- Indexing Speed and Reliability: The time required for thorough initial indexing can be substantial—many hours to more than a day, depending on library size and hardware. Even after completion, some files or folders may remain stubbornly undiscovered.
- Inconsistent Semantic Understanding: While some queries succeed even with vague or indirect wording, others fail to connect obvious contextual dots. There remain substantial gaps where the AI doesn’t seem to “get it.”
- Partial File Type Coverage: Proprietary and less-common document or image formats may not be indexed or searchable, limiting the benefit for advanced users or creators using specialized software.
- User Interface Fragmentation: Not all Windows search surfaces are upgraded—file dialogs in third-party apps, for instance, still rely on the older, less capable search logic.
- Copilot+ Lock-In: The technology is exclusive to select, new-generation hardware, meaning millions of Windows 11 users are excluded unless they shell out for an NPU-equipped device. There is, at present, no plan for wider rollout.
- Transparency for Non-Experts: Technical users can dig into the indexing service via Windows Management Console, but there is little transparency or control in standard Settings for issues like “half of my files aren’t indexed,” which can puzzle everyday users.
Strengths: Why Semantic Search Represents the Windows Future
Despite these shortcomings, there are compelling reasons to believe semantic search marks the beginning of a fundamental shift in how people interact with their files and system settings:- Natural, Conversational Queries: Instead of forcing users to remember exact file names or precise keywords, semantic search accommodates more “human” queries. This is a meaningfully better experience, especially for less technical users.
- Privacy by Design: All processing is local; user data is neither exported nor pooled for remote model training.
- AI-Powered Visual Discovery: The ability to surface relevant images based on content (not just metadata) hints at a future where finding media files becomes frictionless and intuitive.
- Foundation for Continuous Improvement: With a user feedback loop firmly in place and the underlying AI models upgradable via Windows Update, the technology is poised for rapid refinement.
- Synergy With Other Copilot+ Features: As Microsoft introduces deeply integrated, AI-powered tools (like Recall, Paint Cocreator, and Studio Effects), semantic search provides a connective tissue tying these enhancements together, making the OS feel smarter and more cohesive.
Risks and Potential Downsides
The “Copilot+ only” nature of semantic search could accelerate device obsolescence for millions of otherwise-capable Windows 11 machines, posing environmental and value concerns. If the performance gap is mostly attributable to AI acceleration rather than deep platform changes, those left behind may view this as a forced upgrade tactic.Additionally, users must temper expectations. This first-generation AI search provides glimpses of brilliance but can just as often disappoint—either through incomplete indexing, semantic misses, or missing support for specialized files. There is also the potential risk that local AI models, if vulnerable, could one day become an attack surface (though at present, there is no indication or reporting of exploits in Microsoft’s implementation).
Finally, while local processing is a substantial privacy win, Microsoft’s opaque communication around machine learning pipelines means some users may still worry about unexpected data exposure—especially as Copilot+ features continue to roll out and integrate more deeply across the OS.
The Verdict: Imperfect Today, But Undeniably the Future
In the final analysis, semantic search on Copilot+ PCs is a clear leap over traditional Windows Search. Its ability to understand intent, surface information from across multiple file types, and protect user privacy through local processing sets a new bar for what’s possible on consumer PCs. However, it is equally clear that this is a version 1.0 product, with rough edges that will frustrate those expecting the all-seeing AI promised in marketing materials.Within a year or two, as AI models mature and Microsoft iterates on user feedback, it is likely semantic search will become a staple of the Windows experience—seamlessly integrated, more accurate, and accessible across hardware lines. For now, Copilot+ owners get an early taste of that future. While it’s not flawless, its strengths already outweigh its inconsistencies, and it serves as a glimpse of the way we’ll soon all expect to interact with our devices.
The key takeaway for Windows power users and newcomers alike: semantic search is worth trying now, but don’t expect perfection. Give it time, provide feedback, and watch as your Copilot+ PC becomes not just smarter, but more attuned to what you actually mean when you search. With each update, that vision will only become clearer.
Source: PCMag Australia Semantic Search Makes Your Copilot+ PC Smarter, But Only Sometimes
