Samsung and Glance are introducing an opt-in AI-driven lock screen advertising experience that uses your selfie to tailor fashion ads. Built on Glance’s existing lock screen platform, the new AI shopping feature fuses personalized imagery with shoppable content, leveraging generative AI to place you in outfits and destinations you might not have imagined. The rollout is slated to begin in the coming weeks on a broad swath of Samsung devices, starting with the Galaxy S22, S23, S24, and S25 series. While the premise centers on convenience and personalization, the approach raises questions about biometric data, consent, and how much control users retain over the ads that appear on their screens. Samsung emphasizes that participation is strictly opt-in, and users can continue to use the standard lock screen if they choose not to engage with Glance AI.
This article delves into how Glance AI operates on Samsung devices, what data it collects, and how it uses that data to generate and display personalized fashion content. We will explore the technical underpinnings of the feature, including the AI models involved and the data flows that power real-time ad generation. In addition, we’ll compare this AI-powered experience to Glance’s traditional lock screen ads and to other AI shopping initiatives announced by tech giants, such as Google’s AI Mode in Search. The piece also examines privacy safeguards, retention policies, and the broader implications for users, advertisers, and device manufacturers. By unpacking the rollout details, user experience, and regulatory context, we aim to provide a comprehensive, SEO-friendly analysis of this evolving intersection of AI, advertising, and personal data on mobile devices.
Overview and rollout details
Glance’s AI-enabled shopping experience marks a notable evolution in how lock screen real estate is monetized and personalized. The concept has long positioned the lock screen as a prime advertising surface due to the frequency with which users interact with their devices. Glance has historically offered an ad-supported, non-AI lock screen experience that has appeared on devices from Samsung, Motorola, and other manufacturers. The existing model relied on curated imagery, notifications, and promotional content that could be tapped to open shopping experiences, all while maintaining a baseline level of user engagement through familiar visuals and timely updates. The new AI-enhanced version expands on that premise by introducing generative capabilities that create bespoke visuals featuring the user themselves.
The AI shopping feature is designed to be fully opt-in. Samsung and Glance emphasize that users must explicitly enable the AI experience to access the enhanced lock screen ads. If a user never opens Glance or completes the initial setup, the phone remains on the standard lock screen experience, with no AI-generated content appearing on the device. This opt-in model is central to the rollout strategy and is intended to give users a clear boundary between traditional lock screen content and the more personalized, AI-driven advertising. The rollout is described as broad but phased, with initial availability rolling out to Galaxy devices in the S22, S23, S24, and S25 lineups. The deployment is expected to begin immediately and extend over the next month, with plans to broaden support across additional Samsung devices within approximately 30 days.
From a product design perspective, Glance AI aims to blend the familiar convenience of a lock screen with the allure of personalized shopping. The standalone Glance AI app will be available in the Google Play Store, while on Samsung devices, the experience will integrate with the Galaxy Store to ensure a seamless installation and update path. The dual-path availability—via a dedicated app and an integrated lock screen feature—allows Samsung to test the waters with users who prefer a discrete app-based experience and those who want a more integrated, native feel on their device. This arrangement also helps Glance experiment with usage patterns, engagement metrics, and monetization strategies without forcing a single, uniform user experience across all devices.
To summarize the rollout timeline: the AI-enhanced lock screen experience will be accessible to a wide audience of Galaxy users in the coming weeks, beginning with the Galaxy S22 through S25 families. The company plans to expand to a broader set of Samsung devices within 30 days, potentially including newer or mid-range models based on regional availability and device compatibility. Samsung and Glance have positioned this as a staged deployment designed to collect real-world usage data and feedback, enabling iterative refinements to both the user interface and the behind-the-scenes AI inference processes. It’s worth noting that the opt-in requirement remains a core safeguard, ensuring that users retain ultimate control over whether face-based, AI-generated ads appear on their lock screens.
How Glance AI works: technology and user experience
At the heart of Glance AI is a generative pipeline that relies on a user-provided selfie and minimal demographic details to craft personalized fashion advertisements. After opting in, a user is asked to take a selfie and provide basic body-type information, which serves as inputs for the AI system. The feature then leverages powerful image-generation models to produce stylized visuals that place the user in outfits and contexts that align with the advertised items. The end result is a dynamic set of lock screen images that depict you wearing clothing and visiting locations you would plausibly encounter, thereby making the ads feel both personal and aspirational.
Two AI systems underpin the generation process in this implementation. The service utilizes Google Gemini and Imagen as its core image-generation engines to construct fashion ads that reflect the user’s likeness and preferences. The combination of these models enables the production of photorealistic or stylized renderings, depending on the chosen ad campaign and design language. Because the visuals are AI-generated, the ads can adapt in real time to trending content, local events, and social media moments. This dynamic capability helps ensure that the inventory on display remains timely and relevant to the user’s context.
From a user experience standpoint, the lock screen becomes a living gallery of personalized fashion content. Images render you in outfits that are tailored to your body type, lifestyle, and inferred preferences, with destinations and scenarios suggested by the creative algorithms. The experience is designed to be visually engaging and highly interactive: users can tap on the displayed outfits to explore purchase options, potentially triggering a shopping flow within the app or a partner ecosystem. The “buy with a tap” concept is central to Glance’s monetization strategy, providing an immediate conversion path for advertisers and a measurable revenue stream for the platform.
The Glance AI workflow also includes safeguards around data handling and consent. Users are explicitly informed that the AI will generate personalized imagery, and the opt-in framework allows for consent withdrawal and account deletion processes. The AI-generated content is tied to the user’s biometric input (the selfie) and metadata such as location granularity, which Glance reports as general rather than precise. The plan to retain biometric data for 12 months from the last interaction or until account deletion is part of the privacy posture described by Glance. While the policy indicates that this data won’t be used for other purposes or shared with third parties without consent, the reality of such claims depends on ongoing oversight and regulatory compliance, especially given the sensitivity of biometric information.
In practice, the AI-driven experience aims to create a sense of immediacy and relevance. The ads are designed to reflect outfits people might consider buying in daily life, with options anchored in real-world fashion items and travel contexts. The AI-generated imagery can feature outfits and scenarios that align with local events, seasons, or trending aesthetics, thereby increasing the likelihood of engagement. This approach blends the allure of novelty with practical shopping, offering a seemingly seamless pathway from casual scrolling to purchase. For users who are curious or enthusiastic about AI-powered fashion discovery, Glance AI presents a compelling—albeit potentially unsettling—vision of next-generation shopping.
Opt-in model and user controls
A central pillar of Glance AI is its explicit opt-in design, which governs whether users participate in the AI-powered lock screen experience. Samsung and Glance have stressed that the feature should be activated deliberately by users who want to engage with personalized fashion ads generated from their selfies. If a user prefers not to participate, they can continue using the standard lock screen without any AI augmentation. This distinction between opt-in and opt-out experiences provides a clear boundary and helps preserve user autonomy over the presence of face-generated content on their devices.
Activation typically occurs through the Glance app or Galaxy Store integration, where users can grant permission for access to the camera, biometric data, and location in a controlled and reversible manner. The opt-in flow is designed to be transparent, with explicit explanations of what data will be collected, how it will be used, and what controls are available to manage consent. Users retain the right to revoke consent at any time, which should disable further generation of AI imagery and remove biometric data from Glance’s systems according to the stated data-retention policy.
Within the opt-in framework, users gain access to a fully integrated AI shopping experience on the lock screen, which includes real-time generation of personalized visuals and direct tappable links to purchase items. The purchasing pathway is designed to be frictionless: tapping an image prompts a shopping flow that showcases the item and may offer a quick purchase option. This streamlined interaction is what makes the experience attractive to advertisers and potentially lucrative for Glance and Samsung, but it also heightens the importance of robust consent mechanisms and transparent disclosures to users.
To support user control, Glance provides settings that allow users to manage their AI-generated content. For example, there should be options to disable certain features, adjust privacy preferences, or delete biometric data and account information. If the user deletes their Glance account, the platform states that the biometric data used to create the digital avatar will be removed, aligning with common privacy principles that prioritize user choice and data minimization. These controls are essential for ensuring that users can calibrate their engagement with AI-driven advertising and mitigate concerns about data retention and cross-service sharing.
In addition to opt-in choices, the experience includes safety and content moderation features to prevent inappropriate use of AI-generated imagery. While Glance emphasizes the novelty and personalization aspects, there is also an implied responsibility to avoid generating content that could be misleading, harmful, or defamatory. The moderation framework would need to address edge cases, such as the use of the user’s image in dangerous or unwanted contexts, and to provide remedies for users who encounter such occurrences.
Privacy, biometric data, and data handling
The privacy dimensions of Glance AI are central to understanding the ethics and legality of face-based advertising. The system relies on biometric data—the user’s selfie—paired with non-identifying metadata to produce personalized visuals. This combination heightens concerns about how biometric information is stored, processed, and shared, particularly given the potential sensitivity of facial data. Glance describes a data-retention policy that preserves biometric data for 12 months from the last interaction or until the user deletes their account. This retention window raises questions about user rights, data portability, and the ability to fully erase traces of biometric profiles from sophisticated AI infrastructures.
Glance’s privacy policy indicates that generated images and associated data may be retained for the stated period and that data aggregation enables better targeting and personalization. The policy also notes that some data may be shared with partners, which introduces a layer of third-party exposure. Even with formal consent, sharing biometric-derived outputs with external entities carries unavoidable risks related to data leakage, re-identification, or misuse. Consumers—already increasingly wary of data collection—may find these practices intrusive, particularly when the AI-generated assets depict them in contexts they may not have originally consented to or anticipated.
From a regulatory perspective, the use of biometric data for personalized advertising is subject to evolving standards and guardrails. In some markets, biometric data is treated with heightened sensitivity and subject to stricter consent requirements. The opt-in nature of Glance AI aligns with best practices in privacy-first design, but the practical reality of data flows—such as location data and partner sharing—requires ongoing scrutiny. End-users must be informed about what data is collected, for what purposes, and who may access it. A transparent privacy notice and predictable data deletion processes are essential to maintain trust and comply with applicable privacy laws.
The emotional and psychological implications of seeing a personalized AI-generated avatar on one’s lock screen cannot be understated. The experience can feel intimate or even invasive, depending on how comfortable users are with highly tailored images appearing in a space they interact with frequently. Even if the images are generated from user-provided selfies and consented to, the mere existence of a system that perpetually creates and refreshes AI-rendered likenesses can provoke unease in some audiences. These concerns underscore the need for clear consent language, easy opt-out mechanisms, and robust data-security measures to protect users from unauthorized access or misuse.
In addition to consent and retention, the question of data portability remains important. If users decide to discontinue using Glance AI, they should be able to retrieve their data in a portable format, request deletion, or obtain a summary of what data has been stored and processed. Ensuring that data erasure is comprehensive across all storage locations, backups, and downstream partners is a nontrivial challenge but a necessary one to maintain user confidence and align with privacy-by-design principles.
Comparison with other AI shopping and lock screen ads
Glance’s AI experience sits within a broader ecosystem of AI-assisted shopping and personalized advertising. During a recent product reveal at a separate event, Google showcased its AI Mode shopping feature, which brings shopping capabilities into the AI-powered search experience. The concept here revolves around virtual try-on and AI-generated imagery that appears as users search for fashion and other products, enabling a fluid transition from discovery to purchase. While both Glance and Google aim to leverage AI-generated visuals to drive sales, their approaches differ in scope and presentation. Google’s AI Mode shopping emphasizes integration within search results, whereas Glance AI focuses on the lock screen and device-embedded experiences that users encounter repeatedly throughout the day.
The Glance AI method is arguably more persistent and pervasive, given the lock screen’s constant visibility and the potential for continuous image refreshes tied to real-world contexts. In practice, this means that Glance’s system might generate new imagery on a near-constant basis to reflect shifting trends, events, and personal context. The trade-off is a heightened sense of intrusion for some users, who may perceive the lock screen as a private or semi-private space that should remain free of targeted advertising. The balance between relevance and privacy becomes crucial in this space, with successful execution requiring careful attention to consent, data handling, and user controls.
From a technical perspective, both companies lean on advanced generative AI, but the model choice, training data, and deployment strategy influence outcomes. Glance’s combination of Gemini and Imagen signals a robust, multi-model approach that can support diverse visual styles and content variations. Google’s AI Mode relies on its own suite of models designed to operate within the search ecosystem, with a strong emphasis on seamless integration into a broad set of services. The practical difference for the user lies in where and how the generated content is encountered: Glance AI appears directly on the lock screen, while Google’s experience is more embedded within the search journey. This distinction affects user interaction, engagement rates, and potential monetization paths for advertisers.
The advertising ecosystem around these AI-driven experiences is evolving rapidly. Brands and retailers are likely to be drawn to highly personalized ad formats that leverage user likeness and contextual data to boost conversion. The allure is clear: personalized visuals can increase engagement and reduce friction in the shopping path. However, this also introduces heightened responsibility for consent management, data protection, and transparent disclosure of how user data informs content generation. Industry observers anticipate that privacy regulations will increasingly shape the design and deployment of such features, encouraging more explicit consent mechanisms and clearer boundaries around data sharing and retention.
Impact on brands, advertisers, and the advertising ecosystem
The introduction of AI-generated, face-based ads on lock screens represents a potential shift in how brands interact with audiences on mobile devices. For advertisers, the ability to place highly personalized visuals in a space that users frequently glance at—without requiring explicit user navigation—offers a powerful channel for discovery and conversion. The lock screen acts as a non-intrusive yet highly visible touchpoint, especially when paired with an opt-in model that ensures relevance and user willingness. In this context, brands have the opportunity to craft immersive campaigns that showcase their products in aspirational, user-specific contexts.
However, this new form of advertising also invites scrutiny about privacy, consent, and user experience. Brands must carefully consider the boundaries of personalization, ensuring that messages remain respectful and non-coercive. Over-personalization could lead to a perception of manipulation or invasion of privacy, which in turn risks eroding user trust. Advertisers will need to align campaigns with ethical guidelines and regulatory expectations, emphasizing transparent data use and clear opt-out options. The balance between effective marketing and user autonomy becomes a critical axis for success in this space.
From a monetization perspective, Glance’s model blends ads with e-commerce, offering a direct path from impression to purchase. The ease of tapping on an image to initiate a shopping flow can reduce friction and accelerate conversions, creating tangible revenue opportunities for both Glance and Samsung. The standalone app and Galaxy Store integration provide flexible distribution channels, allowing advertisers to reach users through multiple onboarding experiences. It is plausible that Glance will experiment with different ad formats, pricing models, and performance metrics to optimize ROI for advertisers while maintaining a positive user experience. The ongoing challenge will be to reconcile the desire for personalized content with responsible data practices and user trust.
The broader advertising ecosystem could see ripple effects beyond Samsung devices. If Glance AI proves successful, other OEMs and platform providers might explore similar opt-in, AI-driven, face-based advertising modalities. This could lead to a more widespread adoption of privacy-forward consent mechanisms, improved transparency around data use, and a push for more user-centric control over personalized advertising. The market dynamics could shift toward models that emphasize user empowerment and value alignment, reinforcing the notion that high personalization can coexist with robust privacy protections, provided there is clear, user-controlled governance over data and consent.
Technical and security considerations
Technically, Glance AI relies on sophisticated AI models and a data pipeline that processes user-provided imagery and contextual data. The integration with Gemini and Imagen signals a hybrid approach to generating diverse visual outputs, which may be optimized for speed and realism. The on-device experience is complemented by cloud-based processing that can handle heavy computation, model orchestration, and content delivery. This architecture must balance latency, privacy, and scalability to deliver a smooth user experience across a wide range of Samsung devices.
Security considerations are central to protecting biometric data and ensuring that ads remain appropriate and non-manipulative. Biometric data, such as facial imagery used to generate avatars, demands rigorous safeguards against unauthorized access, retention beyond the stated period, and potential leakage through data breaches. Encryption, strict access controls, and robust authorization mechanisms are essential to minimize risk. The policy of retaining biometric data for up to 12 months introduces a window during which data must be secured against misuse and accidental exposure. In addition, any third-party sharing with partners requires explicit consent and compliant data-handling practices.
The AI generation process also implies content moderation challenges. Generated images could inadvertently reflect sensitive attributes or be misused in ways that violate platform policies or cultural norms. Effective moderation—both automated and human-reviewed—helps prevent inappropriate outputs that could harm users or brands. The system must monitor for misuse, ensure that prompts are constrained to acceptable categories, and provide an easy route for users to report concerns or request content removal.
Regarding data flows, the lock screen experience introduces a constant loop of data generation and retrieval. The selfie and accompanying metadata feed the AI inference pipeline, and the resulting visuals are rendered on the device’s lock screen or displayed through the Glance app. Data may also be transmitted to partners as part of the advertising workflow. To maintain user trust, it is essential that these data flows include explicit consent, transparent disclosure of purposes, and robust controls for data minimization, retention, and deletion. Users should have a straightforward path to delete biometric data from all storage locations, including backups, and to deactivate or remove their Glance account entirely.
From a security architecture standpoint, the deployment strategy must account for supply-chain integrity and app integrity protections to prevent tampering with ad content, image generation outputs, or credential storage. Regular security audits, vulnerability assessments, and transparent incident reporting help maintain confidence in a system that handles sensitive biometric data. Given the sensitive nature of face-based personalization, ongoing risk management and responsible disclosure practices will be critical to sustaining a safe and trusted experience.
Public policy, regulatory context, and user rights
The rollout of AI-generated, face-based lock screen ads intersects with a rapidly evolving regulatory landscape around biometric data and personalized advertising. Privacy laws in various jurisdictions place heightened emphasis on consent, data minimization, purpose limitation, and the right to deletion or data portability. Opt-in mechanisms can be aligned with these requirements, but their effectiveness hinges on how clearly users understand what they are consenting to and how easily they can revoke consent. Regulators may scrutinize the scope of data used for AI generation, the retention timelines for biometric data, and the extent to which users can control or opt out of partner data sharing.
User rights in this context include access to information about what data is collected, how it is used, and with whom it is shared. A meaningful right to delete or export biometric data becomes especially important when dealing with self-generated images that represent a person’s likeness. Regulatory bodies might also demand that platforms provide straightforward, user-friendly interfaces for adjusting consent preferences, removing data, and confirming retention policies. In jurisdictions with strict biometric privacy laws, the Glance AI approach could face additional compliance requirements or even restrictions.
From a consumer advocacy perspective, there is an expectation that AI-driven personalization should improve user experience without compromising privacy excessively. Critics may argue that any system that relies on facial data to generate imagery for advertising risks normalizing the creation and storage of biometric profiles, potentially normalizing surveillance-like practices. Proponents, however, might emphasize the benefits of highly relevant shopping experiences, reduced search friction, and the ability to discover items aligned with one’s personal style. The ultimate takeaway for policymakers is to balance innovation with robust privacy protections, ensuring that consent remains informed, verifiable, and reversible.
Samsung’s broader device and software strategy also comes into play. As device-makers balance revenue generation with user trust, features like Glance AI illustrate a push toward monetizing pervasive mobile experiences while maintaining opt-in safeguards. The success of this approach depends on clear communication with users, consistent privacy protections, and demonstrable value that does not come at the expense of user autonomy. The market’s response will likely hinge on how effectively Samsung and Glance translate consent into a trusted, value-driven shopping experience that respects privacy while enabling personalized discovery.
Conclusion
Samsung’s collaboration with Glance to introduce AI-generated, face-based lock screen ads represents a significant step in the evolution of mobile advertising and AI-powered shopping. The opt-in framework is a critical pillar, offering users a choice about whether to engage with a highly personalized, selfie-based content experience. The use of Google Gemini and Imagen to power the visuals underscores the ambition to deliver striking, contextually relevant fashion ads directly on the lock screen, with direct pathways to purchase through tap-enabled actions. The rollout across Galaxy S22, S23, S24, and S25 devices signals a broad market test that will help determine the appetite for this kind of personalized advertising in daily mobile use.
Yet the approach also foregrounds enduring concerns about biometric data, privacy, and the potential for perceived intrusion. The retention of biometric data for up to 12 months, the possibility of data sharing with partners, and the constant generation of AI images based on user likeness raise questions about consent, control, and security. The policy framework described by Glance emphasizes user choice and data deletion, but the real-world effectiveness of these safeguards will depend on ongoing compliance, clear user communication, and responsive protection against misuse. As this technology matures, regulators, industry players, and users will be watching closely to assess whether the benefits of highly targeted shopping can be achieved without eroding trust or compromising personal privacy.
In the broader landscape, Glance AI’s lock screen shopping experience sits alongside other AI-driven shopping innovations that aim to shorten the path from discovery to purchase. The tension between seamless convenience and privacy remains a defining feature of this category. For advertisers and brands, the opportunity to reach users with personalized visuals on a highly engaged touchpoint is compelling, but it must be pursued with transparent consent mechanisms and rigorous data protections. As Samsung and Glance continue to refine the product, the coming weeks will reveal how users respond to a more intimate, AI-generated advertising experience and whether the market embraces this new model of on-device personalization.
