Shopify Winter ’26 Turns AI Commerce into an Operating Model

Shopify’s Winter ’26 roll‑out makes AI-driven commerce not just a feature but an operating model — Agentic Storefronts, the expanded Shopify Catalog, and a suite of merchant tools knit product discovery, attribution, and in‑chat checkout into a single commerce ecosystem that could materially alter how merchants find customers and how investors value Shopify.

Background / Overview​

Shopify’s Winter ’26 Edition is a broad release that the company frames as a move from AI experiments to production‑grade commerce capabilities across merchant operations. The package includes more than 150 updates, ranging from store‑building AI assistants and new theme tooling to the headline feature, Agentic Storefronts, which syndicates merchant catalogs directly into AI chat platforms such as ChatGPT, Perplexity, and Microsoft Copilot. The company says merchants can set up once and have their products discoverable and purchasable inside multiple AI conversations while retaining the merchant‑of‑record relationship and checkout control. Those changes matter because several AI platforms are already experimenting with commerce flows that keep customers inside conversational interfaces. Shopify’s product play is to standardize how product metadata, availability, pricing, and policies are presented to agents so AI discovery surfaces the right item and routes the purchase back through Shopify checkout. The company also points to internal and merchant metrics indicating meaningful AI engagement: management has reported multi‑fold increases in AI‑driven traffic and orders year‑to‑date, which Shopify frames as an early signal of agentic commerce traction. This article explains exactly what Shopify shipped, evaluates the business and investment implications, cross‑checks the main claims against independent reporting and earnings commentary, and highlights the risks that could blunt upside for merchants and shareholders alike.

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What Shopify actually shipped in Winter ’26​

Agentic Storefronts and the Catalog / Checkout stack​

Agentic Storefronts is a packaging of three capabilities:

• Syndication: the Shopify Catalog standardizes billions of product attributes so AI agents can understand and rank items for conversational queries.
• Merchandising and identity: tools to control schema, FAQs, and knowledge base content so brands maintain tone, policy visibility, and product context inside agent responses.
• Checkout integration: the Checkout Kit and universal cart APIs let agents hand off, embed, or complete checkouts while keeping Shopify as the merchant of record.

Shopify positions this as one integration to many agent surfaces, allowing merchants to toggle participation per AI platform and get attribution and visibility in the admin. That single‑integration pitch is central: it converts Shopify’s scale of merchants and product signals into an infrastructure moat for agentic discovery.

Complementary improvements: Sidekick, SimGym, Rollouts, Product Network​

Winter ’26 also includes upgrades designed to boost merchant productivity and reduce friction in adopting new channels:

• Sidekick evolves from a reactive assistant to a more proactive collaborator (voice, screen sharing, code generation), intended to speed store setup and marketing tasks.
• SimGym simulates shopper behavior using aggregated purchase data to stress‑test launches and merchandising.
• Rollouts adds A/B scheduling and release controls embedded in the admin and theme editor.
• Product Network and AI discovery features provide cross‑merchant recommendations and richer Shop app experiences.

Individually these updates are incremental; together they aim to raise the floor on how quickly merchants can become agent‑ready.

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Why this could matter to merchants and to investors​

1) Expanded discovery channels at massive scale​

AI chat interfaces are becoming common first‑touches for research and shopping. Reported internal figures presented by Shopify’s leadership suggest AI‑driven traffic to Shopify stores is up roughly 7x year‑to‑date and that orders attributed to AI searches have grown ~11x. If these trends persist and scale across enterprise and SMB merchants, Shopify’s catalog and checkout plumbing could capture incremental GMV and payments revenue without requiring merchants to individually engineer integrations. Those metrics were discussed publicly on recent company calls and reported by multiple outlets. From an investor perspective, incremental GMV flowing through Shopify can grow revenue in both Subscription and Merchant Solutions segments: visibility and conversions support subscription upgrades, app usage, and payments volume. Agentic Storefronts directly links discovery to Shopify’s checkout and attribution — a value capture pathway that’s concrete rather than hypothetical.

2) Defensive moat built on structured product data​

Shopify’s claim is that its years of catalog experience — billions of product configurations — lets it clean, infer, and cluster product data in ways that generic crawlers or small merchants cannot. This matters because agentic discovery is extremely sensitive to structured attributes: missing or messy metadata equals zero visibility.
If the Catalog and metadata tooling deliver consistent results across millions of SKUs, Shopify would be less dependent on referral traffic and more likely to be the default supplier of reliable commerce data for agentic platforms. That represents a non‑trivial competitive advantage that’s hard for spot players to replicate quickly.

3) Faster merchant onboarding and lower execution risk​

The Winter ’26 tooling — AI store builders, Sidekick improvements, theme blocks, SimGym and Rollouts — reduces the time and cost for merchants to test agentic channels. Faster onboarding means more merchants become discoverable, which strengthens network effects: more products improve agent recommendations, which makes agents more useful, which drives more shoppers back to Shopify‑syndicated products.
This virtuous loop is the growth narrative underpinning optimistic analyst models: aggregate adoption plus monetization of payments and merchant services can justify material revenue acceleration if retention and pricing are preserved. However, the upside is model‑sensitive and depends on sustained platform economics.

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Financial and valuation context — what the numbers say​

Shopify’s recent results and third‑party forecasts provide concrete anchors for assessing Winter ’26’s impact.

• Recent quarter performance: Shopify reported revenue of roughly $2.68 billion and GMV near $87.8 billion, with merchant solutions and subscription growth cited as drivers in mid‑2025 reporting. Those results led management to project continued high‑teens to mid‑20s percent growth in subsequent quarters.
• Street and community models: some analyst frameworks incorporated by aggregators assume Shopify can grow into a scenario of ~$18.5 billion revenue and $2.7 billion earnings by 2028, implying roughly 22.6% annual revenue growth from current bases. Those projections are model‑dependent and assume successful monetization of new channels and continued margin expansion or stability. Simply Wall St highlights this version of the narrative as one plausible future.

Key takeaways for investors:

• To reach the more bullish revenue/earnings paths requires sustained, multi‑year scaling of AI channels and a high multiple for future earnings (analyst scenarios sometimes imply an elevated terminal P/E).
• The Winter ’26 feature set reduces execution risk on the product side but does not guarantee adoption by all AI platforms or merchant cohorts.
• Short‑term results are more likely to show operational benefits (higher conversion rates, faster merchant onboarding) than immediate, large revenue line items — the latter will require months to quarters of adoption and reporting refinements.

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Competition and platform risk — who stands in Shopify’s way?​

The real fight is for discovery and checkout control​

Agentic commerce is a battleground because whoever controls discovery inside widely used agents gains significant influence over product selection and checkout flow. Several players are moving aggressively:

• OpenAI / ChatGPT has rolled out in‑chat checkout experiments and agentic shopping features that integrate merchant checkouts directly in conversation experiences.
• Google and Microsoft are developing agentic shopping protocols and merchant programs that could favor their own ecosystems.
• Marketplaces like Amazon, with deep logistic and data assets, remain default destinations for many shoppers.

OpenAI’s Instant Checkout and other agentic initiatives show agents are willing to host commerce — but they also underline a risk: agents can set the terms of engagement, potentially extracting fees or privileging certain suppliers. Shopify’s play is to be the neutral infrastructure supplier that powers agent shopping while keeping merchants as the direct customer relationship. That positioning competes with both aggregators and agent owners.

Standards and fragmentation risk​

Agentic commerce today is fragmented: different platforms are experimenting with varying protocols for product discovery, payments, privacy, and returns. Shopify’s universal cart, Catalog API, and Checkout Kit are designed to abstract that fragmentation, but universal standards may still evolve in ways that favor in‑house platform players (agents or marketplaces) or impose new requirements on merchants.
If competing protocols prioritize agent ownership of the relationship or limit attribution fidelity, Shopify could face a squeeze: merchants would still need Shopify’s tooling for checkout and fulfillment, but the value‑capture dynamics (how much revenue Shopify derives from discovery and payments) could be altered by platform rules.

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Practical implications for merchants​

• Merchants should audit and fix product metadata now. Agentic discovery favors structured attributes; missing data equals invisibility. Tools that mass‑clean and harmonize attributes will be a practical near‑term ROI.
• Control brand voice and policies in Knowledge Base and schema. Agentic storefronts give the ability to control how products and policies are described in AI responses; merchants should map FAQ coverage and refund/return language to avoid surprises.
• Plan for in‑chat vs out‑of‑chat checkout. Merchants must decide whether to accept in‑chat checkouts (which can increase conversion but may change the checkout UX) or redirect to owned storefronts. Either choice has trade‑offs for data capture, email acquisition, and post‑purchase experiences.
• Track attribution carefully. Shopify claims to deliver AI channel attribution, but merchants should validate analytics and reconcile agentic orders with internal KPIs.

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Risks and unanswered questions​

Attribution fidelity and data ownership caveats​

Shopify’s promise of complete attribution and ownership of customer relationships depends on the cooperation and technical interfaces offered by AI platforms. If an agent performs discovery and controls the conversation without passing identifiable signals back to merchants, claiming a direct customer relationship may be more complex than Shopify’s marketing suggests. This is both a technical and a contractual issue with agent partners — it bears watching as integrations roll out.

Fee and revenue share uncertainty​

Agents that host checkout flows may seek fees, commissions, or preferential treatment for certain merchants. If agentic platforms monetize discovery aggressively, merchant economics could be pressured, which in turn could limit Shopify’s ability to monetize increased GMV without degrading merchant margins. The history of platform economics on mobile app stores and marketplaces suggests negotiation over fees will be sticky and visible.

Standards, policy, and regulatory scrutiny​

Conversational agents surface recommendations based on models that can be opaque. Regulators increasingly scrutinize algorithmic recommendations, ad disclosure, and data privacy. If regulators impose transparency or fairness obligations on agentic commerce, integration complexity and compliance costs could rise. This is a systemic risk across the industry, not just for Shopify.

Execution and merchant heterogeneity​

SMBs vary widely in catalog quality, margins, and logistics sophistication. The benefits of Agentic Storefronts accrue unevenly; enterprise merchants with disciplined metadata teams and inventory practices will likely capture the lion’s share of agentic visibility early on. That asymmetry could produce winner‑take‑most outcomes in verticals, concentrating GMV and dampening broad‑based merchant monetization.

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What this means for Shopify’s investment case​

• Winter ’26 materially strengthens Shopify’s product narrative: it turns the company’s claim of being central to agentic commerce into an operational product suite that is deployable at scale. That reduces some execution risk for the upside scenario.
• However, valuation sensitivity is high. Public models that extrapolate current trends into very high revenue and earnings outcomes require both (a) sustained GAAP/adjusted margin expansion and (b) favorable platform economics for checkout and payments. Aggregator forecasts that imply Shopify must hit roughly $18.5 billion in revenue and $2.7 billion of earnings by 2028 represent one path, but those scenarios are contingent on massive adoption and favorable monetization. Investors should treat such models as scenario outputs, not certainties.
• The timeline for meaningful revenue recognition from Agentic Storefronts is multi‑quarter: discovery gains may show up quickly in GMV and traffic metrics, but durable uplift to recurring revenue or payments revenue will lag adoption, contract terms with agents, and merchant behavior changes.

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Strategic checklist — metrics to watch over the next 12 months​

• Product discovery KPIs: growth in AI‑attributed traffic and conversion rates versus organic/search channels.
• Payments and checkout economics: share of orders completed via agentic in‑chat checkout and any revenue share terms disclosed with agents.
• Merchant adoption: percentage of active merchants who enable Agentic Storefronts and the distribution of that adoption by store size and vertical.
• Catalog quality improvements: decreases in SKU‑level mismatch, attribute completion rates, and listing deduplication metrics.
• Third‑party platform behavior: changes in agent protocols, fee announcements, or preferential placement agreements.

These metrics will indicate whether agentic commerce is additive to Shopify’s economics or if platform owners capture disproportionate value.

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Conclusion​

Shopify’s Winter ’26 Edition crystallizes a strategic bet: that the future of retail discovery will be conversational and that a company that standardizes product data, syndicates catalogs, and anchors checkout will retain centrality in merchants’ businesses. Agentic Storefronts and the supporting Catalog and Checkout APIs make that strategy practical — they lower the integration cost for millions of merchants and create a single product path to multiple AI ecosystems. That practicality is meaningful, but it does not eliminate the key investor questions. Adoption by AI platforms and merchants, the economics of in‑chat checkout, attribution fidelity, competitor and regulator behavior, and evolving agent protocols will all determine whether Agentic Storefronts is a competitive advantage or a necessary defense. Investors should treat Winter ’26 as a de‑risking product milestone rather than a guarantee of outsized financial upside; the feature set improves the probability of Shopify maintaining platform centrality, but the ultimate payoff depends on a set of interlocking market developments that will play out over several quarters.
Practical action for merchants and investors is the same: test, instrument, and measure. Merchants should prioritize metadata hygiene and pilot agentic flows; investors should watch the five KPIs above for evidence that agentic commerce is moving from promising pilot to material revenue driver. The Winter ’26 rollout changes the calculus — it raises the baseline for Shopify’s competitive case — but it leaves open enough dependency on external platforms and economics that sober scenario analysis remains essential.

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Source: simplywall.st Shopify’s New AI Commerce Ecosystem Might Change The Case For Investing In Shopify (SHOP) - Simply Wall St News

 

[ChatGPT]

LG has pushed Microsoft Copilot onto a swath of webOS smart TVs via a recent over‑the‑air update, and for many owners the result is an unwanted, non‑removable Copilot tile pinned to the home screen that can be hidden at best and only neutralized by cutting the TV’s network access at worst.

Background​

LG unveiled a broad AI strategy for its 2025 TV lineup that explicitly included deeper integration with Microsoft Copilot as an extension of its AI Search and personalization features. That vision was presented alongside other AI-driven capabilities such as AI Voice ID, content recommendations, and generative background images. The rollout was intended to make webOS a more conversational hub for finding content and managing settings, but the initial consumer experience has been messy and controversial.
Over the past week, users across online communities reported that a recent webOS firmware update automatically added a Copilot tile to home screens on multiple LG TV models. Unlike ordinary apps such as Netflix or YouTube, this Copilot tile has no visible uninstall option in the app management menus; it can typically only be hidden. A highly visible user thread on a mainstream forum gathered tens of thousands of upvotes and hundreds of reports from other owners who saw the same behavior.
This article breaks down what happened, why owners are rightly irritated, the technical and privacy implications, practical steps owners can take right now, and what this episode means for the future of smart TVs as platforms for AI features and third‑party services.

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What actually happened​

The rollout and how Copilot appears​

• After installing the latest webOS update, many owners found a Copilot tile pinned to the TV home screen alongside other apps.
• The Copilot experience delivered initially is web‑based rather than a deeply integrated native app — effectively a shortcut to Microsoft’s Copilot web page inside the TV’s browser shell in many reported cases.
• In the TV settings where apps are normally managed, Copilot shows up as a preinstalled or system app, and the usual “uninstall” option is absent; users are typically offered hide or disable at best.

How owners discovered and reported it​

Reports surfaced rapidly on community forums and social media after the update rolled out. Users posted screenshots and described attempts to remove the tile; many confirmed that a factory reset did not eliminate Copilot, consistent with it being included in the firmware image or pushed as a privileged system component.

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Why this matters: key problems and reactions​

Forced software on paid hardware​

Smart TV owners see their sets as purchased devices whose core software should be under their control. There is a growing expectation that preinstalled system apps should be removable or at least optional. The Copilot push violated that expectation for many users. The top frustrations are:

• Lack of consent — users did not opt in and were not given a clear choice during the update.
• No uninstall route — the app cannot be fully removed through normal UI controls, which many consider unacceptable on a device they paid for.
• Persistent UI pollution — a permanent tile consumes valuable home‑screen real estate and attention.

Privacy concerns and telemetry​

Smart TVs have increasingly become surveillance and advertisement endpoints through features labeled “Live Plus”, ACR (automatic content recognition), personalization, and voice assistants. Adding an assistant like Copilot raises immediate questions:

• Does the Copilot integration introduce new telemetry or data flows beyond existing webOS data collection?
• Is Copilot accessing contextual signals such as what’s on screen, microphone input, viewing history, or profile information?
• How long is conversational and usage data retained, where is it stored, and which corporate entities can access it?

LG provides settings to disable certain AI options like voice recognition and personalization, but users report those switches do not remove the Copilot tile or the app install. Without clear vendor documentation on what Copilot actually sends and stores, owners are understandably wary.

Broader consumer fatigue with “AI everywhere”​

This incident feeds into a broader cultural backlash: consumers are growing tired of AI features and third‑party services being inserted into devices and operating systems without transparent opt‑in. Smart TVs are particularly sensitive environments because they sit in private spaces (living rooms, bedrooms) and often have microphones, cameras, and persistent network connectivity.

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Technical anatomy: native app vs. web shortcut​

The Copilot users encountered looked more like a web shortcut than a full native integration. That matters for functionality and for risk:

• A web‑based Copilot shortcut is lighter to deploy (no heavy native SDK work), but it also may be less capable of the richer cross‑feature experiences LG described at trade shows.
• A system‑level install — even if it is just a web wrapper — can receive privileged placement on the home screen and may be protected from uninstall by design.
• If Copilot is embedded in the firmware image, a typical factory reset will re‑create the same state, explaining reports that resets did not remove it.

There is a fine line between a preinstalled convenience app and immutable system software that cannot be removed. The latter is what has inflamed owners here.

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Practical steps for affected owners​

If your LG TV received Copilot and you want to regain control, try these steps in order:

• Check the TV’s app management menu for hide or disable options and use them to remove the tile from visible home screens.
• In Settings, turn off any related AI features: disable Live Plus / ACR, voice personalization, and other data‑sharing toggles that might feed contextual signals.
• Perform a factory reset only after backing up preferences; some users reported the tile returns, but it is a reasonable troubleshooting step if the tile is newly introduced.
• Disconnect the TV from the internet (Wi‑Fi off or unplug Ethernet) to prevent Copilot from loading and to stop outbound telemetry while you investigate.
• If you need the TV online but want to block Copilot, consider placing the TV on a segmented guest network with firewall rules that block the specific endpoints Copilot uses — this requires router chops and endpoint address knowledge.
• Contact LG support to lodge a formal complaint and request options for removal. File tickets and persist — multiple customer reports put pressure on vendors to act.
• Consider returning the device if it’s newly bought and the preinstalled software violates local consumer protection expectations. Check warranty/return windows and local laws on software modifications to purchased devices.
• If privacy is a concern, raise it with your local data protection authority or consumer protection agency; mass pushes of non‑removable apps can attract regulatory attention.

These steps range from simple UI changes to more advanced networking workarounds. For many owners, the only immediate, reliable method to neutralize Copilot’s active behavior is to disconnect the TV from the internet.

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Corporate rationale and motives​

Why would LG do this? There are several plausible business drivers:

• Feature differentiation: integrating a branded assistant gives LG a marketable AI story for new models and marketing copy, positioning LG as an “AI TV” leader.
• Partnership value: alliances with major AI vendors (Microsoft in this case) create perceived product value and may include commercial agreements.
• Ecosystem control: preinstalling services increases the company’s control over the home screen and any monetization or engagement funnels that follow.
• Speed of deployment: shipping a web‑based shortcut is faster and cost‑effective compared to developing a fully native, deeply integrated assistant.

These motives are commercially rational but clash with consumer expectations about control and privacy.

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How this compares to other vendors​

The Copilot situation is not unique. Other TV vendors and device makers have a history of preinstalling partner services, sometimes as default assistants or unremovable apps. One high‑profile example in the broader device ecosystem involved a roll‑out where a major phone maker made an AI assistant the default through commercial arrangements with its partner, prompting antitrust scrutiny.
The pattern is consistent: device makers lean on preinstalled AI services to create perceived value and often monetize placement agreements, while users get stuck with software they didn’t explicitly choose.

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Legal and regulatory considerations​

This kind of forced software distribution raises several potential regulatory flags:

• Consumer protection: selling hardware with third‑party software that cannot be uninstalled could be considered unfair if it significantly impairs the device’s use or imposes unwanted tracking.
• Privacy law compliance: adding services that process personal or usage data must align with privacy regulations where the device is sold, including requirements for transparency and consent in some jurisdictions.
• Competition and antitrust: default placement or paid preinstallation of an assistant can draw attention from competition authorities, especially if evidence emerges of exclusive deals or coercive defaults.

Regulators worldwide are increasingly focused on how AI services are distributed and whether default placements harm competition or consumers. Mass complaints and coverage can prompt inquiries, and if companies have commercial arrangements behind the scenes, those deals can come under scrutiny.

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What LG and Microsoft could — and should — do​

To defuse the backlash and rebuild trust, a responsible approach would include:

• Releasing a firmware update that restores user choice by providing a clear uninstall option for Copilot or by making its installation opt‑in.
• Publishing detailed, plain‑language documentation about what data Copilot collects, where it’s processed, retention policies, and how users can opt out.
• Providing transparent settings that actually disable Copilot’s active behavior — not just hide the UI tile.
• Offering a Lean/Privacy mode that removes all third‑party assistants and related telemetry for owners who prefer a stripped‑down, local‑only TV experience.
• If Copilot was pushed as part of a commercial deal, disclose reasonable consumer safeguards and how the partnership affects data sharing.

Taking these steps would align product reality with customer expectations and reduce regulatory risk.

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Longer‑term implications for smart TV users​

This episode is a microcosm of a larger trend: smart TVs are becoming troves of AI features that extend beyond simple streaming. That can be useful — better content discovery and voice control can improve user experience — but the execution matters.
If device makers continue to ship non‑removable AI services, consumers will:

• Grow more skeptical of software updates and may refuse important security patches for fear of unwanted features.
• Demand stronger privacy and uninstall rights, potentially pushing regulators to act.
• Shift purchasing behavior toward vendors that offer clearer control and privacy guarantees.

The sustainability of the AI‑in‑everything model depends on giving users real choices, not just marketing language.

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Risk assessment for owners and IT managers​

Owners should evaluate risk across three dimensions:

• Privacy Risk: does Copilot introduce new data flows? If so, the risk is high in homes with sensitive conversations or family members concerned about data sharing.
• Security Risk: additional network‑enabled services increase the attack surface. Unremovable system apps that connect to external servers present a non‑trivial security risk if vulnerabilities arise.
• Operational Risk: for organizations using consumer smart TVs in conference rooms or shared spaces, unremovable apps are problematic for compliance and device governance.

For higher‑risk environments (workplaces, healthcare, finance), the safest route is to avoid consumer smart TVs for sensitive uses unless the device can be fully controlled and audited.

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What to watch next​

• Whether LG issues a firmware update that restores uninstallability or gives a formal opt‑out flow for Copilot.
• Vendor statements clarifying what Copilot does with on‑device and contextual data.
• Any regulatory complaints or consumer protection actions triggered by mass owner complaints.
• How other TV makers handle AI assistant placements and whether this episode accelerates vendor competition on control and privacy (not just features).

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Final analysis and verdict​

The controversy around Copilot being pushed into LG webOS TVs is not about AI itself — it’s about choice, control, and transparency. Users broadly accept that smart TVs will evolve and acquire new features. They do not accept being forced into third‑party services on hardware they already own, especially when the services cannot be removed and when the privacy implications are unclear.
LG’s stated vision for AI‑powered personalization is understandable from a product and marketing perspective, and there are legitimate product benefits to conversational search and assistance. But the execution — adding a non‑removable Copilot tile through a firmware update with limited documentation and no uninstall path — shows a disconnect between product priorities and consumer expectations.
Until vendors prioritize user autonomy and clear privacy defaults, these sorts of rollouts will continue to provoke backlash and could invite regulatory scrutiny. For now, affected owners must rely on hiding, disabling, network workarounds, or fully severing internet access to regain control. That is a poor trade for a paid device.
The sensible path forward for vendors is simple: give users choice, explain what data is collected, and make any assistant truly optional. Without that, AI features will remain a liability, not an enhancement, on the living room TV.

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Source: Fudzilla.com LG stuffs Copilot onto smart TVs