Google Gemini on iPhones and Samsung devices – a dominant shift in the global smartphone and AI market

What Gemini actually changes on smartphones

When Google lands on Apple: How a single AI assistant is reorganizing two platforms, entire industries, and billions of dollars in revenue

For years, interacting with our smartphones was clearly defined: tapping, swiping, and clicking on blue links. With the deep integration of Google Gemini, this habit is beginning to dissolve. The classic search function is being replaced by an intelligent dialogue partner that not only provides information but also understands and completes tasks. The smartphone is evolving from a mere information portal into a personal assistant.

Google Gemini is more than just a new feature; it's an attack on the foundations of the mobile internet. The existing paradigm—searching for information via lists of links—is giving way to a proactive, conversational assistant. For Google, this means a radical realignment of its business model, away from the search engine and toward ubiquitous AI.

The first deeply integrated partnerships in the smartphone segment emerged with Samsung's Galaxy S24 series. There, Samsung combines its own Galaxy AI features with Google's Gemini Pro in the cloud and Gemini Nano as an on-device model for selected tasks. The S24 devices are thus early examples of hybrid AI architectures: computationally intensive tasks run via Google Cloud or Vertex AI, while latency-critical or sensitive tasks run locally on the device.

In parallel, Google rolled out its Gemini app and chatbot approach across platforms. From mid-2024, Gemini was initially available on iPhones in Europe via the Google app. At the end of 2024, a standalone Gemini app for iOS followed, offering expanded features such as Gemini Live, integration with Dynamic Island and the Lock Screen, and support for numerous languages. This means that Gemini on iPhones is no longer just a hidden feature within the Google app, but a prominent, independent access channel to Google's AI.

What is economically decisive is less the technical fact that Gemini now also runs on iPhones, but rather the combination of three developments:

First, interaction with digital services is shifting from traditional search to AI-powered assistants. Second, this layer is becoming cross-platform – Gemini runs on Android (including Samsung) and iOS, with features that extend beyond browsers and apps. Third, a new market is emerging for AI-driven premium services, subscriptions, and on-device features, spanning hardware, chips, cloud services, and advertising.

Against this background, the economic effects can be structured into four dimensions: global market structure, regional shifts, industry and value chain effects, and the strategic positioning of Google, Apple, Samsung and other players.

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Global market structure: How significant is Gemini's leverage on iPhones?

To understand the economic relevance, the basic question is: How large is the addressable market?

In global smartphone sales, Apple and Samsung were virtually neck and neck in 2024. Studies based on IDC data show that Apple sold approximately 232 to 233 million iPhones in 2024 (around 18.8 percent market share), while Samsung sold about 223 million devices (around 18.1 percent). Both manufacturers thus operate at a similar volume, although Apple is the clear number one in numerous premium and high-price segments.

The picture looks different when looking at the installed base. Android dominates globally with a market share of approximately 70 to 73 percent, while iOS holds around 27 to 28 percent. In absolute numbers, this roughly equates to 3.3 to 3.5 billion active Android devices compared to approximately 1.4 to 1.5 billion iPhones. This means that even if Gemini were used on all iPhones, Android would still clearly lead in terms of numbers.

The economic leverage lies not only in the number of units sold, but also in willingness to pay and usage patterns. Various analyses show that iOS users spend significantly more per capita in the app ecosystem than Android users and generate more revenue in the App Store than on Google Play, even though there are twice as many Android devices worldwide. Premium smartphones now account for roughly a quarter of global smartphone sales, with Apple controlling two-thirds of sales in this segment and Samsung just under a fifth. This means that while iPhone users are fewer in number, they are, on average, considerably more valuable in terms of services, advertising, and subscriptions.

At the macro level of AI markets, the field is growing rapidly. Depending on the study, the global generative AI market is estimated to be worth between $20 billion and $40 billion by the mid-2020s and is projected to reach $1 trillion or more by the early to mid-2030s, with annual growth rates of well over 20 to almost 40 percent. Specifically, the market for mobile or on-device AI is estimated at around $20 billion to $25 billion by the mid-2020s and is expected to grow to $80 billion to $85 billion by 2030. In parallel, the market for on-device AI architectures is growing from around $5 billion to $6 billion in the mid-2020s to over $17 billion by 2032.

For Google, the move to iOS means systematic access to a particularly lucrative segment of this growth market. For Apple, it means that its own devices will increasingly become a front end for third-party AI services – with opportunities (increased device appeal) and risks (loss of added value).

Technological starting point: Different Gemini roles on Samsung and iPhone

Although Gemini is available on both platforms, the roles differ fundamentally

On Samsung Galaxy S24 generation devices, Gemini is present in three forms: as the cloud-based model Gemini Pro, which enables features such as note summaries and context processing in system apps; as the image-based model Imagen 2 for generative photo editing; and as the on-device model Gemini Nano for local tasks such as smart replies or text summarization, integrated via Android's AICore. The models run partly in the Google Cloud (Vertex AI) and partly directly on the device using dedicated NPUs in the Snapdragon or Exynos SoC.

Technically speaking, Gemini is a base layer in the operating system and hardware architecture that Samsung integrates into its own features such as Chat Assist, Live Translator, Note Assist, and Generative Edit. Samsung pays Google Cloud for access to these cloud models and simultaneously differentiates its premium devices from cheaper Android devices, which lack such NPUs or have limited functionality, through on-device AI.

The situation is different on iPhones. Initially, Gemini was available as a separate tab within the Google app; later, a dedicated iOS app was added, which relies on text- and voice-based interactions, image generation, and integration with Google services (YouTube, Maps, Gmail, Calendar, etc.). Most of the processing takes place in the cloud; the iPhones primarily serve as the interface. There is no on-device Gemini variant at the chip level like Samsung's; instead, there is an app layer that is abstracted via iOS.

From an economic perspective, this difference is significant: On Samsung devices, Gemini generates cloud revenue (Vertices AI) but simultaneously drives demand for high-performance NPUs, DRAM, and high-end SoCs for on-device AI. On iPhones, Gemini primarily generates cloud and subscription revenue for Google, while Apple sells the devices and controls the infrastructure, but outsources the AI ​​computing workload to Google. In scenarios involving deeper Siri/Apple Intelligence integration of Gemini, as discussed since 2024/2025 and hinted at in initial agreements in 2026, this disparity would become even more complex, because Apple would then have to pay Google for access to Gemini models.

Economic effects for Google: From search giant to platform-agnostic AI provider

For Google, the rollout of Gemini on Samsung smartphones and iPhones is the key lever to reduce its dependence on the traditional search business without jeopardizing its cash flow

Historically, roughly two-thirds of Alphabet's revenue came from search and advertising services, with a significant portion of mobile search volume originating from Apple devices. Court documents and market analyses indicated several years ago that more than half of Google's search business was conducted via Apple devices, and that Google paid Apple between $15 billion and $20 billion annually to remain the default search engine in Safari. It was estimated that Apple thus received about one-third of the search advertising revenue generated by Google in Safari, while Google retained the rest.

With Gemini, the pattern is shifting: Instead of using Safari and classic search fields, more and more queries are being processed via AI interfaces, whether as a standalone app, integrated into Android, or later through Apple Intelligence/Siri collaborations. This has several economic consequences.

First, the direct revenue stream is expanding. The Gemini app on iOS and Android offers paid tiers (Gemini Advanced, often part of a Google One AI premium plan priced around $18 to $20 per month) that are billed through app stores. This shifts part of Google's monetization strategy from pure advertising revenue to subscription models with recurring income and greater predictability. iOS users with a high willingness to pay are a particularly attractive segment here.

Secondly, new indirect revenue opportunities arise through stronger integration with Google services. Gemini is closely linked to YouTube, Gmail, Docs, Maps, and other Google applications, which in turn generate advertising and cloud revenue. The more iPhone users conduct their information searches, creative work, and organization via Gemini, the more time they spend within Google's ecosystem—even on an Apple device. This amplifies network effects and data advantages that are crucial for the further development of the models and the personalization of advertising.

Thirdly, the balance of power vis-à-vis Apple is shifting. Until now, Google has paid substantial sums to remain the default search engine on Apple devices. Initial reports of a new AI agreement suggest that this relationship is partially reversing: Apple is reportedly paying Google for the use of Gemini as infrastructure for Apple Intelligence and Siri, thus mitigating the previous one-sided flow of payments. Even though the details and figures are not yet fully public, it is clear that this opens up a new revenue stream for Google in the B2B sector of model licensing, in addition to its search engine value creation.

Fourth, Samsung's deep integration strengthens Google Cloud's position. Samsung's use of Gemini Pro and Imagen 2 via Vertex AI for text- and image-based functions in its S24 devices results in high recurring cloud workloads. The more Samsung promotes and actually uses these features, the higher the resource consumption in Google's data centers—along with corresponding revenue from cloud services. In the context of a generative AI market that is more dominated by cloud deployments than on-premises solutions, this is a strategic advantage.

At the same time, risks exist. Generative answers can shorten traditional click paths via search ads, thereby cannibalizing traditional advertising formats. The more users remain directly within Gemini, the fewer page views, banner impressions, and traditional search ads are generated. Google is attempting to address this by tightly integrating Gemini and search and developing new ad formats that can be embedded in AI answers. However, monetizing the AI ​​layer is more complex and more susceptible to regulatory challenges because transparency and labeling of advertising become more difficult.

On the competitive front, Gemini's presence on iOS forces Google into an open platform mode. Instead of exclusively upgrading Android, Google is positioning itself as a cross-platform AI provider, present on both Apple and Samsung devices. Strategically, this is a safeguard: Even if Apple increasingly favors its own AI models in the future, Google already has a foothold in the ecosystem and can secure market share in the AI ​​sector through apps, services, and potential system integrations.

Economic effects for Apple: Between increased hardware value and loss of control in the service layer

For Apple, Gemini on iPhones and possible deeper integrations are ambivalent – ​​in the short term it increases the attractiveness of the devices, in the medium term it threatens an erosion of exclusive control over the service layer

On the positive side, the availability of a powerful Google Assistant on iPhones increases competitiveness against Android manufacturers, who have long promoted generative AI in their system interfaces. In particular, the close partnership between Samsung and Google around Galaxy AI and Gemini has strengthened the narrative of "Android as an AI platform." By now offering users both ChatGPT and, in the future, Gemini as options for AI features in iOS 18 and Apple Intelligence, Apple can address concerns about falling behind in the AI ​​race.

Economically, this has multiple impacts. Greater AI differentiation increases users' willingness to upgrade to new iPhone generations, particularly in the premium segment, where Apple already controls roughly two-thirds of global sales. This extends or stabilizes upgrade cycles and supports high average selling prices (ASPs). At the same time, attractive AI features strengthen Apple's position in emerging markets like India and Southeast Asia, where iOS is slowly gaining market share despite Android's dominance.

On the risk side is the gradual erosion of Apple's own service and search revenues. Apple already earns considerable sums from its cooperation with Google: Revenue from the search deal agreement amounted to around 20 billion US dollars in 2022 alone, representing a significant portion of Apple's service revenues. If, in the future, a growing number of users no longer conduct their information queries via Safari search but via Gemini, some of these queries will bypass Apple's share of search revenue. While Apple could negotiate new compensation mechanisms that take Gemini usage into account, its direct control is less than with browser defaults.

Added to this is the strategic question of whether Apple will ultimately relinquish a portion of the emerging AI market to third parties instead of developing its own models of comparable power. The decision to integrate ChatGPT and Gemini is interpreted in some industry analyses as an admission that Apple is lagging technologically behind in the area of ​​large, open foundation models and is focusing more on the role of an orchestrator. Economically, this shifts the value chain: Apple primarily monetizes through devices, platform fees, and its own services, while a growing share of the "intelligence" is attributable to the models of external providers.

At the same time, new lines of conflict are emerging. In recent years, Apple has positioned itself as the antithesis to ad-supported models through its focus on data privacy and restrictions on tracking, thereby particularly impacting the advertising revenue of Meta and Google on iOS. By now sourcing a large portion of its AI intelligence from Google, Apple is once again granting the advertising giant deep insights into user behavior on Apple devices – even though the companies emphasize their adherence to strict data privacy guidelines. From a regulatory perspective – especially in light of the EU Digital Markets Act and the AI ​​Act – this increases the risk that bundling and default settings will come under closer scrutiny.

Another dimension is the internal power balance between the hardware and services divisions. In recent years, Apple has expanded its service revenues as a second pillar alongside the iPhone, including the App Store, iCloud, Apple Music, Apple TV+, advertising, and other services. However, the more central, horizontal AI functionalities are provided by Google or OpenAI, the more difficult it will become for Apple to monetize this layer exclusively. On the other hand, Apple could, in the long term, strengthen its own models in niche areas (on-device models for privacy scenarios, specific media processing, health features) and position third-party models more as complementary.

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Economic effects for Samsung: Between first-mover advantage and fast imitators

Samsung was the first major manufacturer in the Android camp to deeply integrate Gemini into its premium smartphones

The Galaxy S24 devices were explicitly positioned as AI smartphones, with features such as real-time translation, context-based text suggestions, and generative photo editing. With this, Samsung aimed to demonstrate its technological leadership not only against Apple, but also against other Android manufacturers like Xiaomi, Oppo, and Vivo.

This first-mover advantage has three key economic effects. First, it justifies higher sales prices and strengthens margins in the premium segment. In a market where hardware improvements such as cameras or displays are becoming increasingly similar, AI features offer a new layer of differentiation that can be marketed to paying customers. Second, the close cooperation with Google Cloud and Vertex AI strengthens Samsung's position as a reference customer for Google's enterprise AI offerings, which in turn leads to joint marketing effects and potential improvements in terms and conditions.

Third, the integration of Gemini Nano is driving demand for advanced SoCs with powerful NPUs and increased memory capacity. Studies of the mobile AI market show that NPUs in smartphones are growing at annual rates exceeding 30 percent, fueling demand for high-performance, energy-efficient chips. For Samsung, as both a device and chip manufacturer (Exynos), this presents a dual opportunity: increased sales in the premium device segment and a strategically important role in the on-device AI supply chain.

With Gemini's move to iPhones, Samsung loses some of its competitive edge. If iPhone users can access a Gemini assistant with a similar level of performance to Galaxy buyers, part of the unique selling point of the "AI smartphone" disappears, at least from the perspective of end users who are primarily interested in the assistant experience and less so in the implementation method (cloud vs. on-device). While Samsung remains differentiated with on-device features, deep integration into system apps, and its own Galaxy AI, the "Gemini" buzzword loses its power as an exclusive marketing tool.

Economically, this intensifies direct competition with Apple in the premium segment. While Apple continues to expand its dominance in the value creation of the premium segment, Samsung must compete even more strongly on the basis of price-performance ratios, foldable devices, and regional strengths (for example, in parts of Asia and Europe). The integration of Gemini is shifting from an exclusive bonus to a basic requirement, which other Android manufacturers also offer via app (and, in the medium term, more likely through system integration).

Furthermore, Google's historical search and advertising deals with Apple were significantly larger in absolute terms than those with Samsung. Investigations by competition authorities have already shown that the search revenue shares paid to Apple in some countries were many times higher than those paid to Samsung. Should similar patterns emerge with AI integrations—such as higher volume-based payments or more favorable model access conditions for Apple—Samsung could, despite its technological proximity to Google, be relegated to second place economically.

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Regional differences: Europe, USA, Asia and the role of regulation

The economic effects of Gemini on smartphones vary greatly from region to region, mainly due to regulation, infrastructure, and platform distribution

In Europe, access to Gemini was initially limited. The web app was available earlier, but the mobile apps—especially on iOS—experienced delays and functional limitations due to data privacy and regulatory concerns. From mid-2024, the Gemini app was gradually rolled out in Europe, initially via the Google app, and later with a standalone iOS app. However, this version featured some regionally limited functionality and more restrictive access to the free API. Simultaneously, regulatory pressure is increasing due to the AI ​​Act and the Digital Markets Act, which are forcing both Apple and Google to be more transparent, minimize data collection, and be more open in their default settings.

Economically, this slows down short-term monetization in Europe, but at the same time shifts the focus more strongly towards on-device AI. Since the AI ​​Act sets strict requirements for high-risk and general-purpose AI, architectures that perform more processing locally on the device benefit, reducing data flows to the cloud and lowering latency. This particularly benefits manufacturers like Samsung, which emphasizes Gemini Nano and other on-device capabilities, as well as chip producers that supply NPUs and specialized AI hardware.

In the US and much of Asia, regulatory pressure is lower, but the willingness to pay and the infrastructure for premium AI services are high. The market for AI subscriptions, AI-powered productivity tools, and integrated assistants will grow fastest there. Apple already dominates in the US in terms of unit sales, while Android clearly prevails in many Asian markets (except Japan and some urban centers). The availability of Gemini on both platforms allows Google to address both the affluent iOS and the broad Android user base in these regions.

In China, Google is largely blocked, so Gemini plays no significant role there. This means that the Chinese ecosystems (Baidu, Alibaba, Tencent, Huawei) are developing their own AI models and smartphone integrations without being directly influenced by Gemini. However, the global AI race does indirectly affect China, for example through chip demand, semiconductor shortages, and export controls.

In emerging markets like India, Indonesia, and parts of Africa, where Android devices—many of them in the lower and middle price segments—dominate, Gemini will initially appear more as cloud-based assistants via apps than as deeply integrated on-device AI. Hardware costs and income levels limit the adoption of high-priced AI smartphones in these regions. Nevertheless, AI capabilities for education, financial services, and government will gain significant social and economic importance, particularly in these markets. The fact that Gemini is available on both entry-level Android devices and premium iPhones increases its potential impact, provided the services are adapted locally and made available in multiple languages.

Cross-industry impact: Who benefits beyond the platform giants?

The use of Gemini on iPhones and Samsung devices affects far more than just manufacturers and Google. Numerous industries along the value chain are directly or indirectly impacted

In the chip and semiconductor sector, the demand for on-device AI is increasing the importance of NPUs, high-bandwidth memory, and advanced manufacturing processes below 5 nanometers. Market studies estimate that the market for on-device generative AI smartphones reached nearly 200 million units in 2024 and could grow to over 400 million units in 2025, accounting for more than 50 percent of all smartphones by 2027. Premium chips already accounted for around three-quarters of revenue in the smartphone SoC market by the mid-2020s, even though their unit share was significantly lower. Foundries like TSMC, chip designers like Qualcomm, MediaTek, Apple (for its own SoCs), and Samsung itself benefited from this.

The cloud and data center industry is benefiting from the growing adoption of large-scale models like Gemini Pro and Ultra, which require enormous computing power in the cloud. The generative AI market is still predominantly cloud-based, with cloud deployments accounting for the lion's share of revenue. Every additional active Gemini user on an iPhone or Samsung device translates into additional requests to Google's data centers. However, in the long term, there is a risk of some workloads shifting to edge and on-device systems, which will temper the growth rates of traditional hyperscalers and bring hybrid architectures to the forefront.

In the advertising and marketing sector, the AI ​​layer is changing how users are reached. Instead of banners and traditional search ads, context-based recommendations are emerging in AI responses. Advertisers must prepare for a significant portion of customer inquiries to be received via Gemini-like assistants in the future. For Google, this opens up new advertising inventory opportunities, but also new regulatory risks, as the line between recommendations and advertising becomes even more blurred. Publishers and e-commerce providers risk losing visibility if users remain within the AI ​​interface instead of clicking through to websites.

The app market is also being reshaped by Gemini. On the one hand, new categories of AI-centric applications are emerging that use Gemini as a backend, for example, for text generation, summaries, translations, or analysis. On the other hand, horizontal AI assistants could devalue many previously specialized apps, such as note-taking apps, simple translators, or to-do lists, if these functions are integrated directly into Gemini or system apps. Since iOS users, on average, spend significantly more in the App Store than Android users, the economic relevance of this shift is substantial. Apple itself faces the question of to what extent it integrates AI functions into its own apps or allows AI providers like Google room to partially replace the app economy.

For companies and industries beyond the tech sector, Gemini's availability on both dominant platforms opens up the opportunity to massively automate mobile workflows: field service, maintenance, logistics, healthcare, financial consulting, and education can bring AI-powered assistants directly to employee or customer smartphones. The market for intelligent virtual assistants, already projected to reach tens of billions of dollars by the mid-2020s and expected to grow significantly into the 2030s, will be further driven by the standardization of AI on end devices. Gemini serves as a universal layer upon which industry-specific solutions can be built.

Strategic scenarios: How the balance of power could shift in the coming years

With Gemini on iPhones and Samsung devices, several plausible development paths open up for the next five to ten years

In one scenario, Gemini establishes itself as the de facto standard for AI interaction on smartphones, much like Google Search did previously on the web. While Apple offers its own models and integrations, user preference and model quality tip in Gemini's favor, especially if Google continuously invests in new model variations and features. Google would thus extend its dominance from search into the AI ​​realm, this time across platforms and with a stronger mix of subscription and cloud components.

In a second scenario, the market remains fragmented. Apple establishes Apple Intelligence and its own on-device models as the standard, supplemented by optional models like ChatGPT and Gemini for specific tasks. Android remains diverse, with Pixel-exclusive features, Samsung Galaxy AI, and other manufacturers integrating their own models or third-party solutions. Generative AI would then develop more like today's app ecosystem, with several significant players rather than centering around a single dominant assistant. Economically, in this case, Apple, Google, and other providers would each have significant, but limited, power.

A third scenario is shaped by regulation. If antitrust authorities and data protection authorities restrict bundling agreements like "Gemini as the default AI on Apple devices" or exclusive search and AI deals, this could lead to pressure for choice, interoperability, and restrictions on data merging. Users would then have to explicitly choose between multiple AI providers when setting up new smartphones, and default settings would be much more strictly regulated. In this environment, the economic advantage of individual deals could diminish, while the overall size of the AI ​​market would continue to grow due to trust and competition.

Regardless of the scenario, it is clear that the availability of Gemini on both Samsung devices and iPhones has opened a structural path: Smartphone operating systems are becoming carriers and orchestrators of AI models, some of which originate from the platform operators themselves (Apple, Google), and some from third-party providers (OpenAI, Anthropic, local champions). Economic value creation is shifting from pure hardware and traditional app ecosystems to subscriptions, cloud resources, and AI inference, supplemented by significant investments in semiconductors and networks.

For Google, opening up to iOS is a necessary step to avoid remaining solely in an Android niche and to cushion the anticipated decline in traditional search revenue. For Apple, integrating Gemini is both an opportunity and a risk: it protects the value of the iPhone franchise but, in the long run, threatens to outsource a piece of its intelligence layer. Samsung, in turn, benefits in the short term from the AI ​​boost in the premium market but must accept that the Gemini brand will not remain exclusive and that competition in the high-end segment will intensify.

In summary, the data and trends suggest that the deployment of Google Gemini on iPhones – following its already implemented and further expanded integration on Samsung smartphones – is not just another feature in the race for headlines, but a catalyst for a realignment of value creation in the smartphone and mobile AI ecosystem. Whoever gains control over the AI ​​layer, or at least maintains a presence, will significantly determine how revenues, margins, and innovation dynamics are distributed across hardware, cloud, advertising, and services in the coming years.

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