AI smartphone development by Apple, Samsung, Google & Co.: The reinvention of the pocket computer through artificial intelligence

From servant to decision-maker: How AI is disrupting the business model of tech giants

We are not facing the next routine hardware upgrade, but a tectonic shift in the global technology industry. For over a decade, the smartphone has been our primary window to the world – a passive tool defined by apps and touch input. But that era is drawing to a close.

The integration of generative artificial intelligence directly on the end device (on-device AI) transforms the once-powered pocket computer into an autonomous agent that no longer simply executes commands but anticipates needs and independently handles complex transactions. This development marks the transition from "smart phone" to "intelligent machine" and forces industry leaders like Apple and Samsung to radically reinvent their business models.

This article analyzes the economic logic behind this disruption: from the rise of specialized NPU chips designed to make data centers obsolete, to the threat posed to the traditional app economy by the new "agentic commerce," and the geopolitical tensions reshaping supply chains between Asia and the West. Learn why we must say goodbye to the free app culture and why the smartphone as we knew it is already history.

Suitable for:

• Comprehensive Smartphone AI Study: The Reinvention of the Pocket Computer with AI in the USA, Europe, Asia and Latin America

The end of the smartphone as we knew it, marking the beginning of an autonomous hardware era

The global mobile device market is facing not just evolutionary improvement, but a structural disruption that is shaking the economic fabric of the entire technology industry. While the past decade has been characterized by increasing market saturation and hardware commodification, generative artificial intelligence now acts as the crucial lever to transform the smartphone from a passive communication tool into an autonomous agent. This analysis examines the profound economic shifts triggered by the integration of on-device AI and highlights regional differences in adoption as well as the technological hurdles that will define the coming decade.

Global market dynamics and the premiumization cycle

The global smartphone market experienced moderate growth of approximately 2 to 3.3 percent in 2025, representing an important sign of recovery after years of stagnation. However, this growth was not evenly distributed across all segments, but rather heavily concentrated in the premium segment. Manufacturers like Apple and Samsung recognized that AI capabilities are the primary driver of upgrades in a market where physical hardware innovation appears to have peaked. Apple achieved a market share of 20 percent in 2025, recording the highest growth among the top five brands at 10 percent. Samsung followed with a share of 19 percent, although its growth was somewhat more moderate at 5 percent.

Interestingly, this growth is less attributable to an overall increase in the number of units sold and more to a targeted strategy of value creation through premiumization. Consumers in developed markets, but increasingly also in emerging markets, are increasingly opting for high-end models that possess the necessary computing power for local AI applications. This is reflected in the forecast that the total market will reach a volume of US$579 billion by 2026, even though unit sales are expected to remain virtually unchanged.

Despite the positive momentum in 2025, 2026 will be marked by significant supply chain challenges. A critical factor is the massive price increase for memory components. As chip manufacturers prioritize reserving their capacity for AI data centers, bottlenecks are emerging in mobile DRAM and NAND flash. Estimates suggest that prices for LPDDR5 DRAM will rise by approximately 70 percent and for NAND flash by up to 100 percent. This development could increase the manufacturing costs of an average premium smartphone by 5 to 7 percent, forcing manufacturers to choose between sacrificing their margins or drastically raising prices for end consumers.

The architecture of intelligence as an economic competitive advantage

At the heart of this new era is the neural processing unit (NPU), a specialized computing unit optimized for the demands of neural networks. While GPUs have long borne the brunt of AI calculations, NPUs offer significantly higher efficiency with lower power consumption. A dedicated NPU in a modern smartphone consumes considerably less energy than a conventional GPU for similar matrix-vector multiplications, which is crucial in a mobile environment with limited battery capacity.

The economic logic behind on-device AI is compelling: By shifting the computing load from the cloud to the end device, companies can save immense infrastructure costs. Global AI data center costs are estimated to rise to over $76 billion by 2028. However, if just 20 percent of workloads were processed locally on devices, these costs could be reduced by approximately $15 billion. This economic leverage explains why chip manufacturers like Qualcomm, MediaTek, and Apple are investing billions in developing more powerful NPUs.

Beyond pure cost savings, on-device AI enables new forms of personalization. A system that learns locally can better understand the user's context without sensitive data having to leave the device. This creates a relationship of trust, which is a significant competitive advantage in an era of increasing privacy concerns. We are witnessing the transition from reactive AI, which merely responds to requests, to proactive AI, which anticipates needs and prepares actions.

New monetization strategies and the rise of agent-based trading

The integration of AI is forcing manufacturers to fundamentally rethink their business models. Traditional hardware sales are no longer sufficient to cover the massive research and development costs. Three primary revenue streams are emerging: hardware rewards, subscriptions, and agent-based sales.

Hardware incentives are the most obvious approach. In the Chinese market, for example, the share of the premium segment above $600 rose from 11 percent in 2018 to 28 percent in 2024. AI serves as justification for higher prices here. However, this effect is often a one-off. Recurring revenue from AI-as-a-Service models is more interesting in the long term. Samsung is already testing a strategy in which AI features remain free until the end of 2025, after which it will likely transition to a tiered subscription model. A basic tier could remain free locally, while a Pro tier, costing $10 to $15 per month, would offer cloud-intensive features such as complex logical reasoning.

The most radical economic shift, however, is driven by agent-based commerce. When AI agents are able to independently execute transactions such as booking travel or making purchases, value creation shifts from the app interface to the transaction level. A provider could charge commissions of 2 to 5 percent of the purchase value or fees for favoring certain merchants in the agent's recommendations. This poses a direct threat to the traditional 30 percent commissions charged by app stores, as users are less likely to open individual apps and instead interact directly with the system agent.

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North America: The maturity level of mass AI acceptance

In the United States, a market is emerging that no longer views AI capabilities merely as a gimmick, but as an integral part of everyday digital life. According to a Deloitte study, 53 percent of surveyed consumers already use generative AI tools, a significant increase from 38 percent the previous year. Remarkably, users are highly satisfied: 42 percent of regular users report that the technology has a very positive impact on their lives.

The US market continues to be dominated by a strong Apple-Samsung duopoly, with the two brands together holding approximately 85 percent market share. Nevertheless, Google has been able to gain ground with the Pixel 9 series and a clear focus on AI differentiation. Demand in the US is primarily driven by the need for increased productivity. Features such as summarizing information, writing emails, and intelligent image editing are the most frequently used applications.

A critical factor for the US market remains the education level of end users. While the hardware is already AI-capable, the actual use of specific AI functions is often still limited, indicating a gap between technical availability and practical application. Manufacturers are responding with aggressive marketing campaigns that emphasize the immediate benefits in daily life. At the same time, there is a growing desire in the US for a balance between technological dependence and digital well-being, as many users try to reduce their screen time despite more powerful devices.

Europe: Regulation as a strategic area of ​​tension

Economically, Europe presents itself as a market of contrasts. On the one hand, there is a strong interest in technological innovations; on the other, regulatory uncertainties are slowing the rapid introduction of new features. A prominent example is the delay of Apple Intelligence in the European Union. Apple justifies this with the requirements of the Digital Markets Act, which could force the company to compromise the security of its products in order to ensure interoperability with third-party providers.

This regulatory hurdle means that European consumers will have delayed access to features like iPhone mirroring or advanced voice assistants. Critics warn that this could widen the technological gap between Europe and the rest of the world. At the same time, the EU AI Regulation is coming into force, banning unacceptably risky AI systems and imposing strict requirements on high-risk applications. While Google and Microsoft committed early to complying with these rules, companies like Apple and Meta are more skeptical of voluntary self-regulation.

Despite these hurdles, the European market remains lucrative. In 2025, the region recorded 4 percent growth in smartphone shipments, driven by improved macroeconomic conditions and strong demand for premium devices in markets such as Germany and the UK. European users are particularly focused on data privacy and transparency, which presents opportunities for manufacturers who can differentiate themselves through on-device AI and local data processing.

Asia: The epicenter of vertical integration

The most radical transformation is taking place in Asia, particularly in China and India. Chinese manufacturers like Xiaomi, vivo, and OPPO have evolved from mere hardware producers to providers of holistic ecosystems. The strategy of vertical integration is most advanced here. Xiaomi, for example, is investing over 200 billion yuan in AI, chips, and operating systems over the next five years to achieve complete independence in the value chain.

A distinctive feature of the Chinese market is the trend toward agent-based AI. Xiaomi's HyperOS and Huawei's HarmonyOS are designed to create a seamless connection between smartphones, cars, and smart home devices. An AI agent can not only answer questions but also manage complex tasks across various devices. The introduction of prototypes with integrated AI assistants, such as ByteDance's Doubao, demonstrates the extent to which the traditional app landscape in China is already changing.

India has established itself as a global hub for smartphone production. Driven by the government's production-related incentive system, manufacturing is projected to reach a value of US$75 billion by 2026. Apple, in particular, has massively expanded its manufacturing capacity in India, viewing the country not only as a sales market but also as a critical base for its global supply chain. An interesting local development is the Bhashini Initiative, which uses AI-based translations into 22 Indian languages ​​to bridge the digital divide in rural areas.

Latin America: Dynamics despite structural deficits

Latin America is showing remarkable momentum in the adoption of AI technologies. With a 14 percent share of global visits to AI solutions, the region significantly exceeds its actual digital weight. However, this adoption is primarily driven by the consumption of ready-made end-user solutions, while local development and research lag behind.

Structural gaps in investment and talent remain the biggest challenges. Although the region accounts for 6.6 percent of global GDP, it attracts only 1.12 percent of global AI investment. A digital divide is evident between pioneering countries like Chile, Brazil, and Uruguay, which score over 60 points in the Latin American AI Index, and the so-called explorers, whose ecosystems are still in their infancy.

Nevertheless, AI offers Latin America the opportunity to overcome productivity traps. In the mobile economy, its contribution to regional GDP is expected to reach US$680 billion by 2030. The key to success lies in democratizing access to education and healthcare services through AI-powered mobile applications, which could promote social inclusion.

The ecological dimension: The hidden price of intelligence

The environmental impact of the AI ​​revolution is ambivalent. On the one hand, AI data centers consume enormous amounts of electricity and water. Global energy demand for AI is projected to rise to 800 terawatt-hours by 2026, almost double the figure for 2022. A single query to a large language model can consume as much energy as charging a smartphone.

On the other hand, on-device AI can help to massively reduce this ecological footprint. Local processing eliminates energy-intensive data transmission via mobile and cloud networks. Studies show that inference on a modern smartphone can consume up to 95 percent less energy and 96 percent less water than a comparable request in the cloud. Furthermore, AI helps optimize the energy efficiency of the devices themselves by recognizing usage patterns and managing power consumption more intelligently.

Nevertheless, the production of the hardware itself remains a burden. The demand for rare earths and critical minerals often leads to environmentally damaging mining practices. Manufacturers are therefore required to increase the proportion of recycled materials – a trend already observed in approximately 40 percent of the models produced in 2025. Sustainability is thus becoming not only an ethical obligation but also a crucial economic competitive factor.

Suitable for:

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

Technological sovereignty and the reorganization of the global supply chain

The race for dominance in AI smartphones is inextricably linked to the geopolitical situation. The US has tightened its export controls on advanced semiconductor technologies to limit China's access to critical AI chips. This has accelerated China's efforts toward energy independence. China has already achieved ambitious goals and is massively expanding its semiconductor production capacity in older process nodes, which could further increase global dependence in certain segments.

At the same time, we are seeing a diversification of production locations. Countries like India, Vietnam, and Mexico are benefiting from the desire of global companies to reduce their dependence on China. The strategic importance of the semiconductor industry is underscored by billions of dollars invested in national support programs, such as the CHIPS Act in the US or similar initiatives in India and Europe. Technological sovereignty today no longer means just access to software, but control over the entire chain, from the design of the NPUs to the final assembly of the device.

The smartphone as the core of the autonomous digital economy

Economic analysis clearly shows that we are in a transitional phase. By the end of the decade, the smartphone will no longer be merely a device, but the central hub for a multitude of autonomous services. The shift towards on-device AI breaks the traditional dependency on the cloud and enables a new level of privacy and efficiency.

For established players like Apple and Samsung, this means the need to redefine themselves as platform operators for AI agents. Monetization will shift from hardware margins to transaction fees and service subscriptions. At the same time, this disruption offers opportunities for new competitors, particularly from China, who are putting pressure on the market through vertical integration and rapid innovation cycles.

The regional differences also illustrate that there is no one-size-fits-all solution. While the focus in the US and Europe is on productivity and regulation, Asia and Latin America are driving mobile integration into all areas of life. Success in the AI ​​era will depend on who can best reconcile the complex demands of computing power, energy efficiency, data privacy, and new business models. The smartphone is dead – long live the mobile AI agent.

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