Canalys: Apple builds a competitive moat with shared services and a unified system architecture

According to the Zhitong Finance APP, Le Xuan Chiew, a research manager at Canalys (now merged into Omdia), stated: "WWDC 2025 is less about radical AI showcases and more about solid strategic refinement. Apple clearly positions trust, usability, and infrastructure as the core of 'Apple Intelligence'—favoring reliability over flashy gimmicks. This year's signal is clear: Apple is not in a hurry to chase market hype but is deeply cultivating its advantages in ecological depth and user trust." At WWDC 25, Apple unveiled the most comprehensive software design innovation in a decade and officially transitioned to a year-named operating system branding (such as iOS 26, iPadOS 26, etc.), while also launching multiple features to further consolidate its unique position among the three core forms of personal computing devices. Canalys believes that Apple is building a virtuous cycle—creating a competitive moat through shared services and a unified system architecture, which is an advantage that single AI functions find hard to match.

Apple has always viewed its platform and device ecosystem as a core strategic focus.

Apple's competitive advantage lies in its highly vertically integrated ecosystem and its status as the only company with significant market share across the three major terminal forms: smartphones, tablets, and computers—these three types of devices account for over 90% of global internet access and nearly half of users' daily screen interactions. Apple leads the industry in user interactivity across different devices. According to the latest consumer research from Canalys (now merged into Omdia), nearly half of iPhone users in developed markets also own an iPad, and one-third own a Mac. These cross-device touchpoints not only generate continuous revenue streams but also deepen ecological stickiness, forming a moat that is difficult for other OEM manufacturers to replicate.

At WWDC 25, Apple showcased its unique AI strategic direction, but this path is not without challenges. Due to quality issues, the launch of the enhanced Siri has been delayed, reflecting difficulties at the execution level. The AI features released this time are primarily based on machine learning, appearing more incremental compared to the generative AI innovations widely focused on in the current industry. Although this strategy aligns with Apple's "refinement first" product rhythm, the delay has raised questions: will this conservative strategy cause Apple to lose market attention in the critical area of defining the next generation of computing experiences?

WWDC 25 further emphasized that in the AI era, software (rather than hardware) will become the core driving force for platform differentiation and user value. The market demand for "Apple Intelligence" is already evident. Canalys (now merged into Omdia) data shows that for every 100 iPhones, there are 8.7 downloads of the ChatGPT application, while the Android platform has 5.0 downloads, indicating that iOS users are actively seeking capabilities more advanced than Apple's existing native AI Although the iPhone 16e performs well in mature markets such as Europe and Japan, its adoption in emerging markets is relatively lagging, mainly due to the regional restrictions of the "Apple Intelligence" feature. This phased rollout strategy not only weakens the market impact of Apple's latest hardware but may also suppress AI-driven upgrade growth—especially as users increasingly expect smart features to be "ready to use" out of the box.

Apple's AI strategy is close to user behavior but also faces the risk of missing key opportunities.

Apple's main competitors in the AI field are not individual companies but the entire Android and Windows ecosystems. While both platforms have seen significant growth in AI interest and applications, these changes have not yet truly translated into drivers for device purchasing behavior. Recent survey results reveal a clear discrepancy: although consumers generally indicate that AI features will influence their next device purchase, when asked about specific scenarios—such as "Would you be willing to pay a higher price for a laptop with AI photo editing or note summarization features?" or "Would you switch phone brands because of AI features like Circle to Search or Magic Eraser?"—their willingness to buy drops significantly compared to other traditional decision factors.

This gap between stated intentions and actual behavior indicates that AI's influence on purchasing decisions is still far lower than core factors such as brand loyalty, ecosystem integration, and device replacement cycles. Additionally, since most users' AI experiences are still cloud-based, they often struggle to understand what "AI devices" truly mean, making the value proposition of "edge AI" still relatively abstract in public perception, thus weakening its appeal as a differentiating selling point.

Regional differences also highlight a major challenge for Apple: in China, consumers rank AI features as the third most important factor in purchasing decisions, while in the U.S., it ranks only ninth. However, due to regulatory restrictions, Apple Intelligence has not yet launched in China. This leaves a gap in a market with a large number of AI-capable iPhone users, prompting users to turn to third-party applications (such as Doubao) to meet their AI needs. Meanwhile, local manufacturers like Xiaomi and Huawei are accelerating the integration of AI features, more accurately responding to consumer expectations. This not only represents a significant loss of market opportunity but also a strategic risk—Apple is unable to leverage AI as a competitive advantage in one of the markets with the highest global acceptance of AI.

The popularization of Apple Intelligence or outsourcing innovation?

Apple's decision to open access to its device-side foundational models for developers marks a strategic choice for its AI strategy towards "platform empowerment" rather than "feature competition." This approach helps Apple avoid the risk of "over-promising on AI features with mediocre results" and instead drives innovation through its ecosystem Currently, Apple has 34 million registered developers and 1.8 million App Store applications, providing a solid foundation for building its AI ecosystem. Behind this strategy is a keen insight into user demand: the annual download volume of AI-related applications worldwide has doubled year-on-year, surpassing 1 billion, and users' expectations for native AI functionality integrated into devices are increasingly strong.

Apple has significantly lowered the development threshold and time to market for cross-platform AI applications by enhancing developer tools (such as AI-driven code generation). At the same time, a unified design language across all platforms has simplified the application expansion process. Apple is building a virtuous cycle—forming a competitive moat with shared services and a unified system architecture, which is an advantage that single AI functionalities find hard to match. The core idea behind this strategy is that truly sustainable AI differentiation will come from a high-quality third-party ecosystem, rather than native AI functionalities that are difficult for consumers to understand or evaluate.

However, execution risks are also significant. Entrusting the AI experience to third parties means that Apple will face enormous challenges in quality control—while Apple's foundation is a consistently smooth and refined experience. At the same time, the adoption rate among developers is also a major variable: if developers prefer to build cross-platform solutions rather than using Apple's exclusive AI APIs, the entire strategy may fail . Therefore, Apple's success depends on whether its developer ecosystem can create an attractive AI experience while maintaining experience standards and stand out in competition with cloud AI service providers—who often have more powerful model capabilities and faster iteration rhythms.