The AI Strategy of Apple: A Discussion

Apple appears uninterested when it comes to banking and capitalizing on the recent developments in artificial intelligence, unlike other tech companies. Some observers have even accused it of lagging or even falling behind its contemporaries. Take note that Google has been pursuing various research and development activities across the different fields of AI while Microsoft has used the AI models from OpenAI to develop and deploy generative AI products and applications to its consumer base. However, despite its apparent indifference, Apple has been using artificial intelligence across the different facets of its product strategy. This is discernible from its range of hardware and software products.

Understanding the AI Strategy of Apple: How Apple Has Integrated Artificial Intelligence in Its Business Strategy

An artificial intelligence strategy or an AI strategy is a blueprint that outlines how an organization can use artificial intelligence to complement or improve further its overall organizational strategy and meet its organizational goals and objectives. Developing and implementing an AI strategy can bring forth several advantages.

Nevertheless, to understand the AI strategy of Apple, specifically how it uses artificial intelligence to add value to its business, it is first important to underscore the fact that it is a technology company that operates as a fabless chipmaker, a consumer electronics company, a software developer, and a publisher or distributor of content.

Apple has been factoring in the practical applications of artificial intelligence across its various business interests. These applications translate into hardware capabilities and software features. The specific AI strategy of the company is embedded into its product strategy and its more specific hardware and software strategies.

Hardware Capabilities: Using AI in the Design of Components that Power Consumer Electronic Devices

The hardware portfolio of Apple includes both end-use consumer electronic devices and specific hardware components. Most of the components used in its products are outsourced from different suppliers and contract manufacturers. It is still important to note that it is heavily involved in the design of these components. Hardware design is an integral part of its product strategy. The company has been using different AI principles and technologies to design hardware components that power the most advanced features of its consumer electronic devices.

Below are examples demonstrating the AI strategy of Apple as it applies to hardware design and overall product strategy:

• Neural Engine: A prime demonstration of the AI strategy of Apple is the inclusion of an AI accelerator or a neural processing unit called the Neural Engine. This coprocessor is designed for accelerating AI operations and tasks was first introduced in 2017 as part of the Apple A11 Bionic system-on-a-chip. This AI accelerator is now a staple component of newer generations of A series and M series chips.

• Image Signal Processor: Mac and iPhone devices are also equipped with an image signal processor integrated within their respective M series and A series SoCs. This coprocessor works with the Neural Engine to provide computational video for improved video editing and video rendering processes. This same coprocessor also powers the computational photography capabilities of the iPhone.

• Face ID System: The Face ID system found in iPhone and iPad Pro devices is a facial recognition technology and biometrics system that uses the Apple TrueDepth camera. This camera fires thousands of invisible lights to create a depth map of the face and also captures an infrared image. This is a basic application of computer vision. The system also tracks and learns facial changes over time.

• Spatial Audio Technology: Wearable audio products like the AirPods and Beats headphones have a feature called Spatial Audio that simulates surround sound. It is specifically a digital surround sound technology that uses motion sensors or dynamic head-tracking and audio processing to adjust the balance and frequency response of different sounds to create a sense of directionality.

• Apple Vision Pro: Apple has introduced its first mixed-reality headset called the Vision Pro. This device is packed with multiple sensors and a dedicated digital signal processor called the Apple R1 chip to merge the physical environment with the digital environment or power augmented reality and virtual reality features. The Vision Pro demonstrates advanced applications of computer vision.

Software Features: Using AI to Provide Value-Adding Software Functionalities and Improve User Experience

It is worth mentioning that the aforementioned hardware components and systems or technologies power some of the AI-enabled software applications and software-based services of Apple. The company is known for its incomparable and commendable hardware-software optimization that demonstrates the importance of ensuring seamlessness between hardware components and software applications. The same product strategy principle has been used in developing and deploying AI-based features and capabilities.

Below are some examples demonstrating the AI strategy of Apple as it applies to software development and feature integration:

• Siri: The introduction of Siri in 2011 suggests that the AI strategy of Apple has long been part of its product strategy. This digital assistant found in a range of Apple devices uses natural language processing or NLP based on a language model to answer questions, make recommendations, and perform certain actions. It also uses machine learning to adapt to its users and his or her preferences with continued use.

• Deep Fusion: Apple introduced Deep Fusion in 2019 as a new photography feature of the iPhone 11. It is specifically based on computational photography and is powered by the image signal processor and Neural Engine. The feature works by taking multiple pictures of the same scene and combining them at a per-pixel level. The process uses machine learning and computer vision principles.

• Adaptive Audio: The newer generations of the AirPods have a feature called Adaptive Audio that analyzes the sound around the user and adjusts it accordingly. This supports more specific features like lowering the volume of the music when the user starts talking to another person. This feature uses machine learning to understand the volume preference of a user and optimize his or her listening experience.

•  Recommendations: Services like the App Store, Apple Music, and Apple TV have a recommendation system that takes into consideration the preference of a user based on his or her browsing and consumption history and pattern of usage. The system learns from the user through machine learning. This helps in pushing relevant content and enabling a personalized user experience.

• Autocorrect: Apple announced in June 2023 that it now has an improved autocorrect feature for its iPhone devices. The specific autocorrect software is based on a transformer language model. This is the same AI model used in the GPT-4 and LLaMA models and the ChatGPT, Bing Chat, and Google Gemini chatbots.

Takeaways from the AI Strategy of Apple: A Product-Oriented Approach to Capitalizing on Artificial Intelligence

Understanding the aforementioned AI strategy of Apple or how it approaches the integration of AI requires an appreciation of its business model in comparison with other tech companies. Take note that Google is a service-oriented company that draws most of its revenues from its digital ad business. Microsoft is still predominantly a software company while Amazon has made significant revenues from its cloud computing services.

The aforementioned companies are more vocal about their respective AI strategies to reposition the value propositions of their businesses and specific productions in light of the recent development and practical applications of artificial intelligence. However, in comparison to its contemporaries, Apple is not only a tech company but also a lifestyle brand with a strong focus on end-user products and providing excellent user experience.

Nevertheless, based on the examples above, the company designs and uses hardware components for deploying specific AI functionalities. It also develops features that can be integrated in a particular app or the overall user interface that can perform computational tasks. Apple has integrated the practical applications of AI subfields like machine learning, natural language processing, and computer vision into its products.

It should not be a surprise that the company approaches AI with a product-oriented focus. It does not need to tell people what AI algorithms or AI models it uses nor does it need to promote a platform strategy through marketing. The AI strategy of Apple focuses on using related technologies to improve its consumer electronic devices, software applications and features of these applications, and the delivery of its digital services.