As GenAI increasingly becomes mainstream, its applications in smartphones are fast becoming a key design vector for smartphone manufacturers.
IDC’s latest forecast estimates that GenAI smartphone shipments will grow 364% year-over-year in 2024, reaching 234.2 million units, growing to 912 million units in 2028 implying a compound annual growth rate (CAGR) of 78.4% for 2023-2028.
Over the past year, many market participants have announced their own set of artificial intelligence (AI) tools to demonstrate smartphone UX changes. These are based on various foundational models, large and small language models (LLM and SLM) enabling generative AI (GenAI) features with on-device processing, and multimodal input and output. The OEMs have a hybrid approach to enabling AI features-device-based for localized and cloud-based for heavy computational activities.
While many of these AI features are presently limited to premium smartphones, we should expect to see these trickle down the pecking order made possible by the use of cloud-based AI solutions as these devices will lack necessary hardware. However, a reduced scope and privacy/latency remain key considerations. Below are some of these features and how they are different across the OEMs.
OEMs are Adding Their Unique Flavor with AI Features
While the AI features fall within the same broad categories for all major platforms and devices, each OEM imprints their unique signature, along with the tools from the likes of Google and OpenAI.
Almost every key OEM has announced features/tools for photo/video editing, writing/editing, translation and interpretation, summarizing, search enhancement etc., targeting the most used smartphone features. To most users, it may not matter if AI is the enabler as long as they get a better outcome. Case in point, users are more interested in the final portrait photo than in the hardware, software, or AI driving it.
A big hit, according to the market participants, are Circle to Search, a Google AI feature tied to Android 14, mentioned by Samsung in their earnings in Apr 2024 as the most used feature and Eraser which OPPO claimed is used 15 times per day on average. Live translation is another extremely useful feature overcoming the barriers of language and can be used conveniently even in an offline mode. There is also increased focus on wellness, where Google, for example has Sleep and Snore detection, Samsung recently announced Sleep Apnea detection, and Apple has been talking about monitoring vitals.
AI Features – An Extension of Brand Message for the OEMs
While the end-use for GenAI features is driven by the same user needs, OEMs use AI features as an extension of their brand message and stand out from the others.
- Apple announced GenAI capabilities as “Apple Intelligence”, indicating AI is central and all under one hood on its devices, with features designed to have cross-functionality across various apps and iPad, iPhone, and Mac devices. It might not be a radically new way of how a user interacts with the iPhone, but enhancing the app functionalities and fun activities such as creating personalized memories, Genmojis and avatars. The revamped Siri with access to underlying user data (emails, messages, photos, locations, files etc.,) can be more context-aware, while sticking to its central message around privacy even as the user connects to ChatGPT. Apple’s vertically integrated approach relies largely on in-house language models and its private cloud infrastructure, while partnering with OpenAI for ChatGPT.
- Google continued with its legacy of using software to enhance smartphone capabilities. Pixel 8 Pro enabled many on-device GenAI features by running language models on the device. It has a host of features such as call management (Clear Calling, spam calls, Call Assistant); photo/video editing (Photo/Audio Eraser, Best Take); communication (Proof Read, Smart Reply, Summarize, Magic Compose) etc. For Google, it can be a blurry line between what is unique to Pixel smartphones vs the rest of the Android lineup. Google has been managing this by bringing some of the features to Pixel smartphones first before they go to the wider Android players.
- OPPO, in continuation of its focus on camera and photography features, has features such as AI Best Face, AI Eraser, AI Studio and AI Clear Face, while also expanding AI features to broader spectrum of AI applications for communication and productivity. OPPO also introduced Social Media Creation tools to assist in creating content specifically tailored for social media platforms.
- Samsung launched Galaxy AI tools on its flagship Galaxy S24 series and on Galaxy Z6 Foldables recently, and extended some of these features to its older models, focusing on communication and productivity. Live translation as well as real-time Interpreter are standout features. Galaxy AI includes Photo Assist, Instant Slow-Mo, AI summarization, Chat Assist and Magic compose writing/editing tools. Features such as dual-screen mode for Interpreter are customized for the foldable form factor.
- While other Android players have also announced AI tools – Xiaomi’s AI-generated subtitles for video calls and Image Editor, Honor’s eye-tracking AI functions, Motorola’s personalization and privacy-oriented features – partnership with Google remains vital to have access to the broader set of tools integrated with the Android operating system.
Another area of differentiation is the size and number of LLMs and the training material used which impact performance and UX. Apple uses its own language models, and OpenAI for tasks that are beyond its realm. Android players use Gemini models (Pro and Nano) and multiple other different-sized models. OPPO has its own SLM that uses 7 billion parameters as well as an LLM AndesGPT in addition to using Gemini. There are partnerships with other tech companies including Qualcomm, MediaTek, and Microsoft.
Further, there are differences in the execution of these features and their accessibility for third-party apps.
- iOS developers and apps have experience of automating tasks or working with features such as Siri Intents and Shortcuts. For example, developers and apps with SiriKit already integrated into their apps could see immediate enhancement with new Siri capabilities. Some of their AI tools such as writing tools would be easily available to developers for their third-party apps.
- Google also provides developers with APIs and SDKs to integrate Gemini AI into their apps. However, Google, OEMs and developers have to work with diverse hardware of multiple Android smartphones and ensuring adequate testing for seamless integration.
AI will be Central in Driving UX Across Smartphones
The opportunity and the challenge for OEMs is to deliver UX that matches the AI hype. Specifically, OEMs can leverage AI to get past user fatigue from the hardware features that have faced backlash as being boring. Just as we now use dictation, text prediction and photo editing, these new AI features will also become everyday tools on smartphones. In any event, below is a summary of key action items that OEMs will need to bring front and center as they embark on this next phase of evolution of smartphones.
- Overall, a more personalized, intuitive and user-friendly experience that doesn’t interrupt the normal workflow can create more stickiness. While iPhone users have high loyalty, it’s not the same for Android users who easily switch between brands. A radical shift such as opting for an app-less device is not yet for the masses, while a traditional interface with an app may be a bit outdated and inefficient for an evolved user. An in-between approach with a generative user interface could take the users on the AI track more gradually.
- Network connectivity will also play a key role to have a faster, smoother connection and a seamless experience for using AI features, especially if there is cloud processing. Together with faster processing on the device, Wi-Fi 6E/7 and 5G network connectivity will help in faster response with lower latency. This will also help with democratization of AI by enabling more smartphones with cloud-AI features.
- User privacy will remain central to these experiences, partly enabled by on-device AI but also reflected in a company’s philosophy to ensure user data remains private while also contextualizing it to provide more personal results. The side benefit of on-device AI is that by spreading out the processing to on-device AI across the installed base of devices, much less server CAPEX is required than would be if AI was only processed on servers.
- As these features go beyond the native apps and start to be integrated in the third-party apps, it will be imperative to work with the developers to bring AI features to more apps and ensuring easy ways for developers to integrate AI features into their apps.
OEMs are riding on the AI hype to develop and integrate the AI features in their smartphones and at the same time educating and convincing the users of the benefits of AI. Afterall, to drive more users to their brand, AI capabilities can have consequences beyond immediate upgrade to a new smartphone.
For a look at industry and segment spending forecasts for broader AI and GenAI use cases, read about IDC’s AI and GenAI Spending Guide.
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