Generative AI (GenAI) is emerging as a major trend in the tech industry, finding its way into the latest smartphones and PCs. However, on-device AI has been around for a few years now, and there is some confusion regarding the definition of a smartphone with AI and a GenAI smartphone.
In this latest episode of ‘The Counterpoint Podcast’, host Mohit Agrawal is joined by Tarun Pathak, Research Director at Counterpoint Research, to talk about GenAI smartphones. We discuss our definition of GenAI smartphones, potential impact on pricing and upgrade cycle, role of chipmakers, OEM strategies and our forecast. In this discussion, we also touch upon hardware requirements, ecosystem players that are driving GenAI experiences, regional differences and much more.
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You can read the podcast transcript here.
Key takeaways from the discussion
Counterpoint’s definition of GenAI smartphone
• We define a GenAI smartphone as a mobile device that leverages large-scale, pre-trained GenAI models to create original content or perform context-aware tasks.
• We expect such devices to have multimodal capabilities, allowing them to process text, image, voice and other inputs to generate a variety of output and enable a user experience that is fluid and seamless.
• We also expect the hardware specifications of such devices to evolve as the technology advances. But at present, a device should have hardware capabilities that are comparable to or exceed the performance of current flagship smartphones to effectively run GenAI models.
Hardware requirements
• A GenAI smartphone should have a processor built on the latest process node designed to undertake AI workloads, like Tensor Processing Units (TPUs) or Neural Processing Units (NPUs).
• It should also support faster hardware such as LPDDR5 RAM, UFS 3.1 storage, Wi-Fi 6E or 5G connectivity, and other advanced connectivity options.
GenAI smartphone vs phone with AI
• A GenAI smartphone can create original content and perform a wider range of tasks.
• A regular smartphone with AI focuses on automating tasks.
Impact of GenAI smartphones on pricing, upgrades
• It is uncertain if GenAI will impact the pricing of smartphones, but a slight increase is possible due to powerful hardware.
• OEMs can explore subscription models for advanced AI features.
• Widespread adoption of GenAI features could help drive upgrades.
• User experience, killer use cases, awareness and effective marketing will be key for consumer adoption.
Ecosystem players, regional differences
• Chipset makers like Qualcomm and MediaTek are doing a great job in creating awareness about the GenAI capabilities of chipsets.
• Smartphone maker Samsung has partnered with Google to bring Gemini LLM features to Galaxy devices.
• Xiaomi is developing its own MILM based on 13 billion parameters.
• OPPO has released its AndesGPT based on a 180-billion parameter model.
• User experiences may vary by region, as LLM developers will work on features catering to local users in different languages and dialects.
Counterpoint’s GenAI smartphone forecast
• Counterpoint Research believes GenAI smartphone share will reach 11% of the overall smartphone market in 2024, and 43% by 2027.
• This translates into roughly 550 million units by 2027. The installed base could surpass one billion by 2027.
• Starting now with premium smartphones, GenAI features, we believe, will diffuse to lower price tiers by 2026, especially the $300-$500 band.
Analyst takeaways
• Smartphones of the future will be more personalized to cater to individual needs and preferences, and AI will play a central role in driving these personalized experiences.
• As OEMs differentiate themselves on AI positioning, the key here will be the evolution of AI use cases. Currently, these use cases include enhanced imaging capabilities, translation features, improved app experiences, content recommendations, creating more personalized content, and more.
• These use cases will evolve as the large language models (LLMs) will continue to grow in both size and efficiency.
• Counterpoint believes that the integration of edge (mobile devices) and cloud will be the mainstream model for GenAI in smartphones, and OEMs with an equally strong play in software capabilities and supported by strategic industry partnerships are likely to stay ahead of the competition.
Podcast chapter markers
01:00 – Tarun defines how smartphones with AI features are different from GenAI smartphone.
05:19 – Tarun talks about LLMs and how Counterpoint is defining them with respect to GenAI experiences.
08:15 – How could hardware requirements for GenAI affect smartphone pricing? Tarun explains.
12:05 – Tarun weighs in on whether GenAI can drive smartphone upgrades and shorten replacement cycles.
15:50 – Apple is currently missing from the GenAI space, but what to look forward to with the upcoming WWDC developer conference.
18:14 – Tarun talks about the role of ecosystem players, from chipmakers to smartphone OEMs and developers, and what they are doing in the GenAI space.
22:35 – Can GenAI experiences differ from one region to another, to cater to local audience? Tarun weighs in on regional efforts.
24:30 – Tarun talks about Counterpoint’s forecast with respect to GenAI smartphones.
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