Intel plans to ship 100 million AIPCs in the next two years

At the recent Intel Vision 2024 conference, Intel (Intel) proposed an ambitious plan to reinvigorate the personal computer (PC) market before the largest replacement of machines in decades.

Intel has gone through the process of transforming from a chip company to a one-stop system company. It is trying to let customers understand that only by making AI ubiquitous can it remain invincible in the competition. AI is fueling the largest PC refresh in decades, driven by unprecedented numbers and age of installed base, looming software obsolescence due to Windows 10 retirement, and challenges across client devices, edge infrastructure, and data With the rapid development of the center, enterprises have a growing demand for AI functions. These factors will trigger a wave of PC refreshes in the next 24 months - OEMs and chip giants are betting heavily on AI to stimulate consumers' sense of urgency to update their devices.

Ecosystem expansion and scale are Intel’s biggest advantages

In order to promote the application of its AI hardware, Intel launched the AI PC Acceleration Program, aiming to attract the participation of hundreds of independent software vendors (ISVs), hardware manufacturers and developers. The goal is to ensure strong software compatibility and optimized performance for the next generation of AI applications running on Intel processors.

The plan will bring more than 300 AI-centric features to market in 2024, which are mainly focused on collaboration and design/creative tools, but also include some professional tools such as improved mobile device management and threat detection. Intel's key advantage in this regard is scale. 80% of PCs currently in use have Intel chips. As a market maker, Intel is in a better position to collaborate with the ecosystem because these ISVs must prioritize optimized systems and are more likely to choose partners that hold the largest share of the PC installed base and have a history of being entrenched in the industry. Intel plans to ship more than 100 million Core Ultra chips within two years and sees the plan as a key driver.

While this will lead to a surge in AI workloads running locally on PCs, there are some limitations. Many features cater to mass-market needs, such as the benefits of AI for collaborative applications. However, initial adoption is focused more on niche markets of interest to budget holders concerned with total cost of ownership, security and manageability, rather than end users. Additionally, the productivity-focused software provider, namely Microsoft, is still developing its own on-device AI applications. Given that ordinary mental workers spend most of their time using Office 365 applications, once Microsoft integrates some new features on the client side, the adoption rate of AI PC will be greatly increased.

Intel's AI PC strategy comes after several years of declining market share in key markets. Since Apple began transitioning from Intel chips to self-developed chips in 2020, Intel has lost 6% of its market share in notebook shipments to enterprise customers. AMD and Qualcomm are also stepping up to compete with Intel in the commercial PC field. Despite fierce competition, Intel still has a strong influence. 80% of enterprise laptops use Intel chips. In other market segments, Intel's share has been relatively stable.

One-stop service makes AI ubiquitous

Intel's transformation from a pure chip manufacturer to an end-to-end systems company will have a significant impact not only on the PC market, but also on the broader ecosystem of enterprises, developers and consumers. Intel's AI PC strategy is driven by the belief that an open ecosystem and "small" custom language models will be key to enabling transformative AI experiences.

In addition to providing AI PCs, Intel also provides enterprises with local solutions for edge computing, namely AI nodes and clusters, and provides "super clusters" for data centers. At the heart of the product is Intel's new Gaudi3 AI accelerator, which will become a staple for building AI at scale.

In addition to creating cutting-edge hardware for AI applications, Intel has also developed Retrieval Augmented Generation (RAG) capabilities to allow companies to apply AI models on their own data. The combination of Intel's new edge platform and the Gaudi3 AI accelerator will provide a solid foundation for enterprises that want to leverage their own data and AI models in end-side devices or servers. Highlight unmet and clear customer needs

There is no doubt that Intel's vision for the future of PC is ambitious and forward-looking. By infusing AI capabilities into its hardware and software portfolio, it is committed to positioning PCs as important strategic assets for enterprises and helping them navigate the ever-changing computing environment.

At the heart of Intel's strategy is the assumption that every business leader wants to embed AI throughout their organization. Most companies, especially large enterprises, view AI as one of the most transformative technologies, so Intel's plans are pretty solid. However, there are some obstacles and potential after-sales pitfalls in the adoption process that must be addressed.

Great products should satisfy unmet and unspecified needs of customers. For now, the value that AI PCs might create is largely unclear to both customers and sellers. Customers don’t know what AI can do specifically and what quantifiable benefits deployment of AI can bring. So far, the PC industry as a whole has not been able to adequately answer these questions.

To truly take advantage of the upcoming PC refresh super cycle, manufacturers and their partners must do more than further demonstrate the performance and hardware capabilities of their AI PCs. Participants must be able to articulate a clear and compelling development direction that resonates with enterprises across various industries, and should be able to accurately depict how AI PC can actually drive business results, streamline work processes, and improve productivity and innovation benefits. At the same time, manufacturers also need to work on reducing the ownership cost of AI PCs, improving security and improving manageability.

Source from Canalys_China. Please indicate the source for authorized reproduction:

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