Integrated AI: Why PC and smartphone manufacturers are turning away

  • Runar Björhofde, economic analyst for technology company Canalysys, analyzes the issues behind the rise of computers and smartphones equipped with built-in artificial intelligence.
  • AI will be used differently in smartphones and computers. He emphasizes that features on computers are mainly intended to provide productivity gains, for example for developers.
  • The huge investments made by companies like Intel or Qualcomm in AI chips illustrate this enthusiasm. However, it is necessary to take appropriate data protection measures.

Share of AI computers in 2027


According to analysis firm Canalysys, computers equipped with artificial intelligence will be widespread by 2025. In 2027, 60% of computers sold will have built-in artificial intelligence. Estimate shared by IDC.

We are seeing more and more advertisements for so-called “ Amnesty International “.Do they promise real changes for consumers?

Things are different for smartphones and computers. Most new features introduced on smartphones focus more on marketing and the experience offered than on the real benefit to users. For example, automatic suggestions in messaging apps or virtual assistants may seem impressive, but they are often viewed as scams. However, AI has huge potential, and I am sure companies will develop more and more features in line with user needs.

Developers will be able to work with language models built directly into their computers.

For computers, do you think things are different?

On computers, AI integration aims to improve users' efficiency in their work. Unlike smartphones, which are often used for light or entertainment tasks, computers are associated with productivity, such as document creation, data processing, and of course, software development. For example, developers will be able to work with language models built directly into their computers. The same applies to multimedia content creators. In this context, AI can play a crucial role by automating some repetitive tasks, providing contextual suggestions, and enabling more intuitive interaction with the computer. For example, technologies like Copilot can help users navigate through large amounts of data more efficiently by making intelligent suggestions and anticipating their needs.

We already have access to AI tools from personal computers in the cloud. Why integrate the power of AI directly into user devices?

Issues related to data privacy and cybersecurity are of increasing concern, especially in Europe where data protection regulations are particularly stringent. For companies looking to leverage AI while adhering to these regulations, it is essential to put strong data protection measures in place and ensure that any personal or other data is handled responsibly and securely. This may include using AI solutions locally or on the device itself, rather than relying on cloud services.

What should we understand about huge investments in AI from companies like Intel or Qualcomm?

The huge investments made by companies such as Intel, Mediatek or Qualcomm show the extent to which manufacturers or , working in this field. These companies are shaping the future of endpoint AI by developing cutting-edge technologies and providing high-quality hardware and software solutions to device manufacturers. For example, they can design specialized chips capable of handling intensive AI workloads, or develop software frameworks that enable developers to create innovative AI applications. The implications for consumers are significant, because it means that future devices will be more powerful and smarter. They will be able to meet more energy-hungry needs.

Canalys AI PC curve

The expected development of the adoption of computers with integrated artificial intelligence

To you, AI is just a technology and not a product. How do you see its development in electronic devices? What are the conditions for consumers to benefit from it?

The future development of AI in devices is promising, but there are still many challenges to overcome for its widespread adoption, especially in Europe. First, there are technical challenges to overcome, such as improving AI algorithms to work efficiently and reliably on resource-constrained devices, as well as managing power, memory, and bandwidth. In addition, there are regulatory and ethical challenges to consider, particularly with regard to protecting privacy, transparency and accountability in AI systems, as well as combating bias and discrimination. In Europe, where data protection regulations are stringent, companies must comply and take proactive steps to ensure their AI systems meet the highest ethical standards.

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Samantha Arnold

<p class="sign">"Web fanatic. Travel scholar. Certified music evangelist. Coffee expert. Unapologetic internet guru. Beer nerd."</p>

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