It’s arguably too early to be confident about market share forecasts for AI PCs. Will they eventually become the standard PC, as smartphones now are the standard phones purchased by consumers? Or will AI PCs remain specialist tools, to a greater or lesser degree?
The issue is less “ability to use AI” and more the issue of the value of local processing.
One might liken the market prospects to that of consumer-grade or work-grade general-purpose PCs and “workstations” used by some, but not most.
High-end workstations are used for 3D rendering, video editing, and complex simulations. They prioritize raw local processing power, high-performance graphics cards and large memory capacities.
AI PCs will feature specialized hardware components like Tensor Processing Units or Neural Processing Units alongside traditional CPUs and GPUs to accelerate AI computations. But that does not necessarily speak to “why” such machines would add value over PCs not including those elements.
At least for the moment, forecasters see a gradual shift of buying patterns.
AI PCs might be useful for developers or users working on AI training, inference and other AI-dependent workloads. For most consumers, that might include image processing, speech-to-text, language translation or gaming.
Some professionals who are AI developers, researchers or data scientists might have work-related reasons that make AI PCs a good choice, if local processing adds value, compared to remote processing.
It is not clear how much of the video editing or 3D rendering market might be affected. “Professional” use cases might not be supported, but casual and user-generated content might be.
There arguably is more debate about the PC market than the smartphone market, though. AI already makes general sense for image processing on smartphones as well as speech-to-text. But additional use cases requiring on-board processing will have to be developed.
The argument for local AI processing on PCs is more complex. AI could personalize software functions, optimize battery usage, or enhance security measures. But it is not certain those tasks must be handled by on-board processors.
AI-specific hardware could significantly improve device performance for tasks such as photo and video editing, gaming, or augmented reality applications, to the extent those features are deemed useful on PCs.
Battery life might be a constraint for smartphones and laptops, though. And, for most users, additional AI device cost will have to be balanced against “new” and valued use cases. It will take some time for those use cases to develop.
At least in principle, one might envision a new category of AI PCs half way between workstations and general-purpose PCs. One might also envision an eventual migration of local AI processing to most PCs as a regular feature, at some point.
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