“AI PCs are still very new with only a handful of options available across brands and at a premium price. The higher prices of AI PCs along with lack of enough use cases, is stopping CIOs from the adoption of AI PCs,” Gupta said.
“Businesses should look beyond impressive hardware specifications—they need genuine, measurable returns on investment,” said Ankush Sabharwal, CEO of CoRover.ai, a human-centric conversational and generative AI platform. “There is no denying that AI platforms are advancing rapidly, and this progress is paving the way for practical, problem-solving AI applications that go beyond mere gimmicks. We already have the necessary technology; the focus now should be on developing AI applications that are tailored for specific devices and industries rather than adopting generic, one-size-fits-all solutions.”
Intel also acknowledged the long road ahead for AI PCs. “AI’s integration into PCs has progressed quickly, yet we’re still exploring its full potential, especially in applications like generative AI for creating images or summaries from text,” said Akshay Kamath, director of the PC client category at Intel India.
Future projections and enterprise readiness
Enterprise readiness to adopt AI PCs often coincides with major OS updates to avoid compatibility issues. Forrester’s 2023 data shows that over half of infrastructure hardware technology decision-makers report that 50% or fewer of the company-issued PCs run on Windows 11. This suggests a broader hesitation towards rapid technological upgrades.
Windows 10’s anticipated end-of-life in October 2025 is expected to coincide with the increased adoption of AI PCs. “Enterprises will likely align their hardware upgrades with the new capabilities offered by the latest operating systems, which will be optimized for NPU technology,” Hewitt said.
Hewitt has predicted a tripling of AI platform budgets in 2024 to accommodate the burgeoning demand for AI applications. This budget expansion is anticipated to catalyze the adoption of AI PCs, especially as enterprise workloads continue to depend on cloud services, which are expected to become more costly. This presents a compelling case for the increased use of AI PCs in digital workplaces.
