Enterprises want AI PCs, just not yet


While the employee benefits of the AI PC are intriguing, they may not be enough to convince IT buyers to go all in just yet, according to a Forrester report.

Despite the enthusiasm generated by PC vendors and chipmakers at the 2024 Consumer Electronics Show, where advanced AI-driven functionalities were prominently featured, enterprises are expected to adopt a more measured approach over the next year, Forrester said in the report.

The Promise of AI PCs

AI PCs are designed to enhance enterprise users’ productivity, cost efficiency, and security. By processing sophisticated AI applications locally, these PCs reduce reliance on costly and often slower cloud services. This could be especially beneficial in sectors such as finance and healthcare, where operations heavily depend on data processing and where data privacy and security are of the utmost importance.

The ability to process data locally on an AI PC minimizes the risk of breaches and helps enterprises comply with stringent regulatory requirements.

Challenges in adoption

Despite the benefits, the adoption of AI PCs among enterprises is fraught with challenges. “CIOs face several barriers when considering AI-powered PCs, including the high costs, difficulty in demonstrating how user benefits translate into business outcomes, and the availability of AI chips and device compatibility issues,” said Andrew Hewitt, Principal Analyst at Forrester Research.

CIOs feel they are struggling to show a return on investment in AI PCs. Limited business use cases for enterprises make it challenging to justify the use of these powerful machines, which are mostly restricted to niches like “gaming or content creation,” said Abhishek Gupta, Dish TV’s CIO.

“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, 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.

The next 18 months are crucial for AI PCs, according to’s Sabharwal. “Instead of just purchasing hardware, shifting the focus towards utilizing AI to address industry-specific challenges is essential. For instance, Small LLMs can be trained to operate efficiently on AI PCs. Startups, particularly cloud-native ones, are the pioneers in adopting this technology. “As chip technology progresses and costs decrease, we anticipate a tipping point where investing in AI-based PCs will become justified.”

Upcoming chipsets with higher processing capabilities will drive further interest in AI PCs across data-intensive sectors such as manufacturing and high-tech, Hewitt said. “Industries that blend creative work with data science are prime candidates for early adoption,” he noted.

Impact on cloud services

As AI PC adoption potentially reduces reliance on cloud computing, cloud providers may have to adjust their pricing models. Hewitt suggests a likely shift towards a hybrid model where some processing will continue in the cloud while other tasks move to local AI PCs. This adjustment would balance cost concerns with enhanced security and privacy benefits.

Despite the potential and capabilities demonstrated by AI PCs, 2024 is shaping up to be a year of gradual exploration and tentative adoption by enterprises. As AI technology continues to evolve and more tailored applications become available, the pace of adoption is expected to accelerate, making AI PCs an integral part of enterprise technology ecosystems in the near future. This cautious but steady approach reflects the enterprise’s strategic planning in integrating cutting-edge technologies into its operations.

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