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AI PCs enable organisations to run AI workloads directly on devices alongside the cloud.
On-device AI improves performance, privacy and accessibility for employees.
Organisations should align AI PC adoption with business needs and employee use cases.
As organisations invest in AI, attention is turning to where AI workloads should run. A new generation of AI-enabled PCs is changing how businesses balance performance, privacy, cost and employee experience.
According to Datacom and Qualcomm Technologies' latest industry trend report, Inside the AI PC Revolution: How Advanced Chipsets Are Powering the Next Generation of Work, the PC is evolving from a traditional productivity device into an intelligent endpoint capable of running AI-powered experiences directly on the device.
The report highlights a broader shift taking place across enterprise technology. AI is increasingly being embedded into business applications, workflows and employee experiences, creating demand for devices that can support AI workloads efficiently while balancing performance, privacy and cost.
Gartner projects that 40% of enterprise applications will feature task-specific AI agents by the end of 2026, and workforce access to sanctioned AI tools has grown significantly over the past year.
Rather than replacing cloud AI, however, the report argues that organisations should think in terms of a hybrid AI model, running different workloads in different locations depending on business needs.
AI PCs are distinguished by the inclusion of dedicated neural processing units (NPUs), which allow certain AI tasks to be processed locally on the device. This creates new opportunities for organisations to run some AI-powered experiences closer to the user while complementing existing cloud investments.
"Transitioning to a hybrid AI architecture allows organisations to reserve expensive cloud resources for complex workloads while handling routine AI tasks at the edge," says Padrick Goodwin, Practice Lead for Emerging Technologies at Datacom.
"The result is a more efficient operating model that can improve performance while reducing the overall cost of AI adoption."
The report describes hybrid AI as an approach that combines cloud, edge and endpoint computing environments. Some workloads remain best suited to centralised cloud environments where organisations require access to large models and shared intelligence. Others benefit from running closer to the user, particularly where speed, privacy, offline access or reduced latency are important.
AI PCs play an important role in this model because they can process certain AI tasks directly on the device via a Neural Processing Unit (NPU), reducing the need to send every request to the cloud.
That capability has practical implications for employees. Features such as meeting summarisation, real-time translation, intelligent search, content assistance and audio enhancement can increasingly be performed locally, helping create faster and more responsive experiences. The report also points to benefits for employees working remotely or in locations where connectivity may be limited.
Amir Bukan, ANZ Commercial Channel Lead for PC with Snapdragon, believes the value extends well beyond the technology itself.
"The value of on-device AI isn't simply that workloads run locally. It's that employees get responsive AI experiences wherever they work, regardless of connectivity, without sacrificing performance or battery life."
One of the report's key findings is that AI PC adoption should not be approached as a blanket refresh programme.
Instead, organisations should identify where AI-enabled devices can deliver the most value based on employee roles, mobility requirements and workloads. The report highlights a range of use cases, from mobile executives and remote workers through to security-sensitive users, field teams and knowledge workers.
For example, field-based employees may benefit from offline AI assistance and local document analysis, while executives could gain value from AI-powered meeting support and real-time transcription. Security-sensitive roles may also benefit from keeping certain AI processing on-device rather than transmitting information externally.
"The most significant change isn't the hardware itself. It's the shift towards AI becoming part of the everyday employee experience, helping people access information, complete routine tasks, and work more effectively without constantly switching between tools," says Goodwin.
The report encourages organisations to view AI PCs as part of a broader AI readiness strategy rather than simply another hardware upgrade. As many organisations continue planning Windows 11 refresh programmes, there is an opportunity to consider how endpoint decisions support future AI adoption.
Importantly, the report challenges several common misconceptions, including the idea that AI PCs are only valuable for employees who use generative AI daily or that they are useful only when connected to the internet. The authors argue that benefits such as accessibility features, intelligent search, workflow automation and privacy-sensitive processing can deliver value across a wide range of employee groups.
For technology leaders, the next step is less about choosing between cloud and device AI and more about determining how the two work together.
As AI becomes embedded across more workplace tools and processes, organisations that align their device strategy with broader AI objectives will be better positioned to support the next generation of work. Datacom's recommendation is to start with business outcomes, identify high-value use cases, test with pilot groups and scale based on evidence and employee needs.
The result is a shift in thinking: from device refreshes driven primarily by lifecycle requirements to endpoint strategies designed to support an increasingly AI-enabled workforce.
The report explores:
Why AI PCs are becoming an important part of enterprise technology and AI readiness planning
How to balance cloud, edge and on-device AI by running the right workload in the right place
Common misconceptions about AI PC adoption and what technology leaders should consider instead
Practical workforce use cases for roles ranging from executives and knowledge workers to field teams and security-sensitive users
Key considerations for evaluating AI-ready devices and aligning them with employee needs and business priorities
A practical roadmap for building an endpoint strategy that supports the next generation of work.
What is an AI PC?
An AI PC is a device designed to support AI workloads more efficiently through dedicated processing capabilities, enabling some AI-powered tasks to run directly on the device rather than relying entirely on cloud services.
What are the benefits of running AI on a device?
On-device AI can help improve responsiveness, support offline use cases, reduce data movement and enable more personalised experiences for employees.
Do AI PCs replace cloud AI?
No. AI PCs are typically part of a broader hybrid AI strategy, where organisations run different workloads across cloud, edge and endpoint environments depending on performance, privacy and business requirements.
Who benefits most from AI PCs?
The greatest value is often seen in roles that rely on mobility, collaboration, security-sensitive workloads or AI-enhanced productivity tools, including executives, field staff, knowledge workers and remote employees.
As AI becomes embedded across everyday work, the right endpoint strategy is becoming just as important as the AI itself. AI PCs can help organisations balance performance, privacy, cost and employee experience by bringing AI capabilities closer to the user. To maximise this investment, organisations should look beyond the device and consider how hardware is deployed, managed, secured and supported throughout its lifecycle.Explore Datacom’s Hardware and Device Management services to see how a strategic approach to device lifecycle management can help your organisation build a more flexible, AI-ready workplace.
