AI PC adoption moves from testing to workplace deployment, AMD report finds

Artificial intelligence-powered personal computers are moving beyond trials and into mainstream workplace use, according to new research from AMD. The report suggests organisations are increasingly treating AI-capable hardware as a practical business tool rather than an experimental technology.

More than four in five organisations surveyed said they are either planning, piloting or already deploying AI PCs in some capacity. This shift indicates that businesses are moving from testing isolated use cases to embedding artificial intelligence into daily operations. The transition is being driven by the need for hardware capable of running some AI workloads locally, without relying entirely on cloud-based systems.

AMD’s findings suggest that performance gains are already visible. Around 70 per cent of organisations reported faster performance and reduced latency when using dedicated AI PCs. At the same time, 59 per cent of respondents described high-performance neural processing units, or NPUs, as “critical” to their computing strategy.

Businesses move from experimentation to everyday use

The report highlights a turning point in how companies approach artificial intelligence in the workplace. Earlier phases focused heavily on experimentation, with limited pilot programmes designed to test the viability of AI tools. Now, however, organisations are shifting towards large-scale deployment, integrating AI capabilities into everyday business workflows.

This transition is closely linked to hardware capabilities. AI PCs are designed to process certain workloads directly on the device, reducing dependence on external servers. Running tasks locally can improve response times and reduce delays associated with cloud processing, particularly in environments where speed is essential. Businesses are increasingly recognising that the right hardware infrastructure is necessary to unlock the full potential of AI tools.

The growing importance of neural processing units is a central theme of the report. NPUs are specialised components designed to efficiently handle AI-related tasks, such as machine learning inference and data processing. Their increasing adoption suggests that businesses are prioritising systems designed specifically for artificial intelligence rather than relying solely on traditional central processing units.

The move towards everyday deployment also reflects a broader shift in corporate technology strategies. Instead of viewing artificial intelligence as an optional feature, organisations are beginning to treat it as a core capability. The report notes that this transition marks the point at which AI moves from a “nice-to-have” to a standard business requirement.

Knowledge workers lead demand for AI PCs

The report identifies knowledge workers as the primary drivers behind the growing use of AI PCs. Employees working with documents, presentations and data-heavy tasks are benefiting most from local AI capabilities. These systems help automate repetitive work, enabling staff to focus on higher-value tasks that require analysis or decision-making.

AI-powered features are widely used for creating and editing documents, preparing presentations and managing spreadsheets. Meeting transcription and automated summarisation have also become common use cases, helping teams save time by converting spoken discussions into written records and concise summaries. These tools are proving particularly valuable in organisations with frequent meetings or distributed teams.

Interestingly, coding assistance ranked lower among practical use cases than image and video generation. The report suggests that many developers still prefer cloud-based tools for coding tasks. These tools often offer large-scale processing power and access to continuously updated models, making them well-suited for software development workflows.

Visual content creation, however, appears to be gaining momentum within workplace environments. Image and video generation tools are being used to support marketing, communications and training materials. By handling these tasks locally, organisations can reduce the need to upload sensitive data to remote servers, offering an additional layer of privacy.

The adoption of AI PCs at scale is already underway. According to the findings, 27 per cent of organisations have deployed these systems widely across their operations. This suggests that businesses are moving beyond limited trials into long-term infrastructure planning, where AI-capable devices are included in standard hardware refresh cycles.

Hybrid AI computing set to shape the future workplace

While AI PCs are gaining popularity, the report makes clear that they are not expected to replace cloud-based artificial intelligence. Instead, the future is likely to involve a hybrid approach that combines local processing with remote computing resources. This balance allows organisations to benefit from both speed and scalability.

Local processing offers clear advantages in terms of responsiveness and data security. Tasks that require immediate results, such as real-time transcription or on-device data analysis, can be completed without delays due to network connectivity. In addition, sensitive information can remain on the device rather than being transmitted to external servers, reducing potential exposure to cyber threats.

Cloud-based systems, however, remain essential for handling large-scale workloads and complex data processing. These platforms provide the computing power needed for advanced model training and resource-intensive tasks. By combining local and cloud capabilities, businesses can distribute workloads efficiently and adapt to changing operational needs.

The report concludes that AI adoption is entering a new phase, characterised by widespread deployment and deeper integration into business operations. As organisations continue to invest in hardware and software infrastructure, AI PCs are expected to become an increasingly familiar presence in offices and remote work environments.

This emerging hybrid model also signals broader changes in workplace technology strategies. Businesses are recognising that effective artificial intelligence deployment requires not only powerful software but also the right combination of local and cloud hardware. As adoption continues to rise, AI PCs are likely to play a central role in shaping the next generation of digital workplaces.