Dell Technologies expects 98% of the global PC market to be AI-enabled by 2028. The company is shifting AI workloads from the cloud to local hardware by embedding specialized neural processing units, aiming to lower data privacy risks and operational costs for corporate clients.
Dell Technologies is recalibrating its hardware strategy to position personal computers as a central hub for artificial intelligence. The company is moving away from a cloud-only model, pushing instead for a hybrid approach where AI agents run locally on the device. By processing data on the PC itself, Dell aims to improve data security and reduce the recurring costs associated with cloud-based AI queries.
To support this shift, Dell is integrating specialized neural processing units across its product range. This strategy relies on partnerships with major silicon manufacturers including Intel, AMD, and Qualcomm to ensure that AI capabilities are available across both consumer and commercial tiers. The company believes this will lower the total cost of ownership for businesses, as they can run complex models on hardware they already possess rather than relying solely on expensive external servers.
For large enterprises, this requires a shift in how hardware is chosen. As companies move from testing AI applications to full-scale deployment, selecting devices with the right performance levels becomes critical. Dell is focusing on the rise of desktop agentic AI, which requires consistent power and high-end graphics processing. These devices are designed to handle background processes, such as autonomous endpoint management and specialized research, without needing a constant cloud connection.
However, the strategy faces challenges. Corporate adoption remains varied, with small businesses often moving faster to adopt productivity tools than larger, more complex organizations that require deeper integration with existing workflows. The success of this hardware-centric AI model depends heavily on the maturity of the software ecosystem. If the software required to leverage these AI-capable chips does not develop as quickly as expected, the value of the new hardware may not be fully realized.
Investors may monitor how quickly corporate clients adopt these AI-ready systems and whether the anticipated demand translates into higher margins for the company. Additionally, the company's reliance on external chip suppliers means that any supply chain delays or technical issues with Intel, AMD, or Qualcomm processors could impact the rollout of these new machines. The company is currently providing dedicated technical support to help large clients transition to this new hybrid infrastructure, aiming to solidify its position as a key player in the enterprise AI stack.