3 Benefits of On-Device AI

For many, artificial intelligence feels almost inextricable from the cloud.

Since the debut of public large language models) nearly four years ago, business users have interacted with most AI tools via the public cloud, and enterprises have largely relied on cloud resources for their training and inference workloads. But the rise of AI PCs provides another option for certain AI workloads. Some tasks will still require cloud resources or data center infrastructure, of course, but others may be better suited to local processing on user devices.

The latest Microsoft Surface devices are outfitted with Intel^®️ Core^TM Ultra Series 3 processors, Intel’s newest processor platform for AI PCs. For organizations refreshing their Surface fleets, on-device AI capabilities provide these three key benefits:

Reduced reliance on the cloud: As AI becomes more embedded in everyday workflows, organizations may find that some lightweight or latency-sensitive tasks are better handled directly on user devices, rather than in the public cloud. These might include live transcription for calls and meetings, predictive typing and real-time camera effects such as framing and background blur. With the neural processing unit  built into Intel^®️ Core^TM Ultra Series 3 processors, Surface devices can run appropriate AI workloads locally while reserving cloud resources for the workloads that truly require them.

Support for offline AI use cases: Cloud-based tools rely on constant connectivity. This can create challenges for employees who travel frequently, work in the field or need to stay productive in environments with limited internet access. For example, an inspector walking a job site might use on-device AI to help tag photos, flag problems or summarize voice notes. Traveling healthcare workers might use on-device AI to draft visit notes. And surveyors and civil engineers might use AI while offline to organize site photos, extract text from signs and documents or help prepare a draft report from observations collected throughout the day.

Improved security and control: As organizations adopt AI more broadly, many are taking a closer look at where sensitive data is processed. Cloud-based AI services can be highly secure, but some workflows may involve confidential documents, intellectual property or data that must be stored and handled in specific ways for regulatory reasons. With on-device AI capabilities, organizations can reduce the need to send certain data to external cloud services for processing. Local processing does not, of course, eliminate the need for strong security controls. Organizations still need policies for data access, identity and device management, among other safeguards. But by combining Surface devices, Windows 11 security features and AI-capable Intel processors, IT teams can support AI-enabled workflows while maintaining greater control over how and where certain data is handled.

Microsoft Surface devices powered by Intel^®️ Core^TM Ultra Series 3 processors give organizations more flexibility in how they support AI. But an effective device strategy requires more than just choosing the right hardware. IT teams must also determine which users need AI-ready devices, how those devices should be configured, and how policies should be applied to protect data across local and cloud-based environments.

CDW can help organizations put their device strategies into action by supporting device selection, configuration, deployment and lifecycle management. With the right plan in place, businesses can deliver Surface devices that immediately support secure, productive AI workflows.